Study of Environmental Design Thinking in Ancient Vedic Settlement Morphology Using Parametric Techniques

STUDY OF ENVIRONMENTAL DESIGN THINKING IN ANCIENT VEDIC SETTLEMENT MORPHOLOGY USING PARAMETRIC TECHNIQUES

Mohammad Tahajibul Hossain

A thesis submitted in partial fulfillment of the requirement for the degree of

MASTERS OF ARCHITECTURE March 2018

Department of Architecture,

BANGLADESH UNIVERSITY OF ENGINEERING & TECHNOLOGY Dhaka, Bangladesh

CANDIDATE’S DECLARATION

It is declared that this thesis or any part of it has not been submitted elsewhere for the award of degree or diploma.

Signature:

------Mohammad Tahajibul Hossain

Dedicated to my parents

Md. Belal Hossain

Selina Akhter

Abstract

The art and science of planning and designing settlements had been practiced in the Indian subcontinent since the Indo-Aryan period. The codes, standards and regulation regarding the settlement morphology can be found in various Vedas (বেদ), Puranas (পুরাণ), epics, shastras (শাস্ত্র) and treaties, which have been compiled in literary form during the Vedic period, which broadly covers 1500 BCE-1100 CE. The influence of Vedic town—planning practice can be traced back to Babylon in the west and China in the east. Apart from contextual, geological, geographical, economic and environmental aspects, the design considerations also included religious, mythological, physiological, cosmological, genealogical, astrological and astronomical aspects. There were several types of settlements such as Griha (গৃহ), Grama (গ্রাম), Palli (পল্লী), Kheta (বেত), Kharvata (খরেট), Dronamukha (বরাণমুখ), Pattana (পট্টনা), Matamba (মাতম্ব), Nagara (নগর), Rajadhani (রাজধানী), Nigama (ননগম), Samvatta-kotta (সামভট্ট ব াট); divided based on the scale and purpose of the settlement. The streets housed the temporary and permanent shops and open spaces were commonly used for public gathering and programs. The cadastral network of these settlements along with the open spaces were used for trade, commerce and public activities. This research takes into account the environmental variables that can be perceived by means of sensory experience and aims to analyze the environmental performance of the outdoor spaces of Vedic villages based on the morphological and built-environmental parameters as per directions in the codes and regulations of ancient treaties by means of experimental methodology. The results will provide a platform to critically evaluate the environmental design thinking of the Vedic architects by means of causal-comparative study.

Acknowledgements

At first, I would like to thank all of the people who helped, encouraged and supported me during my research work to complete this thesis in due time.

I would like to express my gratitude to my supervisor Dr. Khandaker Shabbir Ahmed, Professor and Head, Department of Architecture, Bangladesh University of Engineering & Technology (BUET) for his tireless efforts and encouragement throughout my research work. He inspired me to explore the avenues of the ancient world and guided me during the entire journey.

I would like to thank Prof. Dr. Farida Nilufar, Sk. Md. Rezwan, Md. Nahid Iqbal, Kumar Biswajit Debnath, Tasneem Tariq and Syed Abu Sufian Kushol for their inspiration.

Finally, I am forever thankful to my family members, especially to my mother for supporting and caring me while I was doing my research.

Table of content

Abstract ...... i Acknowledgements ...... ii List of Figures ...... vi List of Tables ...... x List of Abbreviations ...... xiii

1. Introduction ...... 2 1.1 Preamble ...... 2 1.2 Problem statement ...... 3 1.3 Aim and objectives ...... 4 1.4 Conceptual framework ...... 4 1.5 Overview of research methodology ...... 6 1.6 Scopes and limitations ...... 8 References ...... 9

2. Literature review ...... 11 2.1 Preamble ...... 11 2.2 Elements of morphological dimension in urban planning ...... 11 2.3 Settlement planning in Vedic period ...... 14 2.3.1 Vedic period and ‘second urbanization’ (বেনদ যুগ ও নিতীয় নগরায়ণ) ...... 14 2.3.2 Major literary sources ...... 18 2.3.3 Professionals in Vedic period ...... 20 2.3.4 Units of measurement ...... 21 2.3.5 Socio-economic scenario in Vedic period: ...... 26 2.3.6 Origin of Indian cities: types of settlement ...... 27 2.3.7 The Indo-Aryan village ...... 30 2.3.8 Siting considerations and environmental rationales ...... 38 2.3.9 Street planning ...... 42 2.3.10 Site planning and folk planning ...... 45 2.3.11 Building bye-laws ...... 48

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2.4 Examples ...... 51 2.4.1 Case study: Jaipur ...... 51 2.4.2 Settlements in Bengal ...... 56 2.5 Contemporary principles of city planning by Vitruvius ...... 59 2.6 Climatic Imperatives ...... 61 2.6.1 Thermal comfort ...... 61 2.6.2 Determinants of thermal comfort in outdoor urban environment ...... 62 2.7 Critical findings from literature review ...... 64 References ...... 67

3. Simulation and analysis ...... 72 3.1 Preamble ...... 72 3.2 Methodology for simulation ...... 72 3.2.1 Microclimate of Dhaka ...... 74 3.2.2 Sunshine hours and sun path diagram ...... 75 3.2.3 Sky condition ...... 77 3.2.4 Annual wind flow condition ...... 78 3.3 Selection of simulation tools...... 79 3.4 Selection of case diagrams ...... 80 3.5 Axial connectivity study and selection of case-streets: ...... 88 3.6 Introducing built-environment parameters for three-dimensional model generation ...... 90 3.7 Insolation analysis ...... 96 3.7.1 Formation of 3d model for computer simulation ...... 96 3.7.2 Time-basis and other parameters ...... 96 3.8 Insolation analysis results ...... 97 3.8.1 Brahmavithi (BrV) ...... 98 3.8.2 Mahakalavithi (MhV) ...... 107 3.8.3 Rajapatha (RP) ...... 115 3.8.4 Vamanapatha (VP) ...... 123 3.8.5 Key observations from insolation analysis ...... 131 3.9 Shadow analysis ...... 132

3.9.1 Formation of 3d model for computer simulation ...... 132 3.9.2 Time-basis and other parameters ...... 132 3.10 Shadow analysis results ...... 133 3.10.1 Brahmavithi (BrV) ...... 133 3.10.2 Mahakalavithi (MhV) ...... 138 3.10.3 Rajapatha (RP) ...... 143 3.10.4 Vamanapatha (VP) ...... 148 3.10.5 Average shading condition ...... 153 3.11 Wind flow analysis ...... 157 3.12 Wind simulation results ...... 158 3.13 Performance indicator ...... 165 3.13.1 Solar insolation ...... 166 3.13.2 Overshadowing percentage ...... 169 3.13.3 Wind velocity ...... 172 3.13.4 Performance indicator calculation ...... 173 3.14 Causal-comparative analysis ...... 175 3.14.1 Cadastral pattern and orientation ...... 176 3.14.2 Height to width ratio ...... 178 3.15 Summary ...... 182 References ...... 183

4. Discussion and conclusion ...... 186 4.1 Preamble ...... 186 4.2 Key observations ...... 186 4.3 Evaluation of environmental rationales ...... 194 4.4 Suggestion for future research ...... 197 4.5 Conclusion ...... 197 References ...... 199

Appendix A……………………………………………………………...…………200 Appendix B……………………………………………………………...…………206 Appendix C………………………………………………………………………...227

List of Figures

Figure 1.1: Conceptual Framework 5

Figure 1.2: Flow diagram of research process 7

Figure 2.1 (a): Approximate extent of Vedic culture in the Early Vedic Period 17 (1700-1100 BCE) Image Source: Wikipedia Figure 2.1 (b): Approximate extent of Vedic culture in the Late Vedic Period 17 (1100-500 BCE) Image Source: Wikipedia

Figure 2.1(c) The Mahajanapadas mentioned in Jain Sutra during the second 18 urbanization (Image Source: Rahman, 2012) Figure 2.2: Major units of measurement used by this research 25

Figure 2.3: Modulor Man by Le Corbusier 25

Figure 2.4: Diagrams for Vedic villages 37,38

Figure 2.5: Various Length to width ratio of settlements suggested in Vedic 41 literature with same area Figure 2.6: Hierarchy of streets in Vedic villages 43

Figure 2.7: A Street Market Scene in India by Edwin Lord Weeks (1887) showing 45 outdoor commercial activity Figure 2.8: Diagrams of Padavinyasa: Chandita and Paramasayika (Dutt 1925) 47

Figure 2.9: Formation of Axis in Jaipur (Nongrum, 2008) 52

Figure 2.10 (a): Order of streets within the second chowkri from the right at south 54 of Jaipur (Nongram, 2008) Figure 2.10 (b): Zoning within the second chowkri from the right at south of Jaipur 54 (Nongram, 2008) Figure 2.10 (c): Section of main street (Nongram, 2008) 54

Figure 2.11: Built and Unbuilt areas in the second chowkri from the right at south 55 of Jaipur Figure 2.12: Archeological excavation at Wari-Bateshwar 59

Figure 2.13: Archeological excavation at Bhitargarh 59

Figure 2.14: Diagram of Wind, from the edition of vitruvius by fra giocondo, 60 venice, 1511 (Morgan, 1914) Figure 3.1: Methodology for Simulation and Analysis 73

Figure 3.2: Hourly solar radiation averaged by month for TRYs, Dhaka (source: 74 U.S. Department of Energy, 2008).

Figure 3.3: Average monthly hours of sunshine of Dhaka over the year (Source: 76 World Weather Climate and Information data report, 2015)

Figure 3.4: The sun path diagram of Dhaka, Bangladesh (Source: SUNTOOL - 76 Solar Position Calculator, 1998). Figure 3.5: Sky condition of Dhaka city (Ahmed, 1987). 77

Figure 3.6: Monthly average cloud cover and monthly average sunshine hours in Dhaka (Source: Bangladesh Meteorological Department, Dhaka, 2005; cited 77 from: Rahman, 2007). Figure 3.7(a): Average wind direction of Dhaka city (January 2000 - December 78 2008) [28] Figure 3.7(b): The duration of the prevailing wind of Dhaka city [24] 79

Figure 3.8: Settlement Pattern for Dandaka with different length to width ratio 83

Figure 3.9: Settlement Pattern for Sarvatobhadra with different length to width 84 ratio Figure 3.10: Settlement Pattern for Nandyavarta with different length to width 85 ratio Figure 3.11: Settlement Pattern for Swastika with different length to width ratio 86

Figure 3.12: Settlement Pattern for Prastara with different length to width ratio 87

Figure 3.13: Selected case streets from axial connectivity analysis 92

Figure 3.14: Randomly selected blocks in Jaipur having inconsistent porosity 94

Figure 3.15: Three dimensional model of built environment 95

Figure 3.16: Insolation Analysis using Autodesk Ecotect 98

2 Figure 3.17 Average Cumulative Value of Insolation Level (Wh/(m .day)) for BrV 100,101 of all the settlement patterns .2 Figure 3.18: Average Daily Insolation (Wh/(m .day)) within the transverse 105,106 section of BrV for all the settlement patterns 2 Figure 3.19 Average Cumulative Value of Insolation Level (Wh/(m .day)) for MhV 108,109 of all the settlement patterns .2 Figure 3.20: Average Daily Insolation (Wh/(m .day)) within the transverse 113,114 section of MhV for all the settlement patterns 2 Figure 3.21 Average Cumulative Value of Insolation Level (Wh/(m .day)) for RP 116,117 of all the settlement patterns .2 Figure 3.22: Average Daily Insolation (Wh/(m .day)) within the transverse 121,122 section of RP for all the settlement patterns 2 Figure 3.23 Average Cumulative Value of Insolation Level (Wh/(m .day)) for VP 124,125 of all the settlement patterns

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.2 Figure 3.24: Average Daily Insolation (Wh/(m .day)) within the transverse 129,130 section of VP for all the settlement patterns Figure 3.25: Overshadowing percentage (%) of all the BrVs with hours 137,138

Figure 3.26: Overshadowing percentage (%) of all the MhVs with hours 142,143

Figure 3.27: Overshadowing percentage (%) of all the RPs with hours 147,148

Figure 3.28: Overshadowing percentage (%) of all the VPs with hours 152,153

Figure 3.29(a): Average overshadowing percentage (%) of all the types of street 154 with hours for 4th April Figure 3.29(b): Average overshadowing percentage (%) of all the types of street 155 with hours for 21st June Figure 3.29(c): Average overshadowing percentage (%) of all the types of street 156 with hours for 22nd December

Figure 3.30: Wind flow simulation in a virtual wind tunnel using ‘Autodesk Flow 158 Design’ Figure 3.31: Output wind velocity in the streets of all the diagrams 159

Figure 3.32: Wind Flow simulation of the three diagrams of Dandaka 160

Figure 3.33: Wind Flow simulation of the three diagrams of Sarvatobhadra 161

Figure 3.34: Wind Flow simulation of the three diagrams of Nandyavarta 162

Figure 3.35: Wind Flow simulation of the three diagrams of Swastika 163

Figure 3.36: Wind Flow simulation of the three diagrams of Prastara 164

Figure 3.37: Comparison between east-west (BrV and RP) and north-south (MhV 177 and VP) oriented streets Figure 3.38(a): Descending scale from highest to lowest PI (0-1) for 180 Overshadowing Percentage of RP with H/W ratio Figure 3.38(b): Descending scale from highest to lowest PI (0-1) for 181 Overshadowing Percentage of VP with H/W ratio Figure 3.39: PI value of VP and RP in order from highest to lowest 182

Figure 4.1(a): Matrix of individual and cumulative percentage score of Solar Insolation, Overshadowing Percentage and Wind velocity of every street for the 189 diagram Dandaka along with H/W ratio, orientation of streest and length to width ratio of settlement

Figure 4.1(b): Matrix of individual and cumulative percentage score of Solar Insolation, Overshadowing Percentage and Wind velocity of every street for the 190 diagram Sarvatobhadra along with H/W ratio, orientation of streest and length to width ratio of settlement

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Figure 4.1(c): Matrix of individual and cumulative percentage score of Solar 191 Insolation, Overshadowing Percentage and Wind velocity of every street for the diagram Nandyavarta along with H/W ratio, orientation of streest and length to width ratio of settlement

Figure 4.1(d): Matrix of individual and cumulative percentage score of Solar Insolation, Overshadowing Percentage and Wind velocity of every street for the 192 diagram Swastika along with H/W ratio, orientation of streest and length to width ratio of settlement

Figure 4.1(e): Matrix of individual and cumulative percentage score of Solar Insolation, Overshadowing Percentage and Wind velocity of every street for the 193 diagram Prastara along with H/W ratio, orientation of streest and length to width ratio of settlement

Figure 4.2: Shaded Arcades in Jaipur 196

List of Tables

Table 2.1: Units of measurement according to Mānasāra (aṅgula aka angula, n.d.) 23

Table 2.2: Units of measurement according to Vāyu Purāṇa (aṅgula aka angula, 23 n.d.) Table 2.3: Major units of measurement used by this research 24

Table: 2.4 Classification of Brahman villages according to Mayamata 31,32

Table 3.1: Climate data of Dhaka (Khan, 2005; cited from Rahman, 2007). 75

Table 3.2 Sky condition with respect to cloud cover over a year round. (Source: 78 Climatic Division, Bangladesh metrological department, Dhaka, 2005). Table 3.3: Connectivity values of the highest connected streets 91

Table 3.4: Properties of Building Materials 93

Table 3.5: Built-Environment Parameters for all the case diagrams 94

Table 3.6: Basic Information for Insolation Analysis 96

Table 3.7: Time-basis and other parameters 97

Table 3.8: Average Cumulative Value of Insolation Level (Wh/(m2.day)) for BrV of 99 all the settlement patterns Table 3.9(a): Average Daily Insolation (Wh/(m.2 .day)) within the transverse 102 section of BrV for 4th April Table 3.9(b): Average Daily Insolation (Wh/(m.2 .day)) within the transverse 103 section of BrV for 21st June Table 3.9(c): Average Daily Insolation (Wh/(m.2 .day)) within the transverse section 104 of BrV for 22nd December Table 3.10: Average Cumulative Value of Insolation Level (Wh/(m2.day)) for MhV 107 of all the settlement patterns. Table 3.11(a): Average Daily Insolation (Wh/(m.2 .day)) within the transverse 110 section of MhV for 4th April Table 3.11(b): Average Daily Insolation (Wh/(m.2 .day)) within the transverse 111 section of MhV for 21st June Table 3.11(c): Average Daily Insolation (Wh/(m.2 .day)) within the transverse 112 section of MhV for 22nd December Table 3.12: Average Cumulative Value of Insolation Level (Wh/(m2.day)) for RP of 115 all the settlement patterns. Table 3.13(a): Average Daily Insolation (Wh/(m.2 .day)) within the transverse 118 section of RP for 4th April Table 3.13(b): Average Daily Insolation (Wh/(m.2 .day)) within the transverse 119 section of RP for 21st June

Table 3.13(c): Average Daily Insolation (Wh/(m.2 .day)) within the transverse 120 section of RP for 22nd December Table 3.14: Average Cumulative Value of Insolation Level (Wh/(m2.day)) for VP of 123 all the settlement patterns. Table 3.15(a): Average Daily Insolation (Wh/(m.2 .day)) within the transverse 126 section of VP for 4th April Table 3.15(b): Average Daily Insolation (Wh/(m.2 .day)) within the transverse 127 section of VP for 21st June Table 3.15(c): Average Daily Insolation (Wh/(m.2 .day)) within the transverse 128 section of VP for 22nd December Table 3.16: Basic Information for Shadow Analysis 132

Table 3.17: Time-basis and other parameters 132

Table 3.18(a): Overshadowing percentage (%) of all the BrVs with hours for 4th 134 April Table 3.18(b): Overshadowing percentage (%) of all the BrVs with hours for 21st 135 June Table 3.18(c): Overshadowing percentage (%) of all the BrVs with hours for 22nd 136 December Table 3.19(a): Overshadowing percentage (%) of all the MhVs with hours for 4th 139 April Table 3.19(b): Overshadowing percentage (%) of all the MhVs with hours for 21st 140 June Table 3.19(c): Overshadowing percentage (%) of all the MhVs with hours for 22nd 141 December Table 3.20(a): Overshadowing percentage (%) of all the RPs with hours for 4th 144 April Table 3.20(b): Overshadowing percentage (%) of all the RPs with hours for 21st 145 June Table 3.20(c): Overshadowing percentage (%) of all the RPs with hours for 22nd 146 December Table 3.21(a): Overshadowing percentage (%) of all the VPs with hours for 4th 149 April Table 3.21(b): Overshadowing percentage (%) of all the VPs with hours for 21st 150 June Table 3.21(c): Overshadowing percentage (%) of all the VPs with hours for 22nd 151 December Table 3.22 (a): Average overshadowing percentage (%) of all the types of street 154 with hours for 4th April Table 3.22(b): Average overshadowing percentage (%) of all the types of street 155 with hours for 21st June

Table 3.22(c): Average overshadowing percentage (%) of all the types of street 156 with hours for 22nd December Table 3.23: Basic information for wind simulation 157

Table 3.24: Output wind velocity in the streets of all the diagrams 159

Table 3.25(a): Numeric Rating Value of All the streets in terms of Solar Insolation 167 level for 4th April. Table 3.25(b): Numeric Rating Value of All the streets in terms of Solar Insolation 168 level for 21st June. Table 3.25(c): Numeric Rating Value of All the streets in terms of Solar Insolation 169 level for 22nd December Table 3.26(a): Numeric Rating Value of All the streets in terms of Overshadowing 170 Percentage for 4th April. Table 3.26(b): Numeric Rating Value of All the streets in terms of Overshadowing 171 Percentage for 21st June. Table 3.26(c): Numeric Rating Value of All the streets in terms of Overshadowing 172 Percentage for 22nd December Table 3.27: Numeric Rating Value of All the streets in terms of Wind Velocity 173

Table 3.28: Performance Indicator values for all the settlement patterns 174

Table: 3.29: Settlement patterns in descending order based on performance 175 indicator values Table 3.30: Comparison between north-south and east-west oriented streets 177

Table 3.31: PI for RP and VP along with H/W ratio 178

Table 3.32(a): Descending scale from highest to lowest PI (0-1) for Overshadowing 179 Percentage of RP with H/W ratio Table 3.32(b): Descending scale from highest to lowest PI (0-1) for Overshadowing 180 Percentage of VP with H/W ratio Table 3.33: PI value of RP+VP in a scale of 0-3 181

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List of Abbreviations

AGS Architectural Graphics Standards ASHRAE American Society of Heating, Refrigeration and Air Conditioning Engineers BCE Before Common Era BRE Building Research Establishment

BrV Brahmavithi CE Common Era CIBSE Chartered Institution for Building Services Engineers GMT Greenwich Mean Time In Insolation ISO International Organization for Standardization MhV Mahakalavithi MngV Mangalavithi NE North-East NW North-West OP Overshadowing Percentage PI Performance Indicator RH Relative Humidity RP Rajapatha SE South-East SI International System of Units SW South-West UCL University College London VP Vamanapatha WV Wind Velocity

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Chapter 1 INTRODUCTION

1. Introduction

1.1 Preamble

‘Civilization’ can be stated as an advanced state of human society which began with a complex social system. The system can be characterized with the storage of surplus food, emergence of ruling class, specialized occupation and division of labor, social stratification, development of writing, standardization of measures and increased trade (Brown, 2014). In its traditional sense, ‘civilization’ is a product of human evolution where the cities emerge (Wei, 2011). Sir Bannister Fletcher associated ‘true civilization’ with economic and social development which allowed the establishment of towns and cities where people engaged in trade, industry and professional pursuits (Fletcher, 1961).

Designing cities and towns at the dawn of civilization required a complex set of knowledge. Among the earliest cities, the Indus valley civilization displayed a wider understanding of the dynamics of urban design and infrastructure facilities (Ching et al., 2011). These cities sustained over a thousand years which implies that these settlements overcame a broad range of challenges that evolves from housing a large number of population. In contrast to that, the European cities failed to mitigate epidemics when a lot of people started finding works in the cities during the industrial revolution (Vollmar, 1994).

After the demise of the Indus Valley civilization, the Indo-Aryans entered the subcontinent and brought about the Vedas (Ching et.al. 2011). During the early and late Vedic period, a number of Vedic literary sources were composed which provides elaborate categorizations of the cities and settlements, hierarchy of the streets and their network system, principles of site planning and folk planning (Dutt, 1925). The design decisions were based on geographical, geological, economic, environmental, religious, mythological, physiological, cosmological, genealogical, astrological and astronomical aspects (Dutt, 1925). Historical and archaeological evidences provides us with a number of fortified settlements that existed during the second urbanization in an air of Vedic religious and philosophical paradigm (Rahman, 2012).

Among the elements of morphological dimensions of urban design, the cadastral pattern is the most permanent one (Carmona, et al., 2003). Considering the characters of traditional settlements, the streets in a city are the open spaces as opposed to the urban blocks which are used for vehicular and pedestrian circulation as well as routes for trade and commerce (Carmona, et al., 2003). The Vedic codes for city planning provides specific instructions for the streets to be used for trade as well as public spaces. The scriptures give elaborate guidance for providing public squares and incorporating plantation for public interest (Dutt, 1925).

The Vedic treaties contains both direct and indirect suggestions regarding the environmental components. Instructions regarding the environmental features are largely focused on the natural forces that are perceptible by means of human senses, such as the sun, wind and rain along with a variety of siting considerations (Dutt, 1925). This research aims to identify that whether the morphological and built-environment parameters suggested in these literary sources concerned the human comfort in the outdoor spaces which is largely governed by the streets. Solar insolation, shadow condition and wind velocity, three essential components of thermal comfort in the outdoor spaces will be studied in parametric manner to evaluate the environmental rationale of the Vedic architects.

This chapter will continue with the problem statement of the research followed by the aims and objectives. Then the conceptual framework and the overview of the research methodology will be presented. The chapter will conclude with a brief description of the scopes and limitations of the research.

1.2 Problem statement

The research questions were formulated in the following order:

a) What were the morphological and built-environment parameters that were considered in the Vedic literary sources that essentially formed the outdoor spaces, more specifically the streets? b) What were the environmental rationales that had been taken into consideration for planned settlements by the civic architects in Vedic era?

c) What are the environmental performance of the outdoor spaces of Vedic settlements and do the results complement the environmental design thinking suggested in the Vedic treaties?

1.3 Aim and objectives

Specific aim: The aim of this research is to comparatively analyse the environmental performance of the outdoor spaces of the Vedic villages generated with varying morphological and built—environment parameters as per suggestions in the codes and strategies in ancient Vedic literary sources using modern simulation techniques in order to evaluate the environmental thinking of ancient architects.

Objectives: a. To generate scale scenarios of the built—environment according to the settlement morphology and building bye laws of ancient Vedic literary sources. b. To study the environmental performance in terms of solar insolation, shadow analysis and wind velocity of the outdoor spaces of the generated settlements using parametric techniques. c. To analyse and compare the environmental performances of different settlement patterns against the built–environment parameters and also to establish a correlation to derive at a strategic suggestion.

Possible outcome: Comparative analysis of the environmental performances of settlements with different plot pattern, street orientation and height to width ratio will provide a basis for strategic guideline to achieve thermally comfortable outdoor spaces within a settlement. The results will also help to evaluate the design decisions of the Vedic planning scheme.

1.4 Conceptual framework

This particular research follows an experimental method to identify the dependent variables which are solar insolation, wind velocity and shadow conditions; three essential components for determining environmental performance, by means of parametric simulation technique. The experiment examines various combinations of the independent variables; consisting of morphological and built environment parameters

Figure 1.1: Conceptual framework of the Vedic villages. The morphological parameters considered for research are street pattern, plot pattern and length to width ratio of the settlement whereas the built- environment pattern includes bounding condition, height of the plots or blocks and material. Contextual data regarding the location and time is also relevant for this

5 research and crucial for generating simulation data. The research will further carry on discussions regarding the relationship between the independent and dependent variables by means of causal-comparative study. The components of conceptual and operational level of the research framework has been shown in figure: 1.1.

1.5 Overview of research methodology

The various stages of the research methodology has been describes as follows:

The research began with literature survey, which included published data like research papers, books, standards, and websites in order to:

 Explore state of the potential gaps of the codes, guidelines, rules and regulations on settlement planning and design as per suggested in ancient Vedic treaties.  Understand the possible environmental rationale for deriving at the codes, guidelines and siting considerations; and identify the key parameters to determine the environmental performance, which in case of this research are solar insolation, shadow condition and wind velocity.  Determine the morphological parameters such as settlement area and length to width ratio and street pattern and width for the settlements.  Analyse case studies against the codes and standards suggested in the literary sources in order to find out data regarding the built-environment parameters, such as bounding condition, height of urban plot and blocks and material.

The next step is sampling where the scale of the settlement will be limited to Vedic ‘villages’. Among a number of ‘village’ patterns mentioned in the literary sources, the ones to be studied are selected based on the following criteria: having orthogonal diagrams with a suggested orientation. Diagrams with similar road pattern and block division will be considered as one.

The climatic context has been selected to be Dhaka, as the Tropic of Cancer covers the land area of Indian subcontinent under Vedic influence in a common reference line. Also, the research aims to evaluate the simulation data with ancient codes against current settlement pattern in a tropical city.

Settlement Patterns has been generated with the diagrams and morphological parameters as per described in the literary sources using different proportions keeping

6 the same area. Axial connectivity analysis on these patterns will narrow down the study area to more connected outdoor spaces which is basically the streets for this particular research.

Figure 1.2: Flow diagram of research process

Built-environment has been produced by introducing parametric information regarding height of the plots or blocks, bounding condition and building materials on the previously generated settlement pattern. Information regarding building height and material are found from both the literature review and case studies. Suitable three- dimensional model has been generated for relevant environmental simulation tool.

The next step includes conducting environmental simulation to derive the data regarding:

 Solar insolation: average daily incident solar radiation in outdoor ground surface.

 Shadow analysis: overshadowing percentage of the outdoor ground surfaces casted from the built masses.  Wind profile: average wind velocity in the selected outdoor area at human height.

Lastly, discussion and findings will be placed regarding the comparative analysis and correlation between built environment parameters and simulation results of environmental variables in contrast with the variables directly responsible for thermal comfort.

The flow diagram of the research process has been presented in figure 1.2.

1.6 Scopes and limitations

Scopes:

The research works concentrates on the cadastral network as morphological parameter and height to width ratio and orientation as built environment parameter for determining the environmental performance in the context of Dhaka within its scope. The performances of each individual environmental variables will be compared in both isolated and comprehensive manner.

Limitations:

• The research does not consider the demographic data for generating settlement morphology

• Climatic data of the concerned period is not considered.

• The Vedic settlement morphology and built—environment was designed based on religious, mythological, physiological, environmental, cosmological, genealogical, astrological and astronomical variables. This study focuses only on environmental variables.

• Vegetation was not considered in the built—environment generation procedure.

• Material and context for the environmental simulation study is limited.

References

Brown, C (2014), Agrarian Civilization, Newsela [accessed on: 10 March, 2018] Available

Carmona, M., Heath, T., Oc, T., Tiesdell, S. (2003), Public Places – Urban Spaces: The Dimensions of Urban Design, Architectural Press, Oxford.

Ching D. K., Jarzombek, M., Prakash V., (2011), A Global History of Architecture, John Wiley & Sons Inc.

Dutt, B. B., (1925), Town Planning in Ancient India, New Asian publishers.

Fletcher, B., (1961), A History of Architecture (17th Edition), Athelon Press London

Rahman, S.M., Pathan, M.H. (2012), উয়ারী েটটশ্বরঃ বে টের সন্ধাটন, Prothoma.

Vollmar, L., (1994), ‘The effects of epidemics on the development of English law from the black death through the Industrial Revolution’, Journal of Legal Medicine, 15, pp. 385-419.

Wei, R., (2011), Civilization and Culture, Globality Studies Journal, issue 24

Chapter 2 LITERATURE REVIEW

2. Literature review

2.1 Preamble

This chapter explores the potential knowledge gaps between the independent and dependent variables of this research. From the previous chapter, it can be seen that the principle component of this research are concerned with the characteristics of streets as well as open spaces of Vedic settlements as an element of morphological dimension and the environmental variables that had been considered by the Vedic architects for outdoor spaces. This chapter will try to establish that the cadastral network, being the most permanent morphological element of a traditional settlement had been used as public spaces apart from serving as circulation channels. Then the chapter will elaborate on the Vedic city planning principles which will include the discussion regarding the span of Vedic period, major literary sources that describes urban planning, the professionals engaged in architecture and urban planning, units of measurements and socio-cultural scenario etc. Types of settlements with elaborate description of Vedic villages along with siting considerations, environmental rationales and streets planning will be presented. The site planning and building bye-laws during the Vedic period will indicate the extent of their urban design knowledge. Examples of settlements which either belonged to the Vedic period or followed their principles will be described. The principles of Vitruvius will also be brought upon in brief to compare the similarities or dissimilarities. After that, the chapter will discuss the determinants of outdoor thermal comfort to find out which variables to be considered for this study. Key findings presenting the gist of the chapter will establish a relationship between the variables for carrying out the study and analyze the environmental performances.

2.2 Elements of morphological dimension in urban planning

This section will try to define the character of streets as a morphological elements of Vedic as well as traditional settlements in accordance with modern world view of urban morphology. Urban morphology today, deals with the form and shape of settlements. The evolution and change in traditional urban spaces was the primary scope of work in this field. Eminent morphologist Conzen considered land uses, building structures, plot pattern and street pattern as the key elements of urban morphology and emphasized the

11 difference of stability of these elements (Carmona et al., 2003). Keeping in mind that this research is relevant to traditional urban spaces, these elements are briefly discussed as followed. a. Land uses Land uses are relatively temporary compared to the other elements. Current uses of a land may lead to redevelopment, erection of new buildings, amalgamation of plot and less possibly subdivision of plot and changes in the street pattern. Existing buildings in a settlement can adapt and convert to a changed land use (Carmona et al., 2003). b. Building structures Progressive changes or cycles of Building development is quite recognizable within a plot. Historic, iconic, religious and public buildings usually lasts longer than the ordinary ones as they are significant in terms of symbolism, design, construction, ornamentation and financial investment. Other buildings survive if they can adapt to changing land uses in various circumstances and environment over their lifetime; a quality which is termed as ‘Robustness’ (Carmona et al., 2003). c. The plot pattern Urban blocks or cadastral units are usually subdivided into plots or lots. The plots generally have frontage on to the street and a shared boundary at their rear and be placed back to back. The plots may have a service alley at the rear. ‘Through’ plots with frontage onto a principle street at each end are quite rare. As plots are bought and sold, the boundaries can change over time. Plots may be subdivided or amalgamated. In extreme cases, two or more urban blocks may be amalgamated with the intervening streets being privatized or built over. Although, persisting in several old settlements, such changes may remove the evidence of earlier forms of the blocks (Carmona et al., 2003). d. The cadastral (street) pattern The cadastral pattern is the layout of urban blocks and the public spaces or movement channel between them which can be termed as ‘Public Space Network’. Both the urban blocks and spaces define and complement each other. Current plot division, buildings and land uses of a settlement may be overwritten but do not get erased completely. This

12 process is called ‘Palimpsest’. Street and space patterns of older times tends to remain as fragments in the current patterns (Carmona et al., 2003).

Cadastral patterns containing many small urban street blocks have a ‘fine’ urban grain and the ones with fewer larger blocks have a ‘coarse’ urban grain. Settlements with fine urban grains offers greater choices of routes both physically and visually.

In terms of geometric shapes, the cadastral pattern can be simply divided into two categories: regular or ‘ideal’ grids and organic or ‘deformed’ grids. The shape of the grids is relevant more to ensure visual permeability. Physical permeability does not depend on the grid shape (Carmona et al., 2003).

Organic grids are usually found in regions with a long history of incremental urbanization as they were most likely to be generated from the pedestrian movement and local topography, built as integral parts of the spatial configuration rather than as through routes and evolved with use. Regular grids are usually planned and contain geometric discipline. Throughout history of civilization, we can find rectilinear cadastral patterns in Europe, Middle East and India. Regular grids have often been considered as monotonous while the deformed grid have a picturesque character due to their changing spatial enclosure. However, Rybczynski argues that regular grids not necessarily lacks poetic characters; they require a thorough relationship with the context and natural landscape (Carmona et al., 2003).

Public space network

The cadastral (street) pattern creates the public space network of an urban area. Apart from facilitating physical and visual permeability, public space network accommodates within itself the overlapping realms of ‘movement space’ and ‘social space’ (Carmona et al., 2003). The latter one refers to outdoor space where people can engage themselves in economic, social and cultural activities. Social space is an integral part of the public realm. To conceive street as a social space, pedestrian movement needs to be facilitated. Pedestrian movement and interpersonal relationship have a symbiotic relationship. In contrast, vehicular movement only accommodates circulation (Carmona et al., 2003).

In ancient times, the principle modes of transportation were by foot and non-motorized vehicles. Hence, the movement space and social space had considerable overlap.

Motorized vehicles have incrementally compartmentalized the vehicular and pedestrian movement space (Carmona et al., 2003). Public spaces are now dominated by cars and social aspect of the street has been suppressed in favor of movement and circulation.

The block patterns, street patterns, basic infrastructure and other relative permanent components of an urban area forms the ‘Capital Web’, as described by David Crane (Carmona et al., 2003). Buchanan argued that the movement network, the services underneath the surfaces, the monuments and civic buildings within and adjacent to and the images they structured in the mind are the relatively permanent parts of a settlement (Carmona et al., 2003). Within this framework, individual buildings, land uses and activities keep changing. The capital web thus structures a city, its land uses and land values, the density of developments and the intensity of their use, and the way the inhabitant move through, see and remember the city as well as interact with their fellow citizens. Some essence of the identity of a city retains over time through the capital web.

From the above discussion it is eminent that in case of traditional or ancient cities, the street or cadastral network, being a key component of ‘capital web’, was used as a public space which housed outdoor commercial and social activities.

2.3 Settlement planning in Vedic period

This section will describe the span of Vedic period and its influence over time along with the description of major literary sources, professionals, measurement standards followed by various aspects of settlement planning.

2.3.1 Vedic period and ‘second urbanization’ (বেনদ যুগ ও নিতীয় নগরায়ণ)

The Vedic period or Vedic Age can be broadly marked as the period starting from the end of Indus-valley civilization (নসন্ধু সভযতা) and Aryan (আযয) invasion to the beginning of ‘Second Urbanization’ or ‘Historic period’, which approximately covers 1500-600 BCE. The term Vedic (বেনদ ) originates from the term ‘Vedas’ (বেদ), which are sacred texts, which can be considered as ‘historical’ (McClish et al., 2012). The Vedic period can be subdivided into Early Vedic Period and Later Vedic Period.

Early Vedic Period (1500-1100 BCE) mostly denotes the migration and settlement of the Aryans, who spoke Indo-European language into the Indian subcontinent

14 particularly in the North-Western part. Archaeological and Epigraphic evidences suggest the migration of Kassites in Mesopotamia and West Central Asia in approximately 1760 BCE; a race who rode horse and chariots and bore Indo-European names. A treaty from about 1400 BCE between the Hitties, who occupied Anatolia from the beginning of 2nd millennium BCE, reveals the similar names of Gods that appear in the Rig Veda (ঋগ্বেদ). Similar evidences are also found in Central Asia, Southern Russia and Upper Egypt. Historians suggest that in course of worldwide migration, after occupying the Iranian Plateau, these Aryans migrated to northern India and settled in the Sapta Sindhu (সপ্ত নসন্ধু) region, extending from the Kabul River in the north to the Sarasvati (স্বরস্বতী) and upper Ganges-Yamuna Doab (গঙ্গা-যমুনা বদায়াে) in the south (Spear et al., 2012).

These Aryan immigrants involved in violent clashes with the local inhabitants, known as the Dravidians in order to establish supremacy. In the Vedas the locals are referred as Dasas (দাস) and Dasyus (দসুয), who do not perform sacrificial rituals or obey the commandments of the Gods. However, some scholars connect these terms to Iranian tribes Dahae and Dahyu, who arrived in the subcontinent before the Aryans (Singh, 2008; Kulke et al., 1998). During Early Vedic Period, the Vedas were being compiled in written form. Oiteria Brahman (ঐটতনরয় ব্রাহ্মণ) and Manavadharmmashastra (মানেধমযোস্ত্র), two ancient scriptures contemporary to the Vedas, mention the nation of Pundra (পুন্ড্র). If this refers to the city of Pundravardhana (পুন্ড্রেধযন), then it is evident that there were settlement of locals in the North Bengal during this era. The term ‘Banga’ (েঙ্গ) as a place is first found in Oiteria Aranyak (ঐটতনরয় আরণয ), a subdivision of the Vedas (Bandyopadhyay, 1914)

In Later Vedic Period (1100-500 BCE), the Vedic society transitioned from semi- nomadic life to an agrarian settlement and extended along the western Gangetic plains (গাটঙ্গয় সমতলভূনম) (Geoffrey, 2010). The invention of iron axes and ploughs further empowered their expansion. The surplus food and specialized professions lead to trade and commerce and eventually the establishment of permanent settlements. The emergence of social caste system, Varna (েণয), can be observed at this stage (Kulke et al., 1998). A number of kingdoms and settlements are found in the texts, popular among them are Kuru ( ু쇁), Panchala (পাঞ্চাল) and Videha (নেটদহ) (Witzel, 1989). Archaelogical

15 data for this period shows a two-tiered settlement patter in the Ganges valley, which suggests simple chiefdoms. The Kurukshetra ( ু쇁টেত্র) district displays a three-tiered hierarchy, which still, cannot be considered to be urbanized. Urbanized state level society with four tier of site sizes, which includes large towns and fortified cities can be found after 600 BCE (Erdosy, 1995).

The ‘Second Urbanization’ or ‘Historic Period’, terms used by archaeologists and historians, spans between 600-100 BCE, when the Mahajanapadas (মহাজনপদ) emerged as a result of consolidation of political units into large kingdoms. Trade and commerce as well as the process of urbanization was thriving (Olivelle, 1998). According to Boudhha Sutra (বেৌদ্ধ সূত্র), the sixteen Mahajanapadas were Kashi ( ােী), Koshala (ব ােল), Magadha (মগধ), Anga (অঙ্গ), Brijji (েৃনি), Malla (মল্ল), Chedi (বেনদ), Batsya (েৎসয), Kuru ( ু쇁), Panchala (পাঞ্চাল), Matsya (মৎসয), Surasena (সুরটসন), Asmak (অশ্ম, ) Avanti (অেন্তী), Gandhara (গান্ধার) and Kamboja ( টম্বাজ). According to Jain Sutra (বজন সূত্র), the names are a little different: Anga (অঙ্গ), Banga (েঙ্গ), Magadha (মগধ), Malaya (মলয়), Asmak (অশ্ম, ) Batsya (েৎসয), Kaccha ( চ্ছ), Rarha (রাঢ়), Pundra (পুন্ড্র), Brijji (েৃনি), Malla (মল্ল), Kashi ( ােী), Koshala (ব ােল), Abha (অভ) and Sambhutra (সম্ভুত্র). Vedic scriptures provide names of one hundred and seventy five Janapadas (জনপদ). Among them Pundra (পুন্ড্র) and Banga (েঙ্গ) were situated in Bengal. Recently discovered archaeological site at Wari-Bateshwar (উয়ারী েটটশ্বর), which is thought to be the city Gangaridae (গঙ্গাঋনদ্ধ) mentioned by Ptolemy and Megasthenes, evidently belongs to this period (Rahman, 2012).

Approximate Extent of Rig Vedic

Figure 2.1 (a): Approximate extent of Vedic culture in the Early Vedic Period (1700-1100 BCE) Image Source: Wikipedia

Approximate Extent of Major Kingdom

Witzel’s Estimate for late Vedic Period (1995)

Figure 2.1 (b): Approximate extent of Vedic culture in the Late Vedic Period (1100-500 BCE) Image Source: Wikipedia

Figure 2.1 (c): The Mahajanapadas mentioned in Jain Sutra during the second urbanization(Image Source: Rahman, 2012)

Although the Vedic age was followed by Buddhist and Hindu period for about 1500 years, the architectural and city planning principles were being compiled and practiced until the Muslim invasion (Charles, 2012). The extent of these periods are shown in figure 2.1.

2.3.2 Major literary sources

Composed in Vedic Sanskrit (সংস্কৃত), the Vedas are a large body of texts containing liturgical material as well as mythological accounts, poems, prayers and formulas which are considered to be sacred (Violatti, 2013). The Vedas are the oldest scriptures of Hinduism (Jamison et al., 2014). There are four Vedas; the Rigveda (ঋটেদ; knowledge of the hymn of praise), the Yajurveda (যজুটেযদ; knowledge of the sacrificial formulas), the Samaveda (সামটেদ; knowledge of the melodies) and the Atharvaveda (অথেযটেদ; knowledge of the magical formulas) (Violatti, 2013). Each Veda has been subdivided into four major categories: the Samhitas (সংনহতা; mantras and benedictions), the Aranyakas (আরণয ; text on rituals, ceremonies, sacrifices and symbolic-sacrifices), the

Brahmanas (ব্রাহ্মণ; commentaries on rituals, ceremonies and sacrifices) and the Upanishads (উপননষদ; texts discussing meditation, philosophy and spiritual knowledge) (Bhattacharya, 2006). A fifth category is suggested by some scholars, which is the Upasansas (ঊপাসনা; worship) (Bhattacharya, 2006). Based on philological and linguistic evidence, Max Muller suggests the composition span of Rig Veda to be 1700-1100 BCE (Vedas, n.d.). The Samhitas were written during 1700-1100 BCE and the branches of Samhitas are dated to 1000-500 BCE (Johnston, 2014). According to Michael Witzel, the time span is 1500 to 500-400 BCE and 1200 BCE-150 BCE specifically for Atharvaveda (Witzel, 2003). The Sthapatyaveda (স্থাপতযটেদ), a branch which deals with art and architecture is attached to the Atharvaveda (Vasudev, 1998).

The Mahabharata (মহাভারত) and Ramayana (রামায়ণ) are two Sanskrit epics that contains historic description of many ancient cities. Although introduced in oral form much earlier, the period of written compilation for both the epics have been found to be 400 BCE-400 CE (Michael, 20018; Brockington, 1998; Narayan, 2006).

Arthashastra (অথযোস্ত্র) is another Sanskrit compilation of treaties on statecraft, diplomacy, economic policy, military strategy, nature of government, law, ethics, market and trade and last but not the least, city planning. Kautilya (ব ৌনটলয), also known as Vishnugupta (নেষ্ণু巁প্ত) or Chanakya (চাণ য), who was a scholar at Taxila (তেনেলা) and guardian of Emperor Chandragupta Maurya (চন্দ্র巁প্ত বমৌযয), is credited as the author of this book. The book had been composed and expanded between 300-200 BCE (Olivelle, 2013). It was influential until the 12th century CE and was discovered again in 1915 (Charles, 2012).

Shilpa Shastras (নেল্পোস্ত্র; the science of arts and crafts) are manuals for sculpture and Hindu iconography, proportions of sculptured figure, compositions, principles, meanings as well as rules of architecture (Hopkins, 1971). Among a number of treaties that fall under the category of Shilpa Shastras, Mānasāra (মানসারা) and Mayamata (মায়ামাতা) contains principles of town planning. Mānasāra was being compiled in written form between 4th and 5th century CE (Havell, 1915). The compilation date for Mayamata could not be found.

Samarangana Sutradhara (সমরাঙ্গণ সূত্রধর), authored by Maharajadhiraja Sri Bhoja Deva (মহারাজানধরাজ শ্রী বভাজ বদে), who probably ruled over Malwa, situated at the west-central part of India, in the first part of the 11th century CE is an encyclopedic work on classical Indian Architecture. The book discusses town planning, house architecture, temple architecture and sculptural arts in 82 chaptres (Ganapatisastri, 1925).

Apart from the above mentioned treaties, a number of scriptures also discusses principles of city planning and architecture. Among them Mayashastra (মায়াোস্ত্র ; image printing, wall decoration), Agamas (আগামা ; have chapters on other shilpa shastras), Agni purana (অনিপুরাণ; iconography), Brahmanda purana (ব্রহ্মাণ্ডপুরাণ; mostly architecture, some sections on arts), Vastu vidya (োস্তুনেদযা), Vishva karma prakasam (নেশ্বমযা প্র, াে) Vishvakarma shilpa (নেশ্বমযা নেল্প), Vastusutra Upanishad (োস্তুসূত্র উপননষদ) etc. and various Nitishastras (নীনতোস্ত্র), Smritishastras (স্মৃনতোস্ত্র), Grama Vidhana (গ্রামনেধান) and Nagar Vidhana (নগরনেধান) can be mentioned.

2.3.3 Professionals in Vedic period

Several treaties including Mānasāra and Mayamata suggests a mythical genealogy of the artists (Dutt, 1925). From the four faces of Brahma (ব্রহ্মা), the creator, originated the four divine architects Visvakarma (নেশ্বমযা) , Maya (মায়া), Tvashtar (তশ্বর) and Manu (মনু). Their four sons are respectively called Sthapati (স্থপনত), Sutra-grahin (সূত্রগ্রাহী), Vardhaki (েধয ী) and Takshaka (তে ). These four represent the four class of artists and evidently form the guild of architects, consisting the chief architect or master builder, the designer or draftsman, the painter and the joiner (Acharya, 1922). The qualifications of these four class of artists have also been described in the treaties.

The Sthapati is in the rank of director-general and consulting architect and must possess supreme management skills. He must be proficient in all the Vedas and Sastras. He must be able to design and draft. He must be well versed in law, mathematics, history, painting and geography. He must be an expert of the science of architecture. He must be full of resources, and capable of application to all works. He must be acquainted with the use of instruments and should devote himself whole-heartedly to his work (Acharya, 1922).

Apart from these technical skills, the Sthapati also required some physical and moral qualities. He must be of noble descent. He must not have any disease or disability. He must be above committing errors. He must not be malicious or spiteful. He must be content in mind and free from greed. He must be truthful and possess self-control. He must be free from the seven vices (Manu VII, 47-8) viz., hunting, gambling, day- dreaming, blackmailing, addiction to women, etc. Thus, he must be very learned, meritorious, patient worker, dexterous, champion, of large experience, kulina (one who follows ancient custom, possesses modesty, learning, has fame; performs pilgrimage, faithful, peaceful, practices meditation, gives charity) (Acharya, 1922).

Sutra-grahin is the guide (guru, 巁쇁) of the Vardhaki and Takshaka. He must also be proficient in the Vedas and Sastras. He must specialize in measuring and drawing. He must possess general knowledge of all the department of the science and architecture in order to follow the instruction of the master-builder (Acharya, 1922).

Although, Vardhaki also requires to learn the Vedas and Sastras, his area of expertise is painting. Along with Sutra-grahin he should have knowledge regarding accurate measurement. He must also be able to design architectural and sculptural forms from his own conception (Acharya, 1922).

Takshaka, must develop expertise in carpentry and joinery, as well as in clay works. He must follow the instruction of the three superiors i.e. the chief architect, the designer and draftsman and the painter but he must be able to conduct his own works independently. He should have aspiration to rise in rank. As for moral qualities, he should be of good behavior, clever, dexterous, learned in sciences, free from excessive desire for gain and generous to forgive his rivals (Acharya, 1922).

Although these terms appear in the historical documents, no strict divisions have been found among the ranks of Sthapati, Sutra-grahin, Vardhaki and Takshaka during the period of second urbanization (Acharya, 1922).

2.3.4 Units of measurement

As trade and commerce are principal forces for emergence of civilization, standardization of weights and measures became a necessity in order to exchange goods and services. Significant similarities has been discovered since the civilizations of the

Mediterranean and the Oriental region used to trade with each other (Ching et al., 2011). Metal and stone weights have been found amongst the archaeological artifacts all over the world. As this research is concerned with urban design and architecture, the discussion will be limited to units of linear measurement.

Most early civilizations devised their unit of length based on the dimensions of human figure and various parts of it. The Egyptian Cubit was developed around 3000 BCE. One Egyptian Cubit is equivalent to 524 mm or 20.62 inches; derived from the length of the arm starting from the elbow to the extended fingertips (Chisolm et al., 2011). The Babylonian Cubit was termed as Kus, which is equal to 530 mm or 20.9 inches (Chisolm et al., 2011). Basic unit for Greeks was the ‘finger’ which is equal to 19.3 mm or 0.76 inches. 16 fingers constructed a foot which is about 30 cm and 24 fingers equaled 1 Olympic Cubit. Romans had standard Roman Foot which was called Pes, equaled to 296 mm or 11.65 inches (Chisolm et al., 2011). The Chinese initially used the distance from the pulse to the base of the thumb as a unit of measure (Chisolm et al., 2011).

According to ancient Indian literary sources, the unit of linear measurement was also based on human body parts. Aṅgula (আঙ্গুল), a Sanskrit term meaning finger-breadth, is mentioned in Mānasāra II, 40-53 as a unit of measurement (aṅgula aka angula, n.d.). A single Aṅgula is formed with 8 Yava (যে) units or Barley-corn (aṅgula, n.d.). 12 Aṅgula units form a sigle Vitasi (নভতানস/ নভনি) or span (Vitasi, n.d.). 24 Aṅgula units or 2 Vitasi units make a single Hasta (হি) or Cubit (Hasta, n.d.). 26 Aṅgula units make a single Danda (দন্ড). The Aṅgula can be divided into several smaller units (Table 2.1), but for practical purposes it has been considered as the smallest unit for measurement and for this reason it has been specifically highlighted in the texts.

Table 2.1: Units of measurement according to Mānasāra (aṅgula aka angula, n.d.)

UNIT EQUIVALENT UNIT

8 Paramāṇu (পরমাণু) 1 Rathadhūli, chariot-dust

8 Rathadhūli (রথধুনল) 1 Vālāgra, hair-end

8 Vālāgra (োলাগ্র) 1 Likṣā, nit

8 Likṣā (নলে) 1 Yūka, louse

8 Yūka (যু ) 1 Yava, barley-corn

8 Yava (যে) 1 Aṅgula, digit (finger-breadth)

12 Aṅgula (আঙ্গুল) 1 Vitasti, span

2 Vitasti (24 aṅgulas) (নভতানস/ নভনি) 1 Kiṣku, Hasta, cubit (হি)

4 Dhanurmuṣṭi (26 aṅgulas) (ধনুর্ুুষ্টি) 1 Daṇḍa, rod

8 Daṇḍa (দন্ড) 1 Rajju (রজ্জু), rope

Aṅgula is also mentioned as the smallest unit of measurement in Vāyu Purāṇa (োয়ুপুরাণ). Table 2.2 displays the units depicted in the above mentioned scripture.

Table 2.2: Units of measurement according to Vāyu Purāṇa (aṅgula aka angula, n.d.)

UNIT EQUIVALENT UNIT

8 Aṅgulas (আঙ্গুল) 1 Prādeśa (প্রটদে)

12 Aṅgulas (আঙ্গুল) 1 Vitasti (নভতানস/ নভনি)

21 Aṅgulas (আঙ্গুল) 1 Ratni (রনি)

2 Ratnis or 42 Aṅgulas (আঙ্গুল) 1 Kiṣku (ন েু)

24 Aṅgulas (আঙ্গুল) 1 Hasta (হি)

4 hastas (হি) 1 Dhanus (ধনু)

2000 Dhanus (ধনু) 1 Gavyūt (গেুযৎ)

8000 Dhanus (ধনু) 1 Yojana (বযাজন)

Thus, several literary sources suggests the similar units with minor variations. However, dimensional analysis of the Barabar Hill Caves and Nagarjuni (নাগাজুযন) Hill Caves, which were erected during the Mauryan (বমৌযয) dynasty, has shown that the smallest unit of length, Aṅgula or Aṅgulum in this period is equivalent to 17.63 mm. Arthasastra by Kautilya, written during the Mauryan dynasty, in contrary with the Mānasāra, suggests the length of Danda to be equivalent of 96 Aṅgulum, which is equal to 1692.48 mm or 66.63 inch (Balasubramaniam, 2009). According to Mayamata, Danda is equivalent to 6 ft or 1828 mm (Dutt, 1925). As this research uses the book ‘Town Planning in Ancient India’ by Dutt, 1925 as a principal literary resource, it intends to follow 6 ft or 1828 mm as the equivalent of 1 Danda. Table 2.3 and Figure 2.2 portray the major units that will be used in this research.

Although, the length of Danda does not refer to the length of a human body, it seems logical that it should, since the smaller units gradually increase with body parts. It is noteworthy that later on, eminent architect Le Corbusier developed a figure named ‘the modulor man’ in order to create a universal system of proportion, where the length of the human figure is considered six feet (figure: 2.3). The figure could be segmented according to the ‘golden section’ into smaller parts and also could be scaled up to generate bigger module. Needless to say, the approach of Le Corbusier was inspired by the works of Pythagoras, Vitruvius and Leonardo Da Vinci (Wiles, 2009). Relevant units for distance are Krosha, equivalent to 2000 Danda or 2.25 miles or 3.66 km and Yojana, equivalent to 4 Krosha or 9 miles, nearly 15 km (Shamasasry, 1915).

Table 2.3: Major units of measurement used by this research

UNIT EQUIVALENT UNIT

Aṅgula (আঙ্গুল) 17.63 mm

1 Vitasi (নভতানস/ নভনি) 12 Aṅgula

1 Hasta or Cubit (হি) 24 Aṅgula or 423 mm-450 mm or 1.5 ft

1 Danda (দন্ড) 96 Aṅgula or 1828 mm or 6 ft

Figure 2.2: Major units of measurement used by this research

Figure 2.3: Modulor Man by Le Corbusier

2.3.5 Socio-economic scenario in Vedic period:

Caste system as an institution was not as yet a feature of the early Vedic period. The Rig Veda did not mention this strict stratification as a social system except for in one reference in the ninetieth hymn of the tenth book, the Purusha-Shukta (পু쇁ষ-�ক্ত) which in words of scholars had been included later on the late Vedic era (Ragozin, 1895).

The Brahmans (ব্রাহ্মণ)were priestly classes, ranked highest in the strata. The Kshatriyas (েনত্রয়)were the warriors. Vaisyas (বেেয) were the working classes their professions being farmers, craftsmen and traders. Sudras (েূর) were the menial class. The separating lines among the ranks are deep and straight and rather harshly set which is unprecedented in any other place in the world. The first three castes are allowed to learn the Vedas, an event where they consider themselves to be reborn, hence came the term twice-born (Dvi-ja, নি-জ). The Sudras, being non-Aryans, were not only not expected, they were forbidden from many aspects some of which we consider as basic human rights in today’s world. The non-Aryan people possibly belonged to the Dravidian or Kolarian races, who dwelled in the subcontinent from the prehistoric period long before the Aryan invasion (Ragozin, 1895).

Different currencies for Mahajapadas and Janapadas were in use (Rahman, 2012). The economy in this period was village oriented. The villages had arable lands beyond their boundary. The proprietorship of the lands were separated from one another by channels used for cooperative irrigation. Rural economy was based on peasant proprietorship where the farmer or his family cultivated the lands of their own. Also, landless laborers could be employed for cultivation on wages. Taxes were applicable on agrarian products. Beyond the arable lands of the villages, laid the common grazing grounds for pasturing the cattle. After that existed suburban groves. The village ended in the forests, which was the source of firewood and wild animals (Sen, 1999).

The Jataka (জাত ) mentions different kinds of arts and crafts and relevant professionals that prevailed in this era. Among these the noteworthy are the carpenters, the painters, the leather-dressers, the smiths, the stone-workers, the ivory-workers, the weavers, the potters, the bakers, the jewelers and the garland makers. Occupations like tanning, fishing, hunting, dancing, acting, snake-charming etc. were considered hina-sippas (হীন-

ষ্টিপ্পা) or despised callings. Some villages or areas used to become prominent for being specialized in a particular craft.

Trade was both foreign and inland; riverine and sea-borne. Towns and cities were the center of trade and commerce. Literary sources provides evidences of trade connections between Champa (চম্পা) and Suvanrnabhumi (সুেণযভূনম, Myanmar), Pataliputra (পাটনলপুত্র, Patna), Tamralipti (তাম্রনলপ্ত) and Ceylon via river and sea routes. Inland trades were carried on by carts and caravans (Sen, 1999). India at that period was had an extensive foreign trade with Arab, Turkey and Persia and through them with Europe through the famous silk route (Dutt, 1925).

2.3.6 Origin of Indian cities: types of settlement

Binode B. Dutt grouped the ancient Indian cities as consciously and unconsciously evolved (Dutt, 1925). He argued that, some cities had grown as due to deliberate efforts to improve or expand and some had developed rather organically over the course of time. A city could either be laid out by a certain king or it could be grown from a single patriarchal family. The family grew into a village; the village, being developed into a market-center, evolved into a city (Dutt, 1925). Different literary sources provide different classifications of settlements.

According to the Sailendranath Sen, the literary sources from Vedic period mentions the following categories of settlements in ascending order (Sen, 1999):

1. Griha (গৃহ) or house was the unit of settlement 2. Grama (গ্রাম) consisted of a group of houses 3. Palli (পল্লী), a settlement of wild tribes 4. Kheta (বেত), a place fortified by a mud wall or by river or hill surrounding it 5. Kharvata (খরেট), a poor town surrounded by a low wall, while according to Kautilya, it was the center of a union of 200 villages 6. Dronamukha (বরাণমুখ), a town with a harbor like Bhrigukachcha or Tamralipti, Kautilya describes it as the center of a union of 400 villages 7. Pattana (পট্টনা), a large town or a center of trade while according to another version, a mart for precious metals or a mining center.

8. Matamba (মাতম্ব), an open town associated with a cluster of 10,000 villages; according to another interpretation, it was a fortified place in which the product from the field was deposited for safe custody 9. Nagara (নগর), a town exempted from paying any of the 18 taxes levied on a village. 10. Rajadhani ( রাজধানী), capital of a kingdom 11. Nigama (ননগম), settlement of merchants and 12. Samvatta-kotta, a fortified place for refuge.

The Mānasāra and Mayamata are contextually located in southern India and describe seven types of town as follows (Sachdev, 2011):

1. Kevala Nagar (ব েল-নগর): literally meaning ‘ordinary town’, this has four gates located at cardinal point; it is heavily populated, being full of merchants and markets, dwellings for all classes and temples for all Gods. 2. Rajadhaniya Nagar (রাজধানী নগর) or a royal capital: keeping royal palace at the center, the city is inhabited by numerous wealthy people. It is in the center of the kingdom and is preferably located on the banks of a river; it has lofty gateways, temples, gardens, and contains people of all classes. 3. Pura (পুর) is a town frequented by buyers and sellers, busy with trading activity. It is like a capital city (above) but is located in forested country. It has temples of seven gods and is inhabited by people of all classes. 4. Kheta (বেত), meaning ‘field’ is an agricultural town situated next to a river or in close proximity to mountain, with dwellings of the lowest class. 5. Kharvata ( খরেট) is a town surrounded by mountains and pastures and inhabited by people of all classes. 6. Kubjaka ( ুব্জ is) a town situated between a kheta and a kharvata (as described above). It has a large and mixed population without a surrounding rampart. 7. Pattana (পট্টনা) is a coastal trading town. Its stretches along the coast and is protected by a rampart. It has dwellings of various castes with a strong mercantile community conducting import and export of goods such as jewels, silk cloth, camphor, and precious stones. Products of other countries are found here.

The plan of an Indo-Aryan town can be considered as a grand scale representation of the plan of an Indo-Aryan village (Grama, গ্রাম). According to the rules depicted in Mānasāra and Mayamata, we find two central cross-roads and a peripheral pathway surrounding the village or a city. Both treaties poses the same methodology for dividing the wards and distributing them among the inhabitants based on their social class, caste and profession. There are same rules for placing the communal temple, gathering spaces, tanks or wells, gateways and towers at cardinal points and bounding conditions. This similarity in the plan facilitated the process of developing and extending a village into a town. In other words, an Indo-Aryan town is a congregation of multiple villages (Dutt, 1925).

In order to ensure administrative efficiency, the fortress was placed in the midst of villages, which were grouped under their jurisdiction and supervision. A Sthaniya (স্থানীয়; a fortress) was supposed to be placed in the middle of eight hundred villages, a Dronamukha in the center of four hundred villages, a Kharvatika in the center of two hundred villages and a Sangrahana (সংগ্রহণ) in the middle of ten villages. The Shilpa Shastras emphasized that every new ruling dynasty should layout its own capital. King Bhoja said that residing in a city founded by enemy or even another ruler could be suicidal for a king (Dutt, 1925).

Samarangana Sutradhara suggests the relative sizes of settlements in terms of the organization of the population. A Rajdhani is surrounded by several Shakha Nagar (োখা-নগর) or satellite towns. Karvat is a sub-category of such a satellite town. A ‘lesser’ Karvat is termed as a Nigam.

Rajavallabha (রাজেল্লভ), a fifteenth century text from western India categorize the settlements according to their relative sizes: ½ Nagara (town) = a Grama (village), ½ Grama = a Kheta (as above); ½ Kheta = a Kuta ( ূট ; similar to a Kubjaka, as above); ½ Kuta = a Kharvata. A large nation (Rashtra, রাষ্ট্র or state) has 9,090 or 9,064 Grama or villages, a medium sized nation has 5,384 and a small nation has 1,548 villages. All nations must contain the seven types of cities (Sachdev, 2011).

Again, the references from the texts are mere guidelines. They can neither be perceived as strict acts or rules, nor do they describe the actual scenario. The relation between theory and practice can be described as interactive (Sachdev, 2011).

The cities were mostly located at the crossings of the great highways, which were used as trade-routes. River sites, sea coasts and the mouth of rivers were among the critical site forces. River was a means of communication within and out of the area under jurisdiction as well as a natural resource for water and sanitation. The first Indo-Aryan colonies were located along the plains of Indus and Ganges as the rivers provided them the best routes for their advancement. Besides, a coast belt or, a river side along with a mountain valley can provide natural means of defense against invasion. Therefore, we find the reference of a great many Indo-Aryan settlements in the shape of riparian towns. Many orthodox treaties have made it customary to establish the city on the right bank of the river (Dutt, 1925).

As for example, the ancient renowned town of Saptagrama (সপ্তগ্রাম), which today is modern day Chittagong, was a famous emporium. The towns of Bagerhat (োটগরহাট) in Khulna (খুলনা) and Rampurhat (রামপুরহাট) in Birbhum (েীরভূম), according to Mr. Dutt are expansion of local markets, known as hats. There were academic cities, famous among them are University towns of Nalanda (নালন্দা) and Taxila (তেনেলা). Navadip (নেিীপ) of Bengal was a well-known center for learning Sanskrit. Some cities were famous for crafts and local industries which evolved as a result of local geology and climate. Dacca was famous for Muslin, Krishnanagar ( ৃষ্ণনগর) for clay modelling, Murshidabad (মুনেযদাোদ) for silk clothings and Golkunda (বগালট ান্দ) for diamonds. The name of cities Cuttack ( ট , Kataka), Sealkot (নেয়ালট াট), Nagarkot (নগরট াট) and Mangalkot (মঙ্গলট াট) came from the term ‘Katak’ or ‘Kot’, which means a fort. Some cities originated around a single temple. Etymological references thus, provides in some cases the nature and character of some cities (Dutt, 1925).

2.3.7 The Indo-Aryan village

As stated earlier, an Indo-Aryan village (Grama) is a town in miniature; a variety of town (Nagarbheda; নগরটভদ). The texts provide fuller details about the village and the civic-architect is advised to utilize and adapt the same principles in case for a town.

Although a village is generally considered as a spontaneous unit having organic growth (a more appropriate term being ‘Palli; পল্লী’) in ArthaShastra, Kautilya gave instruction for establishing villages throughout the kingdom for the sake of administrative efficiency. New villages were laid out by either inducing foreigners to immigrate (paradesapavahanena; পরটদেপেহটননঃ) or by relocating excessive inhabitants from densely populated centers of the kingdom (svadeshabhisyanda-vamanena va; স্বটদেনভসযন্দ-োমাটননঃ). The kingdom may construct villages either on new sites or on old ruins (bhutapurvam abhutapurvam va; ভূতপূেযম-অভূতপূেযম). Villages were also founded for military purposes (Dutt, 1925).

According to Arthashastra, villages shall be formed having families from a minimum number of 100 to a maximum number of 500 of agricultural people from Sudra caste. The boundaries shall have a length of 1-2 Krosha (বরাে; 2250 yds.) and will be denoted by a river, a mountain, forests, bulbous plants (grshti), caves artificial buildings (setu- bandha; বসতুেন্ধ) or by trees such as Salmali (silk cotton), Sami and Kshira Vrksha (েীরেৃে; Milky tree). Villages were established nearby to tanks, lakes or rivers in order to ensure water supply and sanitation as well as for performing religious ritual. Markendeya Purana (মাট যটণ্ডয় পুরাণ) also suggests that villages are settlements of peasantry, mostly of Sudra castes, in the center of arable lands. However, it will be inaccurate to assume that the Vedic villages were not inhabited exclusively by the Sudras (Dutt, 1925).

Mayamata provides a classification for Brahman villages based on the numerical strength of their population which is shown in Table 2.4.

Table: 2.4 Classification of Brahman villages according to Mayamata

Class Grade Nomenclature Population of Brahmans/ Vipras

Best (Uttama) Superior Uttomottama 12,000

Mediocore Madhyama 10,000

Inferior Adhama 8,000

Average (Madhyama) superior Madhyomottama 7,000

mediocore Madhyama 6,000

Inferior Adhama 5,000

Small (Adhama) superior Uttama 4,000

mediocore Madhyama 3,000

Inferior Adhama 2,000

Inferior (Nicha) superior Nicha 1,000

mediocore Nicha 700

Inferior Nicha 500

A village inhabited by a single patriarch with its large retinue and menial staff is termed as ‘Ekabhoga (এ টভাগ)’. A village of learned Brahmans is called ‘Mangala (মঙ্গল; auspicious)’. Village having noble Brahmans or Vipendra (নভটপন্দ্র) is known as Agraharam (আগ্রহরাম). However, with time as the process of civilization progressed, the nature of the villages became composite (Dutt, 1925).

Mānasāra and Mayamata describes that a village, exactly as a fort or town should be defended by a girdle of walls and moats. However, lexicographer Bharat defines a Grama or village as a settlement devoid of such bounding condition. Mcdonell also opines that the villages were probably open except for the cases with forts inside them (Dutt, 1925).

The Mayamata sets forth the dimension of the villages in two ways:

a) Peripheral measurements: In terms of peripheral measurements the villages are of five kinds. The circumference smallest village is 20,000 dandas and the largest village is 100,000 dandas. b) Length and Breadth: Lengths of villages have forty varieties ranging from 500 to 20,000 dandas. The breadth may be 300, 500, 700, 900, 1000, 1300 or 2000 dandas.

Once again, these instructions are rather optional but these wide range provide a large scope for choice (Dutt, 1925).

The villages as well as all kinds of settlements were oriented in alignment with the cardinal directions. The villages generally had four gates at the middle of four sides and as many near the four corners. There was a large peripheral street running around the

32 village. Two major streets connecting two opposite main gates intersect each other at the center, dividing the village into four large blocks. A temple or hall is generally placed at the center which also works as a public gathering space. Each blocks are subdivided into multiple blocks by internal streets which are always straight (Dutt, 1925).

The two major streets crossing at center had houses on one side facing the street and the ground floor of these houses were used as shops. The peripheral streets also had houses on one side which were mainly public buildings like schools, colleges, libraries, guest-houses etc. All other streets had residential buildings on both sides (Dutt, 1925).

Temples for public worship, gardens, parks, tanks and ponds were placed in such locations so as to be accessible by majority of the inhabitants. The best quarters are reserved for Brahmans and artist classes. The habitation of Chandalas (চন্ডাল; people from lowest caste), the temple of fearful deities and the places for cremation were located outside the village boundaries (Dutt, 1925).

Mānasāra classifies the villages into eight types in terms of their shape, street-planning, folk-planning and temple planning. They are called Dandaka (দন্ড ), Sarvatobhadra (সেযটতাভর), Nandyavarta (নন্দযােতয), Padmaka (পদ্ম, ) Swastika (স্বনি ,া) Prastara (প্রির), Karmukha ( রমুখ) and Chaturmukha (চতুমুযখ). Based on only street-planning Mayamata classifies the villages into: Dandaka (দন্ড, ) Swastika (স্বনি ,া) Prastara (প্রির), Prakirnaka (প্রা ীণয ), Nandyavarta (নন্দযােতয), paraga (পরাগ), Padma (পদ্ম) and Sripratishthita (শ্রীপ্রনতনিত). Kamikagama ( ানম াগাম) classifies the villages into fifteen catagories which includes all the types stated by Mānasāra and Mayamata and the following four: Sampatkara (সম্পত ার), Kumbhaka ( ুম্ভ, ) Srivatsa (শ্রীেৎসয) and Vaidiaka (বেনদ ) (Dutt, 1925). Brief description of the types of Indo-Aryan villages are given below.

1. Dandaka (দন্ড: ) refers to a village that resembles a phalanx or a staff. According to Maayamata this type of village has straight streets running from west to east and south to north crossing at right angle at the center. Even if a village has only one street, it can still be termed as Dandaka. Mānasāra describes that a Dandaka village is rectangular or square and possesses a rampart of the same shape. It has one to five

33 parallel streets running from west to east. Two transverse streets running from north to south are placed at the both extremities forming right angle (Mangalavithi; মঙ্গলনেথী) and another one at the middle (Rajavithi; রাজনেথী). The width of the streets varies from 1-5 dandas. The central transverse street can be made equal to or broader than the rest. The two transverse streets at the extremities have a single row of houses while the principal streets have double rows. Each house may have a breadth of 3, 4 or 5 dandas according to their function and suitability having a length twice or thrice of the breadth. The village may have a wall or a ditch surrounding it. The village should have four large gateways in the cardinal directions and smaller ones at several corners. Two principal reservoirs can be located towards the south-west and north-east corners. This type of village may contain 12, 24, 50, 108 or 300 Brahman families. 2. Sarvatobhadra (সেযটতাভর): This type of village may be oblong or square. The folk-planning of this village can be arranged following the figure of Manduka (মন্ডু ; Figure 2.8) or Sthandila (স্থাষ্টিলা). The number of car streets (Rathya; রথ্য) may vary from 1 to 5 with a boulevard running around the village. The internal streets are lined with single row of houses while the outer streets has double row of houses. The village should be secured by a wall and a ditch, with four large gates on the cardinal sides and many smaller gates nearby the corners. Assigned quarters for artisans and craftsmen can be located along the boulevard (Maharathya; মহারথয). The houses of Vaisyas and Sudras should be allocated towards the south. 3. Nandyavarta (নন্দযােতয): It may also be oblong or square. If the village is square, it can be divided following the mystique figure Chandita (চন্ডীতা, also known as Manduka) and if it is rectangular, if can be divided according to the figure Paramasayika (পরমসানয় া, Figure 2.8). This type of village has four large streets along the periphery, running in each cardinal direction at right angles. The eastern street runs from north to south and projects out. The southern street runs from east to west, the western street from south to north and finally the northern street from west to east. There must be 3, 5, or 7 such sets of concentric streets with rows of houses on each side. The lanes lying transverse between the main roads do not provide access to the houses from them. Hence, a Vithi (ষ্টেথ্ী) refers to a lane which is lined with the houses and a Marga (র্া쇍ু) refers to a road is devoid of or irregularly lined with the houses.

Maayamata describes Nandyavarta as a village having 5 main roads running from east to west, while the number of transverse thoroughfare varies from 13-17. 4. Padmaka (পদ্ম: ) Mānasāra describes that this type of village has equal length and breadth and the enclosing walls are circular. The village and its wall may also be quadrangular, hexagonal or octagonal. It can also be divided following the figures Chandita or Sthandila. According to Mayamata the number of streets running from east to west may be six or seven, while the transverse street may be 20. 5. Swastika (স্বনি :া) According to Mayamata, the eastern street of this village starts from north-east projects out to the south; the southern street begins from south-east corner towards the west. The western street runs in northerly direction starting from south-east. The northern street starts from north-west and run towards east. Mānasāra depicts that the Length and breadth of this village may be of arbitrary proportion. The village should be divided following the figure Paramasayika (Figure 2.8). The streets should be laid out in conformity with the figure Swastka. Internal streets have rows of houses at one side only and the peripheral roads have rows on both sides. The village should be defended by a rampart surrounded by a ditch. 6. Prastara (প্রির): Etymologically, the term Prastara refers to a couch. Mayamata describes that this type of village is intersected by three streets running from east to west and by several transverse streets ranging from three to seven. According to Mansara, this village can be either square or oblong in shape. The village can be divided following the mystic figure Paramasayika, Chandita or Sthandila and Paiscaha (বপোচ). It can be divided into 4, 9 or 16 wards by a network of appropriate number of highways, having a range of breadth between 6, 7, 8, 9 and 11 dandas. The division of plots were executed according to the degree of rank and wealth of the occupants. Therefore, all the wards are not divided into equal number of plots or blocks. One is divided onto nine plots, another into sixteen, the third into twenty five and so on. The high-ranked or rich personnel thus occupied the largest plots. This layout seems to have provisions for future extension by means of enclosing larger areas with new walls. There may be even 8 to 12 of such enclosures. The shape of theses enclosures will be determined by the shape of the original village. 7. Karmuka ( রমুখ): Karmuka means a bow. Therefore, the shape of this type of village is semi-circular or semi-elliptical. Among the various types of towns, the

Pattana, Kheta and Kharvata are planned after this. This shape of village is generally suited to a riparian site or a sea-shore. There are two car-streets and one principal road. The number of transverse streets may vary from one to five. Houses are placed on both side of them. There may be additional radial roads. The gates can be placed as many as desirable and the presence of the peripheral rampart is optional. 8. Chaturmukha ( চতুমুযখ): It can be square or oblong lying from east to west. There are four great car streets on the four sides. The two large streets crosses at the center divides the village into four wards. Each wards are then divided into blocks by four longitudinal and four transverse roads which have comparatively smaller width than the car streets. The four main gates are placed at the terminus of the principal streets. Residential blocks are not recommended to be placed on the car-streets. If the village is chiefly occupied with people from trading class, it is clled Kolakoshtha (কলাগ্বকাষ্ঠ). 9. Prakirnaka (প্রা ীণয: ) It means a ‘Chamara’, a fan made with big hairy tails of yaks fastened to a handle. Mayamata and Kamikagama both suggests that this type of village has five varieties. According to Mayamata, the number of easterly roads is four, while the number of northerly roads varies from eight to twelve. Kamikagama mentions that the northerly roads may vary from four to seventeen. 10. Paraga (পরাগ): According to Mayamata, this type of village has six easterly streets and eight to twenty-two northerly streets. Kamikagama remarks that the layout contains six to twenty three northerly streets and six cross roads facing east. Although, this type of village is small, the road network contains a large number of streets that facilitates easy movement of large volume of traffic. 11. Sripratishthita (শ্রীপ্রনতনিত): Mayamata describes that, this type of village contains eight principal roads facing east and the number of northerly streets varies from eight to thirty-two, which according to Kamikagama, varies from eight to thirty six. 12. Sampatkara (সম্পত ার): Etymological origin suggests that this type of village is very auspicious and secures wealth and prosperity. The Sampatkara along with Kumbhakam, Srivatsa and Vaidika are mentioned in only Kamikagama. It has five streets running from east to west and twenty one transverse streets. 13. Kumbhakam ( ুম্ভ: ) its shape is either circular or polygonal like a pitcher, as the name suggests. The streets in this village run parallel to the contour.

14. Srivasta (শ্রীেৎসয): The number of streets has no limits. The houses are allowed to build up more than one storey. 15. Vaidika (বেনদ ): The number of streets also has no limits. Each street must have houses on both sides. Like the previous case, the houses are also allowed to build up more than one storey.

Although, the description of the last seven types of villages are quite inadequate, it is noteworthy that the number of transverse streets elongated in north-south direction exceeds the number of east-west elongated streets. It implies that the villages were elongated along east to west so that winds could not blow up clouds of dust, while the buildings were open to free ventilation which in India generally runs from south to north and north to south (Dutt, 1925). The diagrams showing cadastral patterns for different types of Vedic villages are shown in figure 2.4.

According to Prof. Dutt, the Indo-Aryan Villages differ from the existing villages of Bengal in terms of planning. He mentions that the villages in Bengal are results of unconscious spread of human habitation due to population growth into soil which was originally overgrown with woods and thickets. These villages are not a product of conscious planning processed as opposed to ‘Vedic villages’.

Dandaka Sarvatobhadra

Nandyavarta for square, oblong and circular settlements from left to right respectively

Swastika Prastara

Padmaka Karmuka Chaturmukha

Figure 2.4: Diagrams for Vedic villages

2.3.8 Siting considerations and environmental rationales

2.3.8.1 Siting considerations

The sites for Indo-Aryan villages or towns were selected by the master builders following the principles of the treaties. Among various natural features the most favorable were the river banks, sea shores or the presence of a large lake or tank nearby the site. Water is essential for both consumption and sanitation purposes. Besides, ablution, cremation and sacrificial rites can be mentioned even today among the iconic Vedic and later Hindu religious rites which requires the presence of water in close proximity with human habitat. The land surrounding the settlements should be fertile and requires a network of water ways for irrigation as agriculture has been the principle profession in India. Also a navigable river in proximity to the site provides access to

38 easier communication. Proximity to hill ensures supplies of minerals, fuel and timber. According to Sukracharya (�রাচাযয), the capital should lie at the foot or the side of a mountain which is strategic for defense, but a mountain should not be included within the city. Both the Mansara and Mayamata suggests various kinds tress to be planted within the streets, public places and houses of the settlements. Majority of them are well –known for their medicinal property and the writers believe that they could purify air.

The Mansara asks to examine the site in terms of color, smell, taste, shape, direction or orientation, sound and touch. The Mansara and Rajavallabha by Sutradhara Madana (সূত্রধর মদন) classifies four types of soil which are associated with the four castes in terms of color, smell, taste, form, direction, sound and touch:

a. The soil appropriate for Brahmans is white in color, has fragrance like ghee (clarified butter) and agreeable to the taste. White symbolizes purity and holiness. b. Soil suited for the Kshatriya or warrior class is red, smells like blood and astringent in taste. Red being the color of blood symbolizing battle and martial spirit. c. Soil for Vaisyas is yellow, smells like sesame oil and sour to taste. Yellow being the color of gold is emblematic to commerce. d. Soil for Sudras is black, has fish-like odor and tastes pungent. Black signifies ignorance and dark complexion of the Non-Aryan population.

2.3.8.2 Environmental rationales

The Vedic literary sources present the environmental rationales using the determinants that are perceptible through sensory experiences, which are the sun, wind and rain. The effects are often described in metaphors. According the Vedic scriptures, The ground should be smooth with a declivity towards the east, producing a hard sound, with a stream running from left to right, of an agreeable odor, containing a great quality of soil, producing water when dug to the depth of a man with his arm raised above his head and situated in climate of moderate temperature. Ground with irregular shape or undulated surface are prescribed to be avoided.

Mayamata says the ground should rise slowly towards the south and the west and slant down towards the north and the east. According to Bhoja, the ground should be slightly elevated to the middle and slanting towards east and north-east. A southern declivity increases insanitation and brings about diseases; declivity towards north increases wealth; slope towards west is detrimental to peace and prosperity; depression in the middle increases poverty and depression on the boundary brings happiness.

All the Shilpa Shastras are in favor of eastward slope as it obtains the benefit of the morning sun. Locating a settlement to the west of a mountain is prohibited as the mountain will obstruct the sun-rays during sunrise.

Being located to the north of the equator, an inclination towards the north is challenging as it lessens the incidence of sunlight from the south and exposes the buildings to the chill winds of winter from the Himalayan ranges. Although, the south provides ample sunlight and wind from the ocean, the Shilpa Shastras focus on the fact that a southerly declivity will provide too much exposure to the sunlight which would increase the heat gain of the built forms and also dry up the soil. This considerations are further strengthened religiously, as the diagram of Padavinyasa (পদনেনযাস; described later in this chapter) shows the north as a quarter of light and region of the Devas (বদে, Deities) or the shining ones, while in the south presides Yama (যম), the god of death. The inclination should not be distinctively perceptive to the eye.

The slopes are also useful for facilitating drainage. In case of southern declivity, the wastes of the settlement would be drained and washed away towards the southern ditch. The wastes usually decompose faster in summer than the winter. Southern declivity would have invited the polluted air into the settlements, thus causing insanitary scenario and hence Northerly slopes are encouraged as they helps the contaminated air to waft away.

The prevailing winds and rains in India are from south and west (east for Bangladesh), a south or westward slope will expose the built forms to storms and showers. Also, exposure to the northerly winds of the summer, which has been considered as the season of epidemics in India, is not conductive to the salubrity of the town.

2.3.8.3 Bounding condition

Mayamata states different schemes of measurements for establishing a town, such as:

a. The length of one side of a town may range from 1000 dandas and the circumference may have four variations from 2000 to 8000 dandas having a common difference of 2000 dandas. b. The lateral measurements for a good, mediocre and bad towns are 768, 704 and 640 dandas respectively while the sides of the same are 832, 896 and 962 dandas having a common difference of 64.

1 1 c. The length may be 2, 1¾, 1½, 1¼, 1 ⁄6, 1 ⁄8 or 1 times the breadth of the settlement (figure 2.5). d. The towns can be divided into 78 kinds according to their lengths of a side ranging from 300 dandas to 8000 dandas by a common addition of 100 dandas. e. The circumference of a splendid town varies 25 times from 1600 to 4000 dandas by a common addition of 500 dandas.

Figure 2.5: Various Length to width ratio of settlements suggested in Vedic literature with same area

These measurements apparently seems arbitrary and they were not strictly adhered to in practice, but the measurements provided enough varieties. The master builder had a wider scope to adjust the measurements according site space and population.

As stated earlier, the Vedic villages did not contain fortified walls but they were most likely to be surrounded by moats. Therefore, further discussion regarding fortified walls is not relevant to this research.

2.3.9 Street planning

Laying out streets had been considered as one of the most important functions of a civic architect. Streets are essential for vehicular and pedestrian circulation as well as dividing plots or blocks to accommodate built forms. They also provide arteries for drainage and sanitary purposes. Efficient planning of streets ensures easy and quick access from one quarter to another, especially to the centers of public importance like courts, health facilities and markets. From the Vedic era, the heights of buildings have been found to be in correspondence with the width of the street in order to ensure sufficient daylight and ventilation within the built forms. The width of the streets were also associated with volume of traffic and their relevant importance in terms of connectivity. From the previous paragraph we have already come to know that majority of villages contain grid iron pattern of streets. Diagonal and curvilinear streets have seldom been used.

2.3.9.1 Hierarchy of streets

Denomination for different kinds of streets in Vedic villages or towns are as follows:

a. The street that runs through the periphery of the village is termed as Mangalavithi (মঙ্গলনেথী). This street is also called Rathya (রথয), which means a road along which the processional chariots (Ratha; রথ্) are dragged. The prescribed width for this type of street is one to five dandas. The peripheral road of a capital is called Janavithika (জননেথী া). b. The street that runs from east to west is called Rajapatha (রাজপথ). The one which contained gates at both extremities is called Rajavithi (রাজনেথী). According to Mayamata, the central among these streets that passes through Brahma’s chamber is called Brahmavithi (ব্রহ্মনেথী). To be noted that a Rajapatha or Rajavithi is not King’s street, which refers to the road running in front of royal palace; etymologically it means king among streets.

c. The short roads lying north to south which connects two easterly parallel streets is called Vamanapatha (োমনপথ). Such short roads can be planted in a straight line so as to form a continuous road. The central among the northerly streets is called Mahakalapatha (মহা ালপথ). d. The roads with junctions are called Sandhivithis (সনন্ধনেথী). e. A narrow pedestrian lane or footpath is termed as Padya (পদয), with a preferable width of three cubits. f. A narrow shopping lane is termed as Vithi (নেথী), which can be five cubits wide. g. Any ordinary road is termed as Marga (মাগয) and prescribed width is ten cubits.

According to Kautilya, Chariot roads, royal roads, roads leading to country parts and pasture grounds shall have a width of four dandas. Roads leading to military stations, cremation grounds to villages shall have a width of eight dandas. Roads leading to gardens and forests shall be four dandas wide.

Mangalavithi Bramhavithi Mahakalavithi

Rajapatha Vamanapatha

Figure 2.6: Hierarchy of streets in Vedic villages

2.3.9.2 Street as a social space

The central streets, Brahmavithi and Mahakalapatha, formed the major arteries for communication within the village or town and also with other such settlements. As India had extensive foreign trade with middle-eastern and western countries in Vedic period, the trade routes was located through the passes of the North Western Frontier Provinces. Hence, in typical circumstances, the Mahakalapatha, running from north to south was used as the chief commercial route within a settlement (figure 2.7). The Brahmavithi was used for military expeditions and inland trade. Exceptions can be found in Northern and Eastern part of India, where these central streets exchanged their purposes.

For ensuring only pedestrian movement, narrow lanes called Padya were provided. Such lanes had too small width so as to allow any vehicle passing through them.

The Smriti Sastras suggest lighting lamps at the cross-roads. At the intersections, divine edifices were erected. The cross-sections also contained the well, the chaitya (বচতয), the sabha-vrksha (িভােৃক্ষ, council tree) or the dipa-stambha (দীপিম্ভ, light post) at the center of their great width in order to minimize the probability of collision between counter going vehicles. Originated from the custom of ‘pradakshina’ (প্রদনেণ, circling around a sacred object, edifice or temple in clockwise direction) it is evident that the pedestrian and vehicular movements were directed towards the left side of the road.

Significant buildings like colleges, shrines and monasteries were placed at the junctions of the roads. The center of the town contained the imperial mansions.

Figure 2.7: A Street Market Scene in India by Edwin Lord Weeks (1887) showing outdoor commercial activity

The streets of most ancient towns were lined with walls on both sides and no lane or window opened up on them. Later on, windows on the second stories were allowed to be placed on the road side. Small stalls for shopping were placed in rows against the wall. The height of the stalls did not exceed the height of the wall. Sometimes, the streets were identified by an entire profession or business class.

The streets were elevated in the middle which provided a curved profile and the country roads were provided with sufficient culverts and bridges. The streets had drains on both side of the roads for drainage. The streets were paved with stone slabs or macadamized with broken stones and gravels (Dutt, 1925).

2.3.10 Site planning and folk planning

A city, town or village was generally divided into gramas (গ্রাম) or muhallas (মহল্লা); i.e. wards when the principal streets or Rajapathas are laid out. The scheme for dividing the town or village is known as Padavinyasa. Generally, the wards are divided according to the principle of Padavinyasa and the principal streets are therefore placed along the line of the division. Padavinyasa provides reference for distributing

45 professions and castes as well as allotting sites to a particular pada or block. The rules of Silpa Shastras describes that the number of padas or quadrangular blocks in any place should vary from one to one thousand and twenty four in correspondence with its area and structural requirements.

The method for dividing a village or town into padas (পদ) is to draw two to thirty three parallel line along the horizontal axis and as many vertical parallel lines required. Each of these thirty-two schemes are distinguished by specific names assigned to them according to the number of squares into which the whole area is divided out. The names in order are Sakala (স াল), Pechaka (বপচ ), Pitha (নপঠ), Mahapitha (মহানপঠ) etc. ending with the thirty second Indrakanta (ইন্দ্র ান্ত). The scheme has been arranged in a way that the number of divisions represent the square of the serial number. Therefore, the seventh scheme, which is called Sthandila (স্থানন্ডল) contains 49 squares, the eighth scheme Chandita (চনন্ডতা) or Manduka (মন্ডু ) has 64 squares and the ninth scheme Paramasayika (পরমসানয় া) has 81 squares. Each of these divisions or squares are assigned to different presiding deities (Figure 3.5).

According to Mayamata, a city planner may select any scheme from the first (Sakala) to tenth (Asana; আসন) while designing a village. The civic architect was at his own liberty to choose at what extent he is willing to follow the schemes as they are not as rigid they may seem. Even so, the generally recommended scheme was Paramasayika with 81 squares.

In terms of shape, the blocks were not necessarily square. The physical shape of these blocks were governed by the peripheral shape of the village or town. Thus rectangular settlements had rectangular blocks and settlements with triangular periphery or located on contour sites had irregular blocks.

Each blocks were again subdivided by narrower and smaller streets into building blocks. Each block was considered as individual and thus were divided according to their character and necessity. Thus diversity within uniformity was introduced. A single town often had various types of village plan adopted to divide the wards. In order to ensure uniformity of life and consequent economic efficiency, people from same caste and profession were being allotted to the same ward or block.

Kautilya (ব ৌনটলয), Sukracharya (�রাচাযয), Agni Purana (অনিপুরাণ) and many other literary sources provides different methods for allocating population from various castes and professions. Mayamata describes the typical site-planning procedure for a village in the following way.

After dividing the settlement into 49, 64 or 81 blocks, they are reclassified into different zones which are organized in tiers. The innermost zone is called Brahma (ব্রহ্ম), the next annular zone is called Daivika (বদনে ), the third tier is termed as Manusha (মানুষ) and the outermost tier is known as Paisacha (বপোচ).

The houses of Brahmans were supposed to be placed in the second and third tier. The outermost tier was occupied by the artisans and laboring classes. In the central quarter the shrine of Brahma should be placed. At the north-east and south-east corner of this shrine, shall be located the town-hall. The cattle-sheds should be placed to the south of the settlement and the north will have flower gardens. The hermitages should be provided to the east or west adjacent to the gates. Tanks, wells or reservoirs are to be distributed evenly throughout the village. The houses of the Sudras were stationed to the right and by the side of Vaisyas or trading class. The potters, barbers and craftsmen were provided with housing plots towards the eastern or the northern quarters.

Figure 2.8: Diagrams of Padavinyasa: Chandita and Paramasayika (Dutt, 1925)

The fishermen and butchers were to be placed in the north-west and west respectively, while the oilmen were given plots on the north. The quarter for architects were being placed either in the south-eastern or north-western plots.

The cottages of sweepers are supposed to be placed a Krosa away from the settlement towards the east. The cremation ground was generally located five hundred dandas to the north-east.

The royal palace should be provided an eastern-quarter dedicated to the deity Apa (অপ) and the royal complex should occupy about one-seventh of the entire settlement. Royal buildings at Jaipur occupy a closer proportion.

According to Bhoja, the central sites should be reserved for the nobility, physicians, astrologers and the pious. The extreme sites should be allotted to the Mlecchas (বেচ্ছ) or foreigners, people from lower castes, cruel professionals, soldiers and sentinels. The barracks of these soldiers should be placed adjacent to the town-gates. The quarter for ministers and counsellors should be relegated adjoining to these barracks for he believed the king should not live in proximity with his counsellors as it poses life risks. However, the nobility, infantry and ministers should not be placed too far away. The quarters of the officers needed to be systematically placed throughout the town (Dutt, 1925).

2.3.11 Building bye-laws

Although, Building design and construction does not fall within the scope of work of a town-planner and has an elaborate domain by itself, the correlation between civic and domestic engineering sciences demands the town planning authority to exercise some control over the construction and arrangement of the buildings within the city. Even in Vedic period, it had been realized that the character of a building within a city or village should be governed by the holistic entity rather than its individual identity. Such sense of civic integrity gave rise to many significant bye-laws which had been exercised through relevant enforcement authority. Several prominent laws (Dutt, 1925) are briefly described below:

1. ‘First lay out the town and then only plan the houses. Violation of this rule portends and brings evil.’

The statement portrays the importance of ensuring proper width of streets, sufficient setbacks between built forms, sanitation and relevant civic facilities which may not be observed in case of unconscious growth of houses. This law emphasizes on systematic and comprehensive layout of the city, its walls, streets and lanes, distribution of sites and buildings in appropriate order. 2. ‘First plant the trees and erect the premises thereafter. Otherwise, they will not look graceful and seemly.’ The trees in discussion are Asvattha (অশ্বত্থ; ficus religiosa), Banian (েট; ficus indica), Udumbara (উদম্বুর/ যজ্ঞ ডুর্ুর; ficus racemosa), Plaksha (প্লক্ষ; ficus tusida), the red flower tree, the tree exuding milk (ক্ষীর েৃক্ষ; Kshira Vrksha), the Rubber tree (manihol glazionii), Banana and flower plants. The majority of these plants are of bulky proportion and have large foliage not suitable to be planted in domestic orchard. These type of trees provide shade to the wayfarers exposed to the sun and are meant to be planted in parks and promenades of the city, its avenues and streets. Such large trees are being discouraged to be placed in domestic precincts as they may pose difficulties to ensure proper daylight and ventilation to that particular house and its neighbours as well. Plants with anti- malarial properties such as the Nimba (ষ্টনর্; azadirachta indica) and the Bael (বেল; aegle marmelos) are generally recommended for domestic orchard. 3. ‘The houses of Brahmans should be Chatusala (চতুোল); that is, they must ocuupy the four sides of a quadrangle which is an open space in the center. Sala (োল) means a long structure of one span only. The houses of Kshatriyas should be Trisala (নত্রোল), i.e., occupying the three sides of a rectangular plot. The houses of Vaisyas should be Dvisala (নিোল), i.e., forming the two sides of a plot, while those of Sudras should be Ekasala (এ োল).’ The Trisala and Dvisala can be articulated to accommodate their open space adjacent to the road which may contain a flower garden. Thus if all the houses recede in one or both side of the streets, a roadside garden can be provided. Although, there is no definitive proof for the existence of such layout, this bye- law aims to ensure a relief in the street façade which otherwise would have been monotonous.

4. ‘The Imperial Palaces should be raised to eleven storeys; the building of Brahmans to nine storeys; the building of provincial satraps (Samantas; িার্ন্ত) to five storeys; Vaisyas and Kshatriyas should have four storeyed buildings and Sudras should have their houses one to three storeys high. According to Mansara, the lower classes must on no account construct houses of more than a single storey. Vrihat Samhita (েৃহৎ সংনহতা) says that no building should be more than hundred cubits high.’ Thus the building bye-laws suggest definite number of storeys for specific classes of people. Proper town-planning requires correspondence and proportion between the width of streets and height of buildings rising along it. Buildings with excessive and disproportionate height may obstruct light and wind. Folk-planning in ancient India addressed this issue by placing the people from higher social strata along the wide thoroughfares, while people from lower strata were relegated towards the relatively narrow roads, so that all the buildings along a particular street has similar number of storeys. 5. ‘As far as possible, the height of buildings in the same street should correspond, that is to say, one should not be lower and another higher.’ This rule ensures uniformity in the height of a building in the same street. 6. ‘A deviation from the fixed measurements of lengths, breadths and heights of respective buildings of the different classes of people is not conductive to good and should not be made.’ This rule also ensures all-round uniformity of buildings on the same street for only a particular class was allocated residence in the same street. As the wide streets divided the wards and each ward was occupied by different classes of people, it was unlikely that buildings on both sides of such a wide road had buildings with similar heights along it, which ensured diversity in uniformity. 7. ‘The houses shall be furnished with Verandas (Alinda; অষ্টলন্দ); and with flight of steps leading down from the high plinth of the veranda and stone-couches. A Vedika or raised seat should be constructed on each side of the door.’ According to Sister Nivedita, “Life in the clear air and under the cloudless skies of India, necessarily passed much in the open air. The street is kind of a club.”

8. ‘Outside the house and touching it there should be planted a foot-path (Vithika), which should be as wide as one-third of the breadth of the house.’ Mansara suggests to place raised footpath on both sides of the streets. Such footpath formed an inseparable part of the house. 9. ‘All houses should face the royal roads and at their backs there should be Vithis or narrow lanes to allow passage for removal of offals and night-soil.’ The interesting feature of this bye-law, which has been reflected in other treaties as well as in old extant buildings is that, the doors never opened on the roads. The rule for intervening spaces between two buildings is useful for ensuring sanitation.

From the above mentioned bye-laws, it is evident that co-operation between building construction and town-planning had long been practiced since Vedic period.

2.4 Examples

This section will present Jaipur as a case study as this city was planned upon the Vedic diagram ‘Prastara’. Although the city was established much later than the Vedic period, it is one of the few living examples. Also, the settlements in Bengal that existed during the Vedic period to second urbanization and have been unearthed archeologically apart from being mentioned in literary sources will be presented.

2.4.1 Case study: Jaipur

The city of Jaipur is located amidst the Aravalli Hills in Rajasthan at an altitude of about 430m above the sea level. It is situated at a distance of 200 miles from Delhi and 150 Miles from Agra. Jaipur, as a planned capital was established in 1727 by Maharaja Sawai Jai Singh II. Amber, the previous capital was replaced with Jaipur for geographical and military reasons. The rocky terrain of Amber was not suitable for expansion and lacked the supply of adequate drinking water. Jaipur was strategically placed at the relatively flat terrain at the foot of Nahargarh hill, which is shaped as a horseshoe, to ensure protection from north, east and west allowing the city to expand towards south. The perennial stream nearby ensured water supply and the rugged hills were a source of building materials. Maharaja Jai Singh commissioned Vidyadhar

Bhattacharya (ষ্টেদযাধর ভট্টাচাযু), a Brahman scholar from Bengal, as the civic architect who planned the city following the principles of Shilpa Shsastra and Vastu Shasra (োস্তুশাস্ত্র).

Figure 2.9: Formation of Axis in Jaipur (Nongrum, 2008)

Although, the Vedic treaties strictly suggest to orient the settlements following the cardinal directions, the axes of Jaipur are a little tilted due to the topographic situation. The planning of the city began with marking two principal axes. A straight line of the ridge along the west-east axis was suggested as the major thoroughfare and the topography could be used to its potential in terms of drainage by placing a road along this axis. Along the north-south axis, the road was planned to connect the Jaigarh fort towards the north to Sanganer, the trading town (Figure 2.9). The point of intersection of these roads at right angles created the city’s main cross-roads (chaupar).

As stated earlier, according to the rules of Padavinyasa, the site can be divided into a number of squares. The site of Jaipur was primarily divided into a grid of 3x3 squares, the gridlines being the city’s main streets. The north-west square was not possible to be allocated due to topographic reason and hence, an additional square was placed at the south-east. Each of these squares measures almost 800x800m. The squares were further divided into wards or muhallas by means of lanes and alleys following the layout of the village type Prastara.

The central axis as well as the main road was laid from east to west between the gates of the sun (suraj pol; িূরজ বপাল) and moon (chand pol; চাাঁদ বপাল). The central two squares at the north of this road was occupied with the royal palaces and state offices. The south of this road contained four almost equal squares. The one opposite to the palace was divided into two rectangles by introducing a road along the north-south axis which is called chara rasta (চার রাস্তা). These five southern blocks are termed as Chowkris (বচৌকষ্টি). Lanes and streets named after occupations of inhabitants suggests the initial distribution of wards following the principles of Padavinyasa. The width of the primary, secondary and tertiary streets are found to be 111ft, 55ft and 27ft respectively. The corresponding Vedic units are 18.5 dandas, 9.1 dandas and 4.5 dandas.

The intersections of the major roads are termed as Chaupars (বচৌপাি) , which measures almost 100x100m. These are used for public gathering on festive occasions. The distance between two Chaupars is almost 700m, which is a tolerable distance in terms if pedestrian movement. Historically, the Chaupars contained outlets of water for intense social use in order to ensure water supply. These infrastructure were connected with underground aqueducts. The major streets housed the main markets, havelis and temples. The street elevation was strictly designed to be uniform. Therefore, these main streets and Chaupars have a social interface even today. Use of sunshades (Chhajjas), colonnaded arcades and delicate lattice screens (Jali; জাষ্টল) shows the effort to reduce heat in semi-outdoor spaces (Singh, 2013).

Figure 2.10 (a): Order of streets within the second chowkri from the right at south of Jaipur (Nongram, 2008)

Figure 2.10 (b): Zoning within the second chowkri from the right at south of Jaipur (Nongram, 2008)

Figure 2.10 (c): Section of main street (Nongram, 2008)

The streets and Chowks (central open urban squares) of the Chowkries with numerous wards or muhallas were not predetermined. Therefore, the internal cadastral pattern of these Chowkries displays a combination of planned and organic urban fabric.

The height of the built forms were regulated by the width of the streets. Although the Vedic building bye-laws suggest a maximum of eleven storeys, the early buildings of Jaipur have a maximum of four storeys.

Figure 2.11: Built and Unbuilt areas in the second chowkri from the right at south of Jaipur

Primary analysis of the Chowkri located at the west of the isolated one reveals the ratio of built and unbuilt portion of the block to be 57.86% and 42.14% respectively (figure: 2.11). The chowkri has all the four types of buildings mentioned in the bye-laws: the ekasala, dwi-sala, tri-sala and chatusala. Among the built-forms the apparent buildings with courtyards (chatusala) occupies 37.79%, the U-shaped buildings or trisala occupies 15.46%, L-shaped dwi-sala occupies 17.81% and I-shaped ekasala occupies 28.94%. The internal neighbourhood blocks adjacent to the major streets are dominated by the buildings with courtyard and the peripheral blocks are mostly occupied with the linear buildings. However, randomly selected neighbourhood blocks reveals that they act as a solid mass in terms of air flow with negligible or no porosity as the internal

55 gaps or setbacks between buildings are irregular and there are no means of quantifying the thorough fissures within these urban blocks. The building along the major streets are also placed adjacent to each other forming a horizontal streetscape with no setbacks between them.

2.4.2 Settlements in Bengal

Tamralipti (তাম্রষ্টলষ্টি): Noteworthy among the oldest settlement with sea port for trade. It is mentioned in the Mahabharata, the writings of Ptolemy and Hsuan Tsang (Xuanzang) (Mortaza, 1996). It was renowned port which successfully functioned from 300 BCE to 7th century CE. Literary sources provides the location to be at the bank of Ganges near the Bay of Bengal. The exact location has been found to be in 24 Pargana district of West Bengal at the bank of Rupnaran River. Traces of human settlements have also been found from Neolithic and Chalcolithic period (Rahman, 2012).

Bangarh (োণ쇍ি): Located in West Dinajpur District of West Bengal. It is situated at the Valley of Punarbhava (পুনভুো) River on Varendra Bhumi (েগ্বরন্দ্র ভূষ্টর্). The ancient names of Bangarh have been found to be Kotivarsha (বকাষ্টিের্ু), Devakota (বদেগ্বকাি), Vanapur (োণপুর) and Sunitpur. (িুষ্টনতপুর) It is mentioned in Vayu Purana (োয়ুপুরাণ) and Bharat Samhita (ভারত িংষ্টহতা; 6th century CE). Archaeologists found a fortified city in this site which the area of which measures almost 1800 x 1500 ft (Rahman, 2012).

Pundranagar (Mahasthangarh; র্হাস্থান쇍ি): Capital of Pundravardhana, located in Bogra district, Bangladesh. The Mahabharata mentioned Pundra as a Janapada and later Pundravardhana was mentioned by Hsuan Tsang. It is situated at the bank of River Korotoa (করগ্বতায়া). A fortified city has also been found which is rectangular and measures about 1523m in north-south direction and 1371m in east-west direction. The city had moats within its periphery Radio carbon dating has determined its earliest date to be 371 BCE, which refers to the Mauryan Empire. But eminent archeologist and researcher Dr. D.K. Chakrabarti argues that human settlement started long before in this location and the city developed as its continuation (Rahman. 2012). The latest city wall dates back to 100 BCE to 100 CE and was made of complete burned brick. Hsuan Tsang had seen 20 Buddhist Viharas (ষ্টেহার) and 100 Hindu temple while travelling during 639-645 CE.

Chandraketugarh (চন্দ্রগ্বকতু쇍ি): Located in 24 Pargana district of West Bengal; situated at the alluvium planes at the junction of Vidyadhari (ষ্টেদযাধরী) River (branch of Bhagirathi River) and Padma River. According to Archaeological Survey of India, the probable period for earliest settlement in this place dates back to 7th -6th century BCE. Although temples and houses are found to be made of brick, researchers believe that brick was first used during the Gupta period. Before that mud was the major building material. Nevertheless, Terracotta and burned brick became the principal component of construction. Some researchers suspect Chandraketugarh to be the old port Ganges as described by Ptolemy and Periplus. It was a famous riverine port (Rahman, 2012).

Kotasura (বকািািুর), Pokhanna (বপাখান্ন), Dihara (ষ্টদহার) and Mangalakota (র্ঙ্গলগ্বকাি): These settlements were part of the Rarha Janapada situated at West Bengal. Kotasura was situated in Birbhum at the bank of Mayurakshi (র্য়ূরাক্ষী) River, Pokhanna in Bankura (োাঁকুিা) at the bank of Damodor (দাগ্বর্াদর), Mangalakota in Bardhaman (েধুর্ান) at the junction of River Kunur (কুর্ার) and Ajay (অজয়). Rarha was the center of life during the Neolithic and Chalcolithic period. Traces of the oldest agrarian society of Bengal has been discovered in this region. The inhabitants prospered in agriculture and as a result adopted urbanization during the pre-historic period. A city wall made of mud with moats surrounding it of almost a kilometer long circumference has been found in Kotasura. Pokhanna is suspected to be a town persisting in Gupta or early Gupta period. Urbanization began in Manglakota during the Mauryan-Sunga-Kushana period. Dihara was also a settlement from per-historic period.

Wari-Bateshwar (উয়ারী-েগ্বিশ্বর): Wari-Bateshwar was a town center during the second urbanization. It is located in Narsingdi (নরষ্টিংদী) along the old Brahmaputra River, having Koyra and Arial Khan River at proximity (Figure 2.12). According to D.K.Chakrabarti, Wari- Bateshwar was most probably the capital of Louhitya Janapada (বলৌষ্টহতয জনপদ). Other researchers believe it was the capital of either Samatata (ির্তি) or Banga. Some suggests that it was the famous ’Gangaridae’ that can be found in the writings of Diodorus, Plutarch and Virgil. Ptolemy probably mentioned it as ‘Sonagoura (বিানাগ্ব쇍ৌিা)’. The fortified city had two walls, one around the fort and another a primary wall around the city locally known as ‘Asama Rajar Garh (অির্ রাজার 쇍ি)’. Around the primary wall there was a moat. The city had satellite settlement within

57 its proximity which are located in Raingar Tek (রাইঙ্গার বিক), Puber Tek (পুগ্বের বিক), Algar Tek (আল쇍ার বিক), Sonarutala (বিানা쇁তলা), Haniabaid (হাষ্টনয়াোইদ), Amlab , Ichhar Tek (ইছার বিক), Kandua (কান্দুয়া) and many other places. It was a famous and prosperous trade center. It was also a river port. Archaeological artifacts indicates that this city had trade relationship with the Roman Empire. According to Dr. Sufi Mustafizur Rahman, Wari- Bateshwar was connected with the world famous trade route the ‘silk road’. The principle building material of this city has been found to be brick, which according to Gordon Child is a specific character of urbanization. Radio carbon dating has determined the period of city to be 450 BCE. Although pit dwellings from almost 1500 BCE and stone axes from Neolithic period proves the existence of human settlement before urbanization (Rahman, 2017).

Among the recent discoveries, Bhitargarh (ষ্টভতর쇍ি) is located at Panchgarh (পঞ্চ쇍ি) which is almost 1500 years old from today (Figure 2.13). This was also a quadrangular fortified city with an area of 25 sq.km surrounded with brick walls with 10 water reservoirs within its perimeter. Discoverer archeologist Dr. Shahnaj Husne Jahan suspects that the city had trade connection with Tibet, Sikkim, Nepal, Bhutan, Assam, Cooch Behar and lower valleys of the Ganges (Yusuf, 2016).

The above discussion regarding the Vedic city planning scheme shows that the civic architects in Vedic era were well aware of the roll of streets and open spaces as an element of urban morphology. The streets and open areas were consciously perceived as spaces for circulation and social interaction. The suggestions as per Vedic codes provide thorough instructions regarding the features, use and management of streets. Environmental rationales also talk about solar exposure and wind flow. This research aims to find out to which extent theses rationales were applicable.

Figure 2.12: Archeological excavation at Wari-Bateshwar

Figure 2.13: Archeological excavation at Bhitargarh

2.5 Contemporary principles of city planning by Vitruvius

One of the first treaties on architecture in the west is ‘De Architectura’ by Marcus Vitruvius Pollio written between 30-15 BCE, which can be broadly said to be contemporary to the recording phase of Vedic literary sources regarding architecture and town planning. Vitruvius was inspired by the principles of architecture developed by the Greeks during the classical period. Among the ten treaties contained in this publication, the Book I has significantly similar contents width the Vedic scriptures. The book describes the education of the architect, the fundamental principles of architecture, the departments of architecture, the site of a city, the city walls, the directions of the streets (with remarks on the winds) and the sites for public buildings (Morgan, 1914).

Vitruvius posed that the architect would need a holistic education in order to understand the various aspects of the citizens. He argued that the architect would require expertise in the fields of: draftsmanship, arithmetic, geometry, history, philosophy, music, medicine, climate, law and astronomy (Morgan, 1914).

Vitruvius developed a system of anthropometric proportions which was widely adapted in the art and architecture during the classical and renaissance period. He said that architecture depends on order, arrangement, eurhythmy, symmetry, propriety and economy. The three departments of architecture described by him are the art of building, the making of timepieces and the construction of machinery. The building had been categorized into the construction of fortified towns including public places and structures for private individual (Morgan, 1914).

According to this book, the site for a settlement should be elevated, not cloudy, not liable to frost, away from the areas prone to intemperate climate and away from swamps. The physical parameters of a settlement were largely governed by the defense mechanisms and specific concerns for the four medical humor, i.e. the yellow bile, black bile, phlegm and blood as described by the Greeks. However, Vitruvius suggested to plan the streets based on the wind pattern of a site and the streets should be laid out at angles oblique to the wind flow. He also told that in summer, the heat makes people weak and be beware of the districts from which hot winds can spread abroad over the inhabitants (Morgan, 1914).

Figure 2.14: Diagram of Wind, from the edition of vitruvius by fra giocondo, venice, 1511 (Morgan, 1914)

Vitruvius developed a diagram of the wind pattern (Figure 2.14). As for seasonal effects cold winds have been classified as disagreeable, hot winds enervating, moist winds unhealthy. Winds are suggested not to enter the interior of the dwellings as it would increase the health condition the well and the patients already suffering from diseases. The patients would have a better chance of recovery from the mildness that comes shutting out of the winds (Morgan, 1914).

2.6 Climatic Imperatives

This section will discuss about the scientific notion of ‘thermal comfort’ in outdoor spaces. The various determinants of thermal comfort will be presented and the relevant determinants will be selected for studying the environmental design thinking of Vedic urban designers.

2.6.1 Thermal comfort

“Thermal comfort is that condition of mind, which expresses satisfaction with the thermal environment” (ASHRAE, 1958). Although, comfort for both indoor and outdoor spaces is expressed in terms of a number of quantifiable environmental variables like air temperature, radiant temperature, relative humidity, air flow and their effect is synergistic, non-thermal factors are also works as determinants (Ahmed, 1996). Thermal comfort judgement can be significantly influenced by olfactory, acoustic and visual environment. Hence, comfort is not only a sensory phenomenon but largely one of perception (Fisher, 1978; Bansal, 1994; cited from: Ahmed, 1996).

It is possible that the requirements for the determinants of thermal comfort may vary from person to person within the same environment. The indeterminacy of categorizing comfort in a changing environmental condition that is of urban climate is quite apparent with regard to a group of people. The designer’s task is to provide a comfortable environment to a majority of people, with a minority of people still remaining dissatisfied (Ahmed, 1996).

2.6.2 Determinants of thermal comfort in outdoor urban environment

The ranges of factors that influence thermal comfort in outdoor urban environment can be broadly categorized into the following three:

a. Physiological determinants b. Behavioral determinants c. Environmental determinants

2.6.2.1 Physiological determinants

‘Metabolic rate’ and ‘Acclimatization’ are the major physiological determinants. The body generates energy through the process of metabolism, a little part of which is utilized by the body, while the rest is discharged to the environment. Metabolic rate means the rate of heat liberation. It is directly related to the age, sex, nutrition, level of activity and relevant factors. The relative thermal tolerance of a person is adjusted through the process of acclimatization. For example, the adaptive mechanism of human body increases the sweating and lowers the metabolic rate when exposed to a hot environment and it takes about 1 to 6 weeks for a person to be acclimatized in such condition (Ahmed, 1996).

2.6.2.2 Behavioral determinants

Psychological adaptation enables a person to be alert when exposed to an extreme environment which results in behavioral adjustment ranging from simple action of changing the cloth to complex action of migration. The thermal resistance of clothing (measured in Clo; 1 Clo=.0155 m2 ℃/ W) and the level of albedo of a person (depends on pigmentation of the skin and color of clothing) are the measurable determinants of ‘clothing’. ‘Migration’ can be observed in both outdoor and indoor environment as a means of altering to a favorable environmental setting by changing location. When people are subjected to a variety of environmental conditions within a same setting - which vary from warm to cool or from dark to light, they often seek out preferred condition. This behavior is known as ‘Tropism’ (Ahmed, 1996).

In tropical urban environment and in many Mediterranean cities, it has been observed that people tend to follow the shaded paths while walking, which are generated by the building geometry and foliage of the trees planted along them. Very often people choose to walk on a crowded but shaded sidewalks in outdoors, while the other side of the road remain unoccupied, irrespective of the ambient temperature. Thus seeking shade is a spontaneous behavior of ‘Tropism’ which is stimulated be solar radiation (Ahmed, 1996).

2.6.2.3 Environmental determinants

The principal environmental factors are dry bulb temperature, radiant temperature, relative humidity and air flow. Their effect on comfort is not individual but synergistic.

Air temperature: Heat exchange by free or forced convection is directly related to the dry bulb temperature of the environment. Heat loss is induced when the air temperature is less than the skin temperature (Ahmed, 1996). Expressed in ℃ (degree Celsius).

Radiation: All thermally excited surfaces in an environment emit radiation in different directions. Radiant temperature indirectly indicates the intensity of radiation field. In outdoor environment the sun is the source of short wave radiation and all other terrestrial bodies or surfaces emit long wave radiation. Radiation, whether long wave or short, can directly excite the thermal receptors of human body (Ahmed, 1996).

Solar Irradiance is a variable which can indicate the level of solar radiation. Solar Irradiance is the sun’s radiant energy incident on a surface of unit area, expressed in W/m2 or kW/m2.

Incident solar radiation, also termed insolation, refers to the wide spectrum radiant energy from the Sun which strikes an object or surface. This includes both a direct component from the Sun itself (sunshine), a diffuse component from the visible sky (skylight) and a reflected component from other vertical surfaces and the ground. Insolation is expressed in Wh/(m2 day).

Relative Humidity: The moisture content in the air is expressed in terms of relative humidity. It is the ratio of the actual amount of moisture present to the amount of moisture air could hold at the given temperature expressed as percentage. Heat loss by

63 means of skin diffusion, respiration and sweat evaporation is directly affected by the relative humidity. It varied diurnally and may also vary between different microclimate within a given period of time. In urban environment, humidity can be increased locally by passive or semi-passive means (Ahmed, 1996).

Air Flow: Air velocity also influences the convective and evaporative cooling. But if the air temperature is greater than skin temperature, it induces heat gain of the body. In warm humid climate, where air temperature is below skin temperature, increasing the air velocity can cause considerable heat loss. The Beaufort scale provides the mechanical effects at various flow rate (Ahmed, 1996). Air velocity is expressed in m/s (metre per second).

Temporality: Time is an important factor in determining the comfort boundaries because the extent of response may vary with the length or duration of a particular stimulus which can directly influence the tolerance level. Also, the perception of comfort is not a fixed experience. People tend to find comfort in various environmental conditions (Ahmed, 1996).

Among the range of determinants of thermal comfort discussed above, the variables which are consistent with the rationale of Vedic architects are solar insolation, shadow condition and wind flow in case of open space.

2.7 Critical findings from literature review a) Among the four elements of morphological dimension of urban design, the street or cadastral pattern and the plot pattern which are also the key components of capital web are relatively permanent and consistent than the built structures and land use. The Vedic building bye-laws also emphasizes on laying out the streets as the primary step for planning a city. b) The units of measurements were derived based on ergonomic data. For ease of further discussion, only the danda (equivalent to 6ft or 1.8288 m) has been taken into account. c) The Indo-Aryan village can be conceived both as an isolated entity or a module for larger settlements. The treaties provide orthogonal and radial cadastral patterns for different types of village. For this research, the orthogonal diagrams with indicated

cardinal directions are followed. Diagrams with similar plot patterns are counted as one. d) The shortest length of a quadrangular village or any settlement has been found to be 300 dandas. The length to width ratio of rectangular settlements has been

1 1 suggested to be 2:1, 1¾:1, 1½:1, 1¼:1, 1 ⁄6:1, 1 ⁄8 :1 or 1:1. e) The two principal streets, the Brahmavithi and Mahakalavithi along with the Mangalavithi has been considered to be 5 dandas wide. All the other streets, the Rajapatha, Vamanapatha, Vithi and Marga has been considered to be 2 dandas wide. f) As vehicles were non-motorized, the ‘movement space’ and ‘social space’ of the streets significantly overlapped. Both the literary sources and the case studies reveal that the streets were social spaces. The principal roads Brahmavithi and Mahakalavithi were used as trade routes and commercial functions. Dedicated pedestrian streets termed as Padya was being provided along with ordinary market streets Vithis and Marga. The streets also used to house social, cultural and religious programs. g) The suggested floor numbers in the literary sources varies from one to eleven stories. However, case study of Jaipur displays the maximum stories of built structures of the capital to be four given the tertiary street width of 27 ft or 4.5 dandas. As this research uses the width of the Mahakalavithi and Brahmavithi to be 5 dandas, the maximum number of floors has been considered to be four. The peripheral plots or blocks has been considered to be two-storied and intermediate blocks has been considered to house built forms with three stories. The building heights of the same plot or block has been considered to be same as per the bye- laws. h) The literary sources depicts a definite system for folk planning based on the caste system. However, the case studies shows significant inconsistency regarding following the principles or it may be assumed that the land use changed over time. As all the information regarding street pattern, plot pattern and height of the built forms can be derived without this data, the research does not include the folk planning or Padavinyasa into consideration.

65 i) Although, the building materials used by the Indo-Aryans ranges from wood to stone, the settlements of Bengal shows the principal materials to be burnt brick in both buildings and road surfaces. Therefore, the simulation of this research will use brick as the building material and external paving for road surfaces. j) The environmental rationales suggested in the literary sources are mostly developed by empirical knowledge as scientific terms and tools of modern age to quantify the relevant variables were not discovered. The variables in discussion are interpretable by means of sensory perception. Hence, the principle environmental design components are sun, wind and rain. This research therefore find Solar Insolation, shadow condition and wind velocity as the dependent variable which are frequently discussed in the treaties. Solar Insolation and wind velocity are environmental determinants and shadow condition of the streets represents ‘Tropism’, a behavioral determinant of Thermal comfort.

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Chapter 3 SIMULATION AND ANALYSIS

3. Simulation and analysis

3.1 Preamble

Chapter 2 provides the basic information regarding both independent and dependent variables. This chapter contains the detail steps of the methodology to conduct simulation in order to determine the environmental performance in terms of solar insolation, shadow condition and wind flow.

This chapter identifies the contextual information regarding the location and weather which is followed by sampling process to select the subjects to be analyzed as well as determine the morphological and built-environment parameters. Separate simulations will be conducted to obtain the quantitative performance of the dependent variables.

The results will be analyzed in a cumulative manner to determine the comprehensive performance based on the three environmental criteria. A causal-comparative analysis will be done to find the relationship between the independent and dependent variables.

3.2 Methodology for simulation

The microclimate of Dhaka has been thoroughly studied as it has been selected as the location for which the environmental variables will be determined. Valid simulation tools has then been chosen to conduct the simulation. The criteria for sampling the settlement pattern for selecting the case villages has then been set. Based on the cadastral pattern, plot pattern and width of the streets found from literature review, the scale diagrams has been prepared. Each diagram has been produced with three different length to width ratios. After that, the most connected streets has been identified by running axial connectivity analysis. The heights of the plot or blocks has then been incorporated based on information found from the literary sources and case studies. This step also determines the height to width of the case streets. Information regarding material and bounding condition has also been provided as built environment parameters. Orientation of the settlements following the cardinal directions has been settled. Based on the above considerations, the performance of the streets of all the settlements has been determined by conducting separate simulations for insolation analysis, calculating overshadowing percentage and identifying wind velocity. These three different variables for each settlement pattern has then been assimilated in a

72 cumulative score by developing a method for determining performance indicator. The results of these scores are then analyzed in a causal-comparative manner to find out the relationship between the input and output variables.

Figure 3.1: Methodology for Simulation and Analysis

3.2.1 Microclimate of Dhaka

The city of Dhaka lies between longitude 90º20’E and 90º30’E and between latitudes 23º40’N and 23º55’N. Dhaka experiences a hot, wet and humid tropical climate. Under the Koppen climate classification, Dhaka has a tropical savanna climate. The city has a distinct monsoonal season, with an annual average temperature of 27.5°C (81.5°F) and monthly means varying between 19.5°C (67°F) in January and 32°C (90°F) in April .Dhaka City has mainly three distinct seasons – the hot dry (March-May), the hot humid (June-November) and the cool dry season (December-February).

Generally the cool dry season is short while the summer is long and wet. April is the hottest month with average maximum temperature that varies from 30.3ºC to 34.8ºC and January is the coldest month with average temperature ranging from 9ºC to 15.2ºC. Although overheating is the major problem of Dhaka City, it is due to some associated factors. For example, it is observed that from March to May there is high air temperature associated with high solar radiation (Joarder, 2007) (Figure 3.2).

Figure 3.2: Hourly solar radiation averaged by month for TRYs, Dhaka (source: U.S. Department of Energy, 2008). From June to October, conditions with high humidity are associated with high air temperature. So from March to May, minimizing the impact of solar radiation can potentially moderate the overheated condition, whereas from June to October maximizing wind flow can contribute to minimize the over-heating situation. This is the overall climatic condition of Dhaka city related with basically thermal environment (Table 3.1). However, the luminous environment of the city is related to the duration of

74 sunshine hours and sky condition, two major climatic factors determining the quality and quantity of daylight. These two are discussed separately below.

Table 3.1: Climate data of Dhaka (Climate, 2018).

Climatic Period Cool-dry Hot-dry Warm -humid Warm -humid

Month Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov

a .Maximum air

temperature 26.4 25.8 28.1 32.5 33.7 32.9 32.1 31.4 31.6 31.8 31.6 29.6

b. Minimum air

temperature 14.1 12.7 15.5 20.0 23.6 24.5 26.1 26.2 26.3 25.9 23.8 19.2

RH% 73 71 64 62 71 76 82 83 82 83 78 73

Rainfall 7.7 12.8 28.9 65.8 34.4 156.3 339.4 340.4 373.1 316.5 300.4 172.3

UV index 6 6 8 9 7 10 12 12 12 12 12 11

Daylight hours 11 11 11 12 13 13 14 13 13 12 12 11

Sunshine hours 9 9 8 7 6 5 3 2 2 3 6 8

Wind speed 2.5 .092 1.23 1.60 4.21 3.80 3.70 3.64 3.21 2.24 1.28 0.93

Wind Direction N,S-W S,S-E S,S-E,S-W S,S-E

3.2.2 Sunshine hours and sun path diagram

Daylight availability of any locations is influenced by latitude and weather patterns (A.G.S. 2000). In the cool period Dhaka has more than 8 hours of sunshine per day. But during monsoon months (warm-humid season) this comes down to 4 hours per day due to cloud cover. It is after June and July that this once again increases steadily (Joarder 2007). Figure 3.3 shows the monthly average sunshine hours of 2015 for Dhaka city.

Figure 3.3: Average monthly hours of sunshine of Dhaka over the year (Source: World Weather Climate and Information data report, 2015

The atmospheric condition during the month of July to November period is cloudy. So, the diffused component of the daylight is considerably high. The variation in sunshine hours during July to November is wide. Figure 3.4 shows the sun path diagram of Dhaka, Bangladesh.

Figure 3.4: The sun path diagram of Dhaka, Bangladesh (Source: SUNTOOL - Solar Position Calculator, 1998)

3.2.3 Sky condition

Dhaka has a composite climate, where both clear sky, overcast and partly overcast skies are observed round the year (Figure 3.5), and designers have to face difficulties while considering both sky conditions (Ahmed, 1987).

Figure 3.5: Sky condition of Dhaka city (Ahmed, 1987).

Direct sunlight is intense and varies substantially as the sun's position changes throughout the day (up to 1, 00,000 lux). Daylight from a clear sky can be 10 to 25 % of the intensity of direct sunlight (10000–25000 lux). Daylight under partly cloudy conditions can vary largely; daylight under full overcast conditions can be 5% to 10% of sunny conditions (5000-10000 lux).

Figure 3.6: Monthly average cloud cover and monthly average sunshine hours in Dhaka (Source: Bangladesh Meteorological Department, Dhaka, 2005; cited from: Rahman, 2007).

In context of Dhaka, the sky remains clear and overcast in different parts of various seasons (Figure 3.6). During summer (Hot Dry), the sky remains both clear (sunny with sun) and overcast. During the warm-humid (March-November) period, the sky remains

77 overcast considerably. During monsoon (June-September) which is one third of the whole year the sky remains significantly overcast. During the winter (December- February) the sky mostly remains clear. While during the rest of the year, both clear and overcast conditions are observed (Joarder 2009a: 2009c). Table 3.2 shows sky condition of Dhaka city with respect to cloud cover for a year.

Table 3.2: Sky condition with respect to cloud cover over a year round. (Source: Climatic Division, Bangladesh metrological department, Dhaka, 2005).

Pre-monsoon Monsoon Post- Cool Dry Total Type of sky Monsoon (March-May) (Jun-Sept) (Oct-Nov) (Dec-Feb) (day)

Clear sky 62 38 39 77 215

Overcast sky 30 84 22 14 150

Total sky 92 122 61 90 365

3.2.4 Annual wind flow condition

In case of wind the majority cases in summer time in Dhaka city wind comes from south and southeast direction (Figure 3.7(a)), which is approximately 42% of all the wind coming from all directions. According to section 2.4.1 the wind flow coming from

Wind Direction and Percentage for Dhaka City

NW 10% W 5% SW 9% S 32% SE 20% E 8% NE 8% N 7%

0% 5% 10% 15% 20% 25% 30% 35%

Figure 3.7(a): Average wind direction of Dhaka city (January 2000 - December 2008) (Source:www.weatheronline.co.uk/weather] southeast and southwest is mostly during monsoon and summer period respectively. The wind frequency with the directions are shown in figure 3.7(b).

The data showed in figure 3.7(a) was collected at a height of 10m from ground. The data is referring to the wind pattern in Dhaka city. The maximum wind flow comes from south with the wind speed of 2.78 m/s for more than 632 hours and 568 hours of wind flow comes from south with the wind speed of 4.18 m/s. Sometimes the wind speed can reach up to 13.88 m/s speed from north, northeastern side, east, southeast and south. But the highest wind speed of 13.88 m/s mostly comes for 63 hours. Majority of the time the wind speed remains between 0 m/s to 5.56 m/s.

Figure 3.7(b): The duration of the prevailing wind of Dhaka city (cited from: Debnath, 2014)

3.3 Selection of simulation tools

Several simulation tools have been used in this research for identifying axial connectivity, insolation level, overshadowing percentage and wind flow. For axial

79 connectivity ‘UCL Depthmap’ developed by the Bartlett School of Architecture, University College London has been utilized. Autodesk Ecotect Analysis has been used for measuring the insolation level and overshadowing percentage. For wind simulation, ‘Autodesk Flow design’ has been used, which is practically a virtual wind tunnel.

UCL Depthmap is primarily a computer program to perform visibility analysis of architectural and urban systems. It takes input in the form of a plan of the system, and is able to construct a map of 'visually integrated' locations within it.

In addition, the most recent version of UCL Depthmap now supplies a range of configurational analyses which come under the umbrella term of 'space syntax' (Turner, 2004).

All the solar position, solar radiation and thermal load calculations supported by Autodesk Ecotect Analysis conform to and are validated against ‘CIBSE TM33 (2006) Tests for Software Verification and Accreditation’. Solar access and rights-to-light calculations conform to the ‘BRE Site Planning Handbook’ (Validation, 2014).

Ecotect Analysis’s specific use of the admittance method is based on ‘ISO 13791:2004 Thermal performance of buildings’ and ‘ISO 13792:2005 Thermal performance of buildings’ as well as parts of ‘ISO 13789:1999 Transmission heat loss coefficient - Calculation method’ (Validation, 2014).

For architectural applications, Autodesk Flow design is suitable, especially for analyzing wind behavior in outdoor spaces. Flow design can predict wind behavior around closed buildings (not considering indoor spaces) and provide an understanding of whether there are risks of elevated velocities and/or stagnant regions. The resultant information can play a vital role for designing outdoor spaces and areas by articulating the built form in order to ensure outdoor air quality (Flow Design, 2014).

3.4 Selection of case diagrams

Among the fifteen types of Vedic Villages mentioned in the previous chapter, ‘Town Planning in Ancient India, 1925’ by Binode Behari Dutt presents the schematic diagram for eight villages: Dandaka, Sarvatobhadra, Prastara, Swastika, Chaturmukha, Nandyavarta, Padmaka, and Karmuka. Although the first five types of these villages have orthogonal street patterns, the principle for laying out street for Padmaka and

Karmuka is omnidirectional. Also, there are three diagrams for Nandyavarta; for square, rectangular and circular shaped settlements; which makes the total number of diagrams to be ten (Figure: 2.4). The diagram for circular settlement is also omnidirectional and have radial cadastral network. For simulating environmental performance, this research considers the diagrams with layout that provide specific cardinal direction. Therefore, omnidirectional diagrams have not been considered for study and hence, Padmaka, Karmuka and the circular diagram for Nandyavarta were not selected as case diagrams. Among the orthogonal diagrams, the plot division principle for Chaturmukha is geometrically the same (although, the Padavinyasa is different in many other terms) as Sarvatobhadra for which it was not considered for studying environmental performance in order to avoid repetition.

Through the above process of elimination, six case diagrams have been selected with orthogonal street and plot division: Dandaka, Sarvatobhadra, Nandyavarta (for square and settlement), Nandyavarta (for rectangular settlement), Prastara and Swastika. The diagrams even have direction towards the east.

From the discussion regarding bounding condition from the previous chapter, we find

1 1 that Mayamata suggests the length of the settlements to be 2, 1¾, 1½, 1¼, 1 ⁄6, 1 ⁄8 or 1 times the breadth. For this particular research, the ratio for length to breadth has been considered to be 2:1, 1½:1 and 1:1; which are the two marginal and one mean value of the suggested proportions. The bounding conditions also suggest that the shortest length of a quadrangular village or any settlement has been found to be 300 dandas (equivalent to 548.78m). Taking this length into account, the area of a square settlement is calculated to be 90,000 square dandas or 301,159.48 sq.m. Considering this as the base area, the length and width of the settlements with the above selected ratios 2:1, 1½:1 and 1:1 are deducted (rounded to meters) to be 780m x 390m (426 dandas x 213 dandas), 675m x 450m (369 dandas x 246 dandas) and 548m x 548m (300 dandas x 300 dandas) respectively. A 9 dandas (15 m) wide moat has been considered at the periphery of the settlements. No walls has been considered as walls were not a mandatory feature as bounding condition for Vedic villages as they were for towns and cities. Various length to breadth ratio for a single type of village will be useful to compare the environmental performance between deeper and linear settlements.

The two principal streets, the Brahmavithi and Mahakalavithi along with the Mangalavithi has been considered to be 5 dandas wide, which is equivalent to 9m. All the other streets, the Rajapatha, Vamanapatha, Vithi and Marga has been considered to be 2 dandas or 4m wide. The Rajapatha and Vamanapatha for Dandaka has been considered to be 3 dandas or 6m wide as the description suggests.

Given the above information, fifteen settlement patterns has been generated from the selected six case diagrams. Dandaka, Sarvatobhadra, Prastara and Swastika; each of these diagrams produce three settlement patterns with the above mentioned ratios. A single settlement pattern with length to width ratio1:1 has been generated from Nandyavarta diagram for square settlement and two patterns has been produced from Nandyavarta diagram for rectangular settlement. The settlement pattern generation process involved laying out the streets and dividing the plots; which are two essential elements of the ‘Capital Web’; following the proportions of the diagrams and incorporating the above mentioned measurements.

A coding system has been followed to identify and classify the streets in each settlement pattern in easier manner. As all the settlement patterns are orthogonal and essentially symmetric (except Prastara), the patterns are divided into four equal quarters: North- East (NE), South-East (SE), South-West (SW) and North-West (NW). The central roads, Brahmavithi and Mahakalavithi are termed as BrV and MhV. The peripheral road Mangalavithi is termed as MngV. The other streets are categorized according to their orientation. The streets elongated towards east-west direction (Rajapatha, which in short this research will refer as RP) are numbered with alphabets and the streets elongated towards north-south direction (Vamanapatha, n short VP) are numbered with numerals. The streets closer to the center of the pattern (as well as the central streets along both cardinal axes) have the beginning character and this character, in association with the quarter initials indicate the position of the street. For example, SE-2 indicates the second north-south oriented street (Vamanapatha) from the center of a settlement pattern as well as the Mahakalapatha of the same and residing on the South-East quarter. Similarly, NW-C indicates the third east-west oriented street (Rajapatha) from the center of a settlement pattern as well as the Brahmavithi and residing on the North- West quarter. All the settlement patterns are presented in figure 3.8-3.12.

:1 Length to Width Ratio 1 Length Width to Ratio

:1 Length to Width Ratio 1.5Length Width to Ratio

ength to Width Ratio 2:1 ength Width to Ratio L

Figure 3.8: Settlement Pattern for Dandaka with different length to width ratio

:1 Length to Width Ratio 1 Length Width to Ratio

:1 Length to Width Ratio 1.5Length Width to Ratio

ength to Width Ratio 2:1 ength Width to Ratio L

Figure 3.9: Settlement Pattern for Sarvatobhadra with different length to width ratio

:1 Length to Width Ratio 1 Length Width to Ratio

:1 Length to Width Ratio 1.5Length Width to Ratio

ength to Width Ratio 2:1 ength Width to Ratio L N

Figure 3.10: Settlement Pattern for Nandyavarta with different length to width ratio

:1 Length to Width Ratio 1 Length Width to Ratio

:1 Length to Width Ratio 1.5Length Width to Ratio

ength to Width Ratio 2:1 ength Width to Ratio L

Figure 3.11: Settlement Pattern for Swastika with different length to width ratio

:1 Length to Width Ratio 1 Length Width to Ratio

:1 Length to Width Ratio 1.5Length Width to Ratio

ength to Width Ratio 2:1 ength Width to Ratio L

Figure 3.12: Settlement Pattern for Prastara with different length to width ratio

3.5 Axial connectivity study and selection of case-streets:

Among the four syntactic measures, Connectivity, Integration, Control value and Global Choice; which are used to represent the streets or spaces of an urban layout in quantitative manner. ‘Connectivity’ represents the number of immediate neighbors that are directly connected to a street or space. In other words, Connectivity (and Integration) shows how good (or bad) a certain place/street/ street segment is integrated in the whole street network. Connectivity represents how often a street is connected to another street (Turner, 2004). High Connectivity as well as Integration value is directly correlated with convenience for a pedestrian in traveling street network environments (Mohammad, 2014). Which eventually implies that the most connected streets will have the highest population density than the other streets.

As learned from the previous chapter, that the overlapping realms of ‘movement space’ and ‘social space’ are accommodated within the public space network. As the principle modes of transport in Vedic period were by foot and non-motorized vehicles, the movement space and social space had considerable overlap. ‘Social Space’ refers to outdoor space where people can engage themselves in economic, social and cultural activities. Street as a social space is augmented by pedestrian movement. Therefore, it can be assumed that, in Vedic period streets with high Connectivity value used to have more social functions than the other streets. The literary sources also inform that the Brahmavithi and the Mahakalavithi were principally used for trade and commerce purposes. Internal Vithis were narrow lanes with small shops.

Axial Connectivity Study using UCL Depthmap software reveals the highest connected streets of the generated settlement patterns in order to select the case streets upon which commencing the environmental study shall be rationally justified as it will focus on the most active street of a layout. After running a ‘Global’1 simulation, the software shows

1 Global integration takes into account the distance from the starting point to all points in the system (Hillier, 1984). A correlation was found between integration values and human appearance in the space. The more integrated the space is, the more people will appear in that space. The relationship between the global availability of space (global integration), and the local availability of space (local integration) is the clarity and readability of the

88 color codes for representing connectivity; red being the highest connected, yellow as moderately connected and blue as the lowest connected pathways. The software also shows connectivity values in numbers. The resultant axial lines can be reduced to a simplified line diagram which also provides the gist of the connectivity scenario.

According to the axial connectivity study, the Brahmavithi and Mahakalavithi for all the settlement patterns are the highest connected streets, which also complies with the codes as per suggested in the literary sources. However, the highest connected Rajapath and Vamanapath varies for each type of villages and in cases for each quarter of a settlement pattern. To be noted, the rectangular settlement patterns for Nandyavarta have no central roads on any axes. The Mangalavithis for all the case diagrams are the least connected streets for which they are not considered as subjects for measuring environmental performance further in this research. The chart for connectivity values for all the streets are presented in appendix. The connectivity values of the highest connected streets for the four quarters of each diagram are shown in Table 3.3. The simulation results are presented in Appendix A.

As all the diagrams except Prastara are symmetric, the connectivity value of a Rajapatha or Vamanapatha of a single quarter of a particular diagram is similar to the corresponding streets of other quarters. Hence, this research aims to select these streets from a single quarter in order to avoid repetition. Since, Prastara is asymmetric, its streets from different quarters have different values, where the highest cumulative value for both Rajapatha and Vamanapatha can be observed in the south-east quarter. In reference to that, this research selects the Rajapatha and Vamanapatha from the South- East (SE) quarter of every settlement pattern for further environmental analysis. The selected case streets are marked with color in Table 3.2 and shown in figure 3.13.

space (intelligibility). The better the correlation between these measures, the better user moving along a given axis is oriented in space and knows where they are in the context of the entire city (Dettlaff, 2014).

3.6 Introducing built-environment parameters for three-dimensional model generation

In order to determine the environmental performance like Insolation, Shadow Condition and Wind Velocity in the streets, the relevant built environment parameters and building materials are required.

From previous chapter, it can be found that all the buildings of an individual block should have similar size. Although, the suggested floor numbers in the literary sources varies from one to eleven stories, case study of Jaipur displays the maximum stories of built structures to be four given the tertiary street width of 27 ft or 4.5 dandas. As this research uses the width of the Mahakalavithi and Brahmavithi to be 5 dandas, the maximum number of floors has been considered to be four. The peripheral plots or blocks has been considered to be two-storied and intermediate blocks has been considered to house built forms with three stories. Therefore, the corresponding heights in S.I. unit are 12m, 9m and 6m respectively assuming a floor height of 3m.

The literature review also suggests the principal material for buildings and road surfaces in the settlements of Bengal in the Vedic era was essentially burnt brick. Although, the building materials used by the Indo-Aryans ranges from wood to stone Therefore, the simulation of this research will use ‘Brick- Timber Frame’ as the building material and ‘External Paving’ for road surfaces. ‘Brick- Timber Frame’ is considered to be consisting of 100mm external brick with 75mm timber frame and 10mm plasterboard inside. ‘External Paving’ is considered to have 1500mm of ground beneath it. The properties of these materials are shown in Table 3.4.

Table 3.3: Connectivity values of the highest connected streets

RP VP Diagram Ratio BrV MhV NE Value SE Value SW Value NW Value NE Value SE Value SW Value NW Value 1:1 169 169 NE-A 127 SE-A 127 SW-A 127 NW-A 127 NE-1 141 SE-1 141 SW-1 141 NW-1 141 Dandaka 1.5.1 169 169 NE-A 128 SE-A 128 SW-A 128 NW-A 128 NE-2 142 SE-2 142 SW-2 142 NW-2 142 2:1 169 169 NE-A 129 SE-A 129 SW-A 129 NW-A 129 NE-3 143 SE-3 143 SW-3 143 NW-3 143 1:1 645 645 NE-B 475 SE-B 475 SW-B 475 NW-B 475 NE-2 475 SE-2 475 SW-2 475 NW-2 475 Sarvatobhadra 1.5.1 645 645 NE-B 476 SE-B 476 SW-B 476 NW-B 475 NE-2 475 SE-2 475 SW-2 475 NW-2 475 2:1 645 645 NE-B 477 SE-B 477 SW-B 477 NW-B 475 NE-2 475 SE-2 475 SW-2 475 NW-2 475 1:1 254 254 NE-B 100 SE-B 100 SW-B 100 NW-B 100 NE-2 100 SE-2 100 SW-2 100 NW-2 100 Nandyavarta 1.5.1 N/A N/A NE-C 57 SE-C 57 SW-C 57 NW-C 57 NE-4 57 SE-4 57 SW-4 57 NW-4 57 2:1 N/A N/A NE-C 57 SE-C 57 SW-C 57 NW-C 57 NE-4 57 SE-4 57 SW-4 57 NW-4 57 1:1 201 206 NE-C 108 SE-A 108 SW-C 108 NW-A 108 NE-1 111 SE-4 111 SW-1 111 NW-4 111 Swastika 1.5.1 201 206 NE-C 108 SE-A 108 SW-C 108 NW-A 108 NE-1 111 SE-4 111 SW-1 111 NW-4 111 2:1 201 206 NE-C 108 SE-A 108 SW-C 108 NW-A 108 NE-1 111 SE-4 111 SW-1 111 NW-4 111 1:1 578 578 NE-C 255 SE-C 424 SW-B 489 NW-E 255 NE-1 476 SE-2 433 SW-1 259 NW-2 251 Prastara 1.5.1 578 578 NE-C 255 SE-C 424 SW-B 489 NW-E 255 NE-1 476 SE-2 433 SW-1 259 NW-2 251 2:1 578 578 NE-C 255 SE-C 424 SW-B 489 NW-E 255 NE-1 476 SE-2 433 SW-1 259 NW-2 251

Ratio 1:1 1.5:1 2:1

Dandaka

Sarvatobhadra

Nandyavarta

Swastika

Prastara

N Figure 3.13: Selected case streets from axial connectivity analysis

Table 3.4: Properties of Building Materials

Property Brick-Timber Frame External Paving

U-Value (Wm-2K) 1.770 3.418

Admittance (Wm-2K) 2.200 5.800

Solar Absorption (0-1) 0.495 0.642

Thermal Decrement (0-1) 0.77 0.02

Thermal Lag (hrs) 4 9

Thickness (mm) 195 1500

Padavinyasa or the folk-planning principles divide the plots or blocks largely based on the caste, religious and cosmological reasoning. Strict application of the principles of Padavinyasa and the building bye laws regarding allocation, distribution, setback, height, size and shape of the buildings are not observed in the case studies. The built forms in Jaipur are rather inconsistent in size and shape. The plots are irregular and setback spaces are not geometrically continuous. The façade of the blocks adjacent to the primary or secondary streets are continuous and has negligible amount of gaps between the built forms. As a result, the blocks do not form significant fissures which can create noticeable contribution to the porosity of the entire block, although the interior spaces have unbuilt areas and building with courtyards (figure 3.15). Therefore, the individual blocks have been considered to be solid, although, block porosity is an essential parameter for wind simulation.

Given the above scenario, the height of the solid blocks has been addressed within the settlement patterns. The resultant three-dimensional built environment of all the fifteen cases has different built to unbuilt ratio and average height to width ratio (for the sample streets). The following chart presents these building parameters for specific cases:

Table 3.5: Built-Environment Parameters for all the case diagrams

Length to Built to Average Height to Width Ratio Diagram width unbuilt Ratio Ratio BrV MhV RP Value VP Value 1:1 0.856 1.1 0.99 SE-A 1.75 SE-1 1.5 Dandaka 1.5.1 0.848 1.1 0.99 SE-A 1.75 SE-2 1.5 2:1 0.826 1.1 0.99 SE-A 1.75 SE-3 1.5 1:1 0.822 1.1 1.24 SE-B 2.625 SE-2 2.625 Sarvatobhadra 1.5.1 0.831 1.1 1.24 SE-B 2.625 SE-2 2.625 2:1 0.823 1.1 1.24 SE-B 2.625 SE-2 2.625 1:1 0.826 1.1 1.1 SE-B 3 SE-2 2.625 Nandyavarta 1.5.1 0.883 N/A N/A SE-C 1.875 SE-4 1.875 2:1 0.878 N/A N/A SE-C 1.875 SE-4 1.875 1:1 0.849 1.24 1.24 SE-A 1.825 SE-4 1.825 Swastika 1.5.1 0.847 1.24 1.24 SE-A 1.825 SE-4 1.825 2:1 0.841 1.24 1.24 SE-A 1.825 SE-4 1.825 1:1 0.798 1.24 1.24 SE-C 2.25 SE-2 2.625 Prastara 1.5.1 0.793 1.24 1.24 SE-C 2.25 SE-2 2.625 2:1 0.784 1.24 1.24 SE-C 2.25 SE-2 2.625

Figure 3.15: Randomly selected blocks in Jaipur having inconsistent porosity

Ratio 1:1 1.5:1 2:1

Dandaka

Sarvatobhadra

Nandyavarta

Swastika

Prastara

Figure 3.14: Three dimensional model of built environment

3.7 Insolation analysis

3.7.1 Formation of 3d model for computer simulation

In order to derive the insolation level of the outdoor spaces, the three dimensional model of the built environment of all the fifteen cases has been produced in Audodesk Ecotect using SI Decimal unit system. The basic information regarding the model has been shown in Table 3.6.

Table 3.6: Basic Information for Insolation Analysis Sl No. Parameter Specification

1 Location Dhaka, Bangladesh

2 Latitude 23. 50°E

3 Longitude 90.20°N

4 Time Zone + 6.00 GMT

5 Unit Unit of Dimension: SI Decimal (m)

Unit of Insolation: Wh/(m.2 .day)

6 Weather Data Dhaka (for parameters, refer to Table: 3.1)

The basic materials has been selected to be ‘Brick- Timber Frame’ as the building material and ‘External Paving’ for road surfaces as discussed earlier with relevant properties.

3.7.2 Time-basis and other parameters

For finding out the insolation levels, each of these fifteen models has been divided into analysis grid of equal size which is approximately 4m x 4m. Each of these grids shows the gradation of insolation level within themselves by means of color coding and contour lines. Three days from different time of the year have been considered for insolation analysis for deriving the changing level of radiation in different seasons. The time-basis and other parameters are shown in table 3.7.

Table 3.7: Time-basis and other parameters Sl No. Parameter Specification

1 Insolation Total (Direct and Diffused) solar radiation falling on surfaces

2 Specified Dates 04 April

21 June

22 December

3 Specified Time 08.00-18.00 hrs

4 Value The sum of all values in each metric and divided by the number of days (one for each of the three days in this case) over which the analysis was run to give average daily result

5 Analysis Grid Calculates values over visible points in the analysis grid which considers the spatial distribution over all three dimensions of the grid

Among the three dates, 21 June and 22 December has been selected as they are the Summer Solstice and Winter Solstice respectively for the northern hemisphere of the Earth. As a result, 21 June is the longest and 22 December is the shortest day of the year which implies that these dates have the maximum and minimum solar exposure in a year respectively, although the level of radiation will be largely governed by the sky condition. According to the weather data of Dhaka, April is the hottest month of the year in terms of air temperature and 04 April has the highest recorded solar radiation level within the month, which can provide us with the maximum threshold of radiation for this study. April, June and December also represents three different seasons: the hot-dry, the warm-humid and the cool-dry.

3.8 Insolation analysis results

The simulation result represents the daily average insolation (summation of direct and diffused radiation) within a unit area and expressed in Wh/(m.2 .day). For each of the settlement patterns the insolation result has been classified by the four type of streets. Each of these streets have three results for the selected days. A significant central portion of a case street which provides a relatively uniform result has been selected for data analysis. The selected area is then divided into equal segments of 0.5m span and the value of each segment has been taken in order to analyze the insolation scenario

97 within the transverse section of the street. The results have been plotted in a table and the represented by means of a line chart. Hence, for Brahmavithi and Rajapatha, the results in the table and the line chart from left to right represent the insolation value throughout the cross section of a street from north to south direction. Similarly, in case of Mahakalavithi and Vamanapatha the values in the table and the line chart from left to right represent the insolation value throughout the cross section of the street from west to east. The insolation levels throughout the transverse section of the streets also provides an average value, which represents the cumulative mean insolation level of that particular section of street for a given day. In this manner, the insolation analysis results are presented in Appendix B. For comparative analysis, the results of each type of streets are discussed as follows.

Figure 3.16: Insolation Analysis using Autodesk Ecotect

3.8.1 Brahmavithi (BrV)

As discussed in the previous chapter, the Brahmavithi (BrV) is the principal street which is elongated in the east-west direction. Except Nandyavarta (1.5:1) and Nandyavarta (2:1), all the settlement patterns has a Brahmavithi. The average cumulative value for a given area for BrV of all the settlement patterns for 4th April, 21st June and 22nd December are plotted in table 3.8.

Table 3.8: Average Cumulative Value of Insolation Level (Wh/(m2.day)) for BrV of all the settlement patterns.

Settlement Ratio 4th April 21st June 22nd December Pattern Dandaka 1:1 1963.3 2379.4 430.0 1.5:1 1963.3 2618.3 381.1 2:1 1991.7 2618.3 381.1 Sarvatobhadra 1:1 1991.7 2642.2 381.1 1.5:1 1991.7 2618.3 381.1 2:1 1991.7 2618.3 381.1 Nandyavarta 1:1 1963.3 2785.6 430.0 1.5:1 N/A N/A N/A 2:1 N/A N/A N/A Swastika 1:1 2048.3 2642.2 393.3 1.5:1 2048.3 2642.2 393.3 2:1 1963.3 2690.0 381.1 Prastara 1:1 1991.7 2570.6 393.3 1.5:1 1991.7 2642.2 381.1 2:1 1991.7 2642.2 381.1 Average 1991.7 2623.8 391.5 The accumulated data from table 3.7 is shown in the form of bar chart in figure 3.17. From the data it can be observed that the average cumulative insolation level (direct and diffused) for Brahmavithi of all the settlement patterns are almost similar for a given day. It is also noteworthy that the built environment parameter for this principle street is also similar for all the patterns. However, average insolation level for 21st June for all the BrV is 2623.8 Wh/(m2.day), which is highest among the three days due to longer solar exposure. The mean value for 4th April and 22nd December are 1991.7 Wh/(m2.day) and 391.5 Wh/(m2.day) respectively. Although, 4th April has the highest recorded incident radiation (W/m2) for a given time, the cumulative value is lower than 21st June due to lower hours of solar exposure. The insolation level for 22nd December is relatively low comparing to the other two days.

Prastara 2:1 Prastara 1.5:1 Prastara 1:1 Swastika 2:1 Swastika 1.5:1 Swastika 1:1 Nandyavarta 2:1 Nandyavarta 1.5:1 Nandyavarta 1:1 Sarvatobhadra 2:1 Sarvatobhadra 1.5:1 Sarvatobhadra 1:1 Dandaka 2:1 Dandaka 1.5:1 Dandaka 1:1 0 500 1000 1500 2000 2500 3000 3500

Insolation [Wh/(m2.day)]

a. Average insolation Level (Wh/(m2.day)) for BrV on 4th April

Insolation [Wh/(m2.day)]

b. Average insolation Level (Wh/(m2.day)) for BrV on 21st June

100

Insolation [Wh/(m2.day)]

c. Average insolation Level (Wh/(m2.day)) for BrV on 22nd December 3.17 Average Cumulative Value of Insolation Level (Wh/(m2.day)) for BrV of all the settlement patterns

The insolation value throughout the cross-section in transverse direction of the BrVs are presented in table 3.9 for all the three days. The data throughout the cross-section is necessary to observe the distribution of radiative heat. The data presented in table 3.8 are plotted in figure 3.18 in the form of line chart, which will represent the level of insolation within the span of the street from north to south direction within an interval of 0.5m.

101

Table 3.9(a): Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of BrV for 4th April

Distance (m)

1 2 3 4 5 6 7 8 9 ------Ratio Pattern 0.5 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 ------Settlement Settlement 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5

830 830 830 320 320 320 1:1 1850 2360 2360 2870 3380 3890 3380 3380 2870 2360 1850 1340

830 830 830 320 320 320 1850 2360 2360 2870 3380 3890 3380 3380 2870 2360 1850 1340 1.5:1 Dandaka

830 830 830 320 320 320 2:1 1850 2360 2870 3380 3890 3890 3380 2870 2360 2360 1850 1340

830 830 830 320 320 320 1:1

1850 2360 2870 3380 3890 3890 3380 2870 2360 2360 1850 1340

830 830 830 320 320 320 1850 2360 2870 3380 3890 3890 3380 2870 2360 2360 1850 1340 1.5:1

Sarvatobhadra 830 830 830 320 320 320 2:1 1850 2360 2870 3380 3890 3890 3380 2870 2360 2360 1850 1340

830 830 830 320 320 320 1:1 1850 2360 2360 2870 3380 3890 3380 3380 2870 2360 1850 1340

N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 1.5:1

Nandyavarta

2:1 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

830 830 830 320 320 320 1:1 1850 2360 2870 3380 3890 3890 3380 3380 2870 2360 1850 1340

830 830 830 320 320 320 1850 2360 2870 3380 3890 3890 3380 3380 2870 2360 1850 1340 1.5:1 Swastika

830 830 830 320 320 320 2:1 1340 1850 2360 2870 3380 3890 3890 3380 2870 2360 1850 1850

830 830 830 320 320 320 1:1 1850 2360 2870 3380 3890 3890 3380 2870 2360 2360 1850 1340

830 830 830 320 320 320 1850 2360 2870 3380 3890 3890 3380 2870 2360 2360 1850 1340 1.5:1 Prastara

830 830 830 320 320 320 2:1 1850 2360 2870 3380 3890 3890 3380 2870 2360 2360 1850 1340

102

Table 3.9(b): Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of BrV for 21st June

Distance (m)

1 2 3 4 5 6 7 8 9 Ratio ------Pattern 0.5 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 ------Settlement Settlement 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5

1:1 2260 2260 2260 2260 2260 2260 2260 2690 2690 2690 2690 2690 2260 2260 2260 2260 2260 2260

1400 1830 2260 2690 2690 3120 3120 3120 3120 3120 3120 3120 3120 3120 2690 2260 1830 1400 1.5:1 Dandaka

2:1 1400 1830 2260 2690 3120 3120 3120 3120 3120 3120 3120 3120 3120 2690 2690 2260 1830 1400

1:1 1400 1830 2260 2690 3120 3120 3120 3120 3120 3120 3120 3120 3120 3120 2690 2260 1830 1400

1400 1830 2260 2690 3120 3120 3120 3120 3120 3120 3120 3120 3120 2690 2690 2260 1830 1400 1.5:1

Sarvatobhadra 2:1 1400 1830 2260 2690 3120 3120 3120 3120 3120 3120 3120 3120 3120 2690 2690 2260 1830 1400

1:1 1830 2260 2260 2260 2690 2690 2690 3120 3120 3120 3120 3120 3120 3120 3120 3120 2690 2690

1.5:1 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

Nandyavarta

2:1 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

1:1 1400 1830 2260 2690 3120 3120 3120 3120 3120 3120 3120 3120 3120 3120 2690 2260 1830 1400

1400 1830 2260 2690 3120 3120 3120 3120 3120 3120 3120 3120 3120 3120 2690 2260 1830 1400 1.5:1 Swastika

1400 1830 2260 2690 3120 3120 3120 3120 3120 3120 3120 3120 3120 3120 2690 2260 2260 1830 2:1

970 1:1 1400 1400 1830 2260 2690 3120 3120 3120 3120 3120 3120 3120 3120 3120 2690 2690 2260

1400 1830 2260 2690 3120 3120 3120 3120 3120 3120 3120 3120 3120 3120 2690 2260 1830 1400 1.5:1 Prastara

2:1 1400 1830 2260 2690 3120 3120 3120 3120 3120 3120 3120 3120 3120 3120 2690 2260 1830 1400

103

Table 3.9(c): Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of BrV for 22nd December

Distance (m)

1 2 3 4 5 6 7 8 9 Ratio ------Pattern 0.5 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 Settlement Settlement ------0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5

430 430 430 430 430 430 430 430 430 430 430 430 430 430 430 430 430 430 1:1

210 210 430 430 430 430 430 430 430 430 430 430 430 430 430 430 210 210 1.5:1 Dandaka

2:1 210 210 430 430 430 430 430 430 430 430 430 430 430 430 430 430 210 210

210 210 430 430 430 430 430 430 430 430 430 430 430 430 430 430 210 210

1:1

210 210 430 430 430 430 430 430 430 430 430 430 430 430 430 430 210 210 1.5:1

Sarvatobhadra 210 210 430 430 430 430 430 430 430 430 430 430 430 430 430 430 210 210 2:1

430 430 430 430 430 430 430 430 430 430 430 430 430 430 430 430 430 430 1:1

1.5:1 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

Nandyavarta

2:1 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

210 430 430 430 430 430 430 430 430 430 430 430 430 430 430 430 210 210 1:1

210 430 430 430 430 430 430 430 430 430 430 430 430 430 430 430 210 210 1.5:1 Swastika

210 210 430 430 430 430 430 430 430 430 430 430 430 430 430 430 210 210 2:1

210 210 210 430 430 430 430 430 430 430 430 430 430 430 430 430 430 430 1:1

210 210 430 430 430 430 430 430 430 430 430 430 430 430 430 430 210 210 1.5:1 Prastara

210 210 430 430 430 430 430 430 430 430 430 430 430 430 430 430 210 210 2:1

104

4000

3500

3000

2500

2000

1500

] 1000 .day) 2

500 Wh/(m 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9

Insolation [ Dandaka 1:1 Dandaka 1.5:1 Dandaka 2:1 Sarvatobhadra 1:1

Sarvatobhadra 1.5:1 Sarvatobhadra 2:1 Nandyavarta 1:1 Nandyavarta 1.5:1

Nandyavarta 2:1 Swastika 1:1 Swastika 1.5:1 Swastika 2:1

Prastara 1:1 Prastara 1.5:1 Prastara 2:1

a. Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of BrV for 4th April

3500

3000

] 2500 .day) 2 2000 Wh/(m

1500

Insolation [ 1000

500

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9

Dandaka 1:1 Dandaka 1.5:1 Dandaka 2:1 Sarvatobhadra 1:1

Sarvatobhadra 1.5:1 Sarvatobhadra 2:1 Nandyavarta 1:1 Nandyavarta 1.5:1

Nandyavarta 2:1 Swastika 1:1 Swastika 1.5:1 Swastika 2:1

Prastara 1:1 Prastara 1.5:1 Prastara 2:1

b. Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of BrV for 21st June

105

3500

3000

] 2500 .day) 2 2000 Wh/(m 1500

1000 Insolation [

500

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9

Dandaka 1:1 Dandaka 1.5:1 Dandaka 2:1 Sarvatobhadra 1:1

Sarvatobhadra 1.5:1 Sarvatobhadra 2:1 Nandyavarta 1:1 Nandyavarta 1.5:1

Nandyavarta 2:1 Swastika 1:1 Swastika 1.5:1 Swastika 2:1

Prastara 1:1 Prastara 1.5:1 Prastara 2:1

c. Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of BrV for 22nd December

3.18: Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of BrV for all the settlement patterns

From the data shown in chart 3.9 and figure 3.18, it is evident that the difference in insolation level is quite diverse throughout the transverse section of BrV in 4th April, while it is rather uniform in 21st June. In 4th April, the southern part of the BrV receives relatively lower insolation while the area from center to the north receives most of the heat. The maximum and minimum value of insolation for 4th April are 3890 Wh/(m2.day) and 320 Wh/(m2.day) respectively, which has a difference of 3570 Wh/(m2.day). Data for 21st June shows peak insolation level in the central area and the distribution is symmetric. 21st June has a maximum and minimum value of 3120 Wh/(m2.day)and 970 Wh/(m2.day) with a difference of 2150 Wh/(m2.day). Insolation level in 22nd December varies between 430 Wh/(m2.day) to 210 Wh/(m2.day), which is significantly low comparing to the other days and the distribution in this case is also symmetric.

106

3.8.2 Mahakalavithi (MhV)

Mahakalavithi (MhV), the principal street elongated in the north-south direction is also absent in Nandyavarta (1.5:1) and Nandyavarta (2:1). The average cumulative value for a given area for MhV of all the settlement patterns for 4th April, 21st June and 22nd December are plotted in table 3.10.

Table 3.10: Average Cumulative Value of Insolation Level (Wh/(m2.day)) for MhV of all the settlement patterns.

Settlement 4th 21st Ratio 22nd December Pattern April June

Dandaka 1:1 2246.7 2379.4 882.2 1.5:1 2218.3 2283.9 980.0 2:1 2218.3 2283.9 1004.4 Sarvatobhadra 1:1 1566.7 1901.7 735.6 1.5:1 2246.7 2116.7 894.4 2:1 1651.7 1925.6 723.3 Nandyavarta 1:1 1878.3 1901.7 747.8 1.5:1 2:1 Swastika 1:1 2303.3 2188.3 967.8 1.5:1 1906.7 2236.1 760.0 2:1 2105.6 2068.9 735.6 Prastara 1:1 2246.7 1877.8 723.3 1.5:1 1651.7 1925.6 735.6 2:1 2246.7 2212.2 943.3 Average 2037.5 2100.1 833.3

The accumulated data from table 3.10 is shown in the form of bar chart in figure 3.19. From the data it can be observed that the average cumulative insolation level (direct and diffused) for Mahakalavithi (MhV) of all the settlement patterns are varies within a close range. The built environment parameter for this principle street is also similar for all the patterns. As opposed to the previous case, the average cumulative insolation level for 4th April and 21st June are almost equal, which are 2037.5 Wh/(m2.day) and 2100.1 Wh/(m2.day) respectively. The average insolation level for 22nd December is 833.3 Wh/(m2.day), which is higher than the insolation level of BrV by more than two times.

107

Insolation [Wh/(m2.day)]

a. Average insolation Level (Wh/(m2.day)) for MhV on 4th April

Insolation [Wh/(m2.day)]

b. Average insolation Level (Wh/(m2.day)) for MhV on 21st June

108

Insolation [Wh/(m2.day)] c. Average insolation Level (Wh/(m2.day)) for MhV on 22nd December

3.19 Average Cumulative Value of Insolation Level (Wh/(m2.day)) for MhV of all the settlement patterns

The insolation value throughout the cross-section in transverse direction of the MhVs are presented in table 3.11 for all the three days. The data presented in table 3.11 are plotted in figure 3.20 in the form of line chart, which will represent the level of insolation within the span of the street from west to east direction within an interval of 0.5m.

109

Table 3.11(a): Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of MhV for 4th April

Distance (m)

1 2 3 4 5 6 7 8 9 ------Ratio 0.5 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 ------Settlement Settlement Pattern 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5

830 830 1:1 1340 1850 1850 2360 2360 2360 2870 2870 2870 2870 2870 2870 2870 2360 1850 1850

830 830 1340 1850 1850 2360 2360 2360 2870 2870 2870 2870 2870 2870 2870 2360 1850 1850 1.5:1 Dandaka

830 830 2:1 1340 1850 1850 2360 2360 2360 2870 2870 2870 2870 2870 2870 2870 2360 1850 1850

830 830 830

1:1 1340 1340 1850 1850 1850 1850 1850 1850 1850 1850 1850 1850 1850 1340 1340

2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 1850 1850 1850 1850 1.5:1

Sarvatobhadra 830 830 830 320 320 320 2:1 1850 2360 2870 3380 3890 3890 3380 2870 2360 2360 1850 1340

830 830 1:1 1340 1340 1850 2360 2360 2360 2360 2360 2360 2360 2360 2360 1850 1850 1340 1340

1.5:1 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

Nandyavarta

2:1 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

1:1 1850 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 1850

830 830 1340 1850 1850 2360 2360 2360 2360 2360 2360 2360 2360 2360 1850 1850 1340 1340 1.5:1 Swastika

830 830 2:1 1350 1850 2360 2360 2360 2360 2360 2360 2870 2870 2870 2870 2360 1850 1850 1340

1:1 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 1850 1850 1850 1850

830 830 320 1340 1850 1850 2360 2360 2360 2360 1850 1850 1850 1850 1850 1340 1340 1340 1.5:1 Prastara

2:1 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 2360 1850 1850 1850 1850

110

Table 3.11(b): Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of MhV for 21st June

Distance (m)

1 2 3 4 5 6 7 8 9 ------Ratio 0.5 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 Pattern ------Settlement Settlement 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5

1:1 2260 2260 2260 2260 2260 2260 2260 2690 2690 2690 2690 2690 2260 2260 2260 2260 2260 2260

970 1830 1830 2260 2260 2690 2690 2690 2690 2690 2690 2690 2690 2690 2260 2260 1830 1400 1.5:1 Dandaka

970 2:1 1830 1830 2260 2690 2690 2690 2690 2690 2690 2690 2690 2690 2690 2260 1830 1830 1400

970 970 1:1

1400 1830 1830 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 1830 1400 1400

1830 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 1830 1830 1830 1830 1830 1.5:1

Sarvatobhadra

970 970 2:1 1400 1830 1830 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 1830 1830 1400

970 970 1:1 1400 1400 1830 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 1830 1830 1400

1.5:1 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

Nandyavarta

2:1 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

1830 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 1830 1830 1:1

970 1400 1830 2260 2260 2690 2690 2690 2690 2690 2690 2690 2690 2690 2260 1830 1830 1400 1.5:1 Swastika

970 970 1400 1830 2260 2260 2260 2260 2260 2690 2690 2690 2690 2690 2260 1830 1830 1400 2:1

970 970 540 1:1 1830 1830 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 1830 1830 1400

970 1400 1400 1830 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 1830 1830 1400 1400 1.5:1 Prastara

2:1 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 2260 1830 1830

111

Table 3.11(c): Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of MhV for 22nd December

Distance (m)

Ratio 1 2 3 4 5 6 7 8 9 Pattern ------0.5 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 Settlement Settlement ------0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5

650 650 870 870 870 870 870 870 870 870 870 650 650 1:1 1090 1090 1090 1090 1090

650 870 870 870 870 650 650 430 1090 1310 1310 1310 1310 1090 1090 1090 1090 1090 1.5:1 Dandaka

650 870 870 650 650 430 2:1 1090 1090 1310 1310 1310 1310 1090 1090 1090 1090 1090 1090

430 650 650 870 870 870 870 870 870 870 870 870 870 650 650 650 430 430

1:1

650 650 870 870 870 870 870 870 870 870 870 870 650 1090 1090 1090 1090 1090 1.5:1

Sarvatobhadra 650 650 870 870 870 870 870 870 870 870 870 870 650 650 650 430 430 210 2:1

430 430 650 650 870 870 870 870 870 870 870 870 870 870 870 650 650 430 1:1

1.5:1 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

Nandyavarta

2:1 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

650 650 870 870 870 870 870 870 1:1 1090 1090 1090 1090 1090 1090 1090 1090 1090 1090

650 650 870 870 870 870 870 870 870 870 870 870 870 650 650 650 430 430 1.5:1 Swastika

650 870 870 870 870 870 870 870 870 870 870 870 650 650 650 430 430 210 2:1

650 870 870 870 870 870 870 870 870 870 870 870 650 650 430 430 430 210 1:1

650 650 870 870 870 870 870 870 870 870 870 870 870 650 650 430 430 210 1.5:1 Prastara

870 870 870 870 870 870 870 870 870 870 650 2:1 1090 1090 1090 1090 1090 1090 1090

112

4000

3500

3000

] 2500 .day) 2 2000 Wh/(m

1500

Insolation [ 1000

500

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9

Dandaka 1:1 Dandaka 1.5:1 Dandaka 2:1 Sarvatobhadra 1:1

Sarvatobhadra 1.5:1 Sarvatobhadra 2:1 Nandyavarta 1:1 Nandyavarta 1.5:1

Nandyavarta 2:1 Swastika 1:1 Swastika 1.5:1 Swastika 2:1

Prastara 1:1 Prastara 1.5:1 Prastara 2:1

a. Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of MhV for 4th April

3500

3000

] 2500 .day) 2

2000 Wh/(m

1500 Insolation [ 1000

500

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9

Dandaka 1:1 Dandaka 1.5:1 Dandaka 2:1 Sarvatobhadra 1:1

Sarvatobhadra 1.5:1 Sarvatobhadra 2:1 Nandyavarta 1:1 Nandyavarta 1.5:1

Nandyavarta 2:1 Swastika 1:1 Swastika 1.5:1 Swastika 2:1

Prastara 1:1 Prastara 1.5:1 Prastara 2:1

b. Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of MhV for 21st June

113

3500

3000

] 2500 .day) 2 2000 Wh/(m 1500

1000 Insolation [

500

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9

Dandaka 1:1 Dandaka 1.5:1 Dandaka 2:1 Sarvatobhadra 1:1

Sarvatobhadra 1.5:1 Sarvatobhadra 2:1 Nandyavarta 1:1 Nandyavarta 1.5:1

Nandyavarta 2:1 Swastika 1:1 Swastika 1.5:1 Swastika 2:1

Prastara 1:1 Prastara 1.5:1 Prastara 2:1

c. Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of MhV for 22nd December

3.20: Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of MhV for all the settlement patterns

From the data shown in chart 3.11 and figure 3.20, it is evident that the difference in insolation level is diverse but symmetric in case of 4th April. 3890 Wh/(m2.day) and 320 Wh/(m2.day) being the highest and lowest value of insolation, the difference is almost 3570 Wh/(m2.day). The central part of the street receives the highest insolation; while the eastern part of the street receives relatively lower insolation. For 21st June, the difference between maximum (2690 Wh/(m2.day)) and minimum value (540 Wh/(m2.day)) is 2150 Wh/(m2.day), which is relatively lower. The insolation level is more evenly distributed again with the eastern part of the road being the one with relatively less radiative heat. The range of insolation varies between 1310 Wh/(m2.day) and 210 Wh/(m2.day) in case of 22nd December. Insolation level is also evenly distributed in this case.

114

3.8.3 Rajapatha (RP)

Rajapatha (RP), the secondary street elongated in the east-west direction which has been determined earlier in this chapter in terms of connectivity values, varies for each settlement pattern. As opposed to the previous case of BrV and MhV, the built environment parameter thus varies for each case. The average cumulative value for a given area for RP of all the settlement patterns for 4th April, 21st June and 22nd December are plotted in table 3.12. The corresponding street code is also mentioned in the table.

Table 3.12: Average Cumulative Value of Insolation Level (Wh/(m2.day)) for RP of all the settlement patterns.

Settlement 4th 21st 22nd Pattern Ratio Street April June December Dandaka 1:1 SE-A 2317.5 1865.8 301.7 1.5:1 SE-A 2317.5 1865.8 301.7 2:1 SE-A 2657.5 2618.3 393.3 Sarvatobhadra 1:1 SE-B 2232.5 1668.8 210.0 1.5:1 SE-B 2232.5 1883.8 210.0 2:1 SE-B 2232.5 1131.3 210.0 Nandyavarta 1:1 SE-B 2232.5 2098.8 210.0 1.5:1 SE-C 2551.3 2206.3 320.0 2:1 SE-C 2551.3 1937.5 320.0 Swastika 1:1 SE-A 2041.3 1991.3 292.5 1.5:1 SE-A 2168.8 1185.0 292.5 2:1 SE-A 2041.3 916.3 265.0 Prastara 1:1 SE-C 2423.8 1185.0 210.0 1.5:1 SE-C 2423.8 1722.5 237.5 2:1 SE-C 2423.8 2206.3 237.5 Average 2323.2 1765.5 267.4 The accumulated data from table 3.12 is shown in the form of bar chart in figure 3.21. From the data it can be observed that the average cumulative insolation level (direct and diffused) for Rajapatha (RP) of all the settlement patterns are varies drastically for each case as the height to width ratio is very different for each street. The average cumulative value for 4th April is 2323.2 Wh/(m2.day), which is higher than the value of 21st June, which is 1765.5 Wh/(m2.day). The average insolation level for 22nd December is 267.4 Wh/(m2.day).

115

Insolation [Wh/(m2.day)]

a. Average insolation Level (Wh/(m2.day)) for RP on 4th April

Insolation [Wh/(m2.day)]

b. Average insolation Level (Wh/(m2.day)) for RP on 21st June

116

Insolation [Wh/(m2.day)]

c. Average insolation Level (Wh/(m2.day)) for RP on 22nd December

3.21 Average Cumulative Value of Insolation Level (Wh/(m2.day)) for RP of all the settlement patterns

The insolation value throughout the cross-section in transverse direction of the RPs are presented in table 3.13 for all the three days. The data presented in table 3.13 are plotted in figure 3.22 in the form of line chart, which will represent the level of insolation within the span of the street from north to south direction within an interval of 0.5m.

117

Table 3.13(a): Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of RP for 4th April

Distance (m)

Ratio Street Pattern

1 2 3 4 5 6 Settlement Settlement ------0.5 1.5 2.5 3.5 4.5 5.5 ------0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5

A - 830 830 1:1 1850 2360 2870 3380 3890 3380 2870 2360 1850 1340 SE

A - 830 830 1850 2360 2870 3380 3890 3380 2870 2360 1850 1340 1.5:1 SE Dandaka

A - 2:1 1850 2360 2870 3380 3890 3890 3380 2870 2360 1850 1850 1340 SE

B - 830 1:1 3380 3380 2870 2360 1850 1850 1340

B - 830 3380 3380 2870 2360 1850 1850 1340

1.5:1 SE

Sarvatobhadra

B - 830 2:1 3380 3380 2870 2360 1850 1850 1340

B - 830 1:1 3380 3380 2870 2360 1850 1850 1340

C - 3380 3890 3380 2870 2360 1850 1340 1340

1.5:1 SE

Nandyavarta

C - 2:1 3380 3890 3380 2870 2360 1850 1340 1340

A - 830 320 1:1 3380 3380 2870 2360 1850 1340

A - 830 830 3890 3380 2870 2360 1850 1340

1.5:1 SE

Swastika

A - 830 320 2:1 3380 3380 2870 2360 1850 1340

C - 1:1 2870 3380 3380 2870 2360 1850 1340 1340

C - 830 3380 3380 3380 2870 2360 1850 1340

1.5:1 SE

Prastara

C - 2:1 2870 3380 3380 2870 2360 1850 1340 1340

118

Table 3.13(b): Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of RP for 21st June

Distance (m)

Ratio Street

1 2 3 4 5 6 ------0.5 1.5 2.5 3.5 4.5 5.5 ------Settlement Settlement Pattern 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5

- 540 970 1400 1400 1830 2260 2690 2690 2690 2260 1830 1830 1:1 SE

A - 970 540 1400 1830 2260 2690 2690 2690 2260 1830 1830 1400 1.5:1 SE

- 830 1 2260 2690 2690 3120 2690 2690 2690 2690 2690 2690 2690 Dandaka 2:1 SE

- 540 970 1400 1400 1830 2260 2690 2260

1:1 SE

B ra - 970 1400 1400 1830 2260 2690 2260 2260

1.5:1 SE

- 830 970 970 540 540 1 1400 1400 1400

Sarvatobhad 2:1 SE

- 1830 2260 2260 3120 2260 1830 1830 1400

1:1 SE

- 1400 1830 2260 2260 2690 2690 2260 2260

1.5:1 SE

- 260 970 2 2690 2690 2260 1830 1400 1400

Nandyavarta 2:1 SE

- 970 1 1400 1830 1830 2260 2690 2690 2260

1: SE

A - 970 970 540 540 1830 1830 1400 1400

1.5:1 SE

- 400 970 970 970 540 540 540 1 1400

Swastika 2:1 SE

- 970 970 540 540 1 1830 1830 1400 1400

1: SE

C - 970 970 2260 2260 2260 1830 1830 1400

1.5:1 SE

- 400 1 1400 1830 2260 3120 3120 2260 2260

Prastara 2:1 SE

119

Table 3.13(c): Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of RP for 22nd December

Distance (m)

1 2 3 4 5 6 ------Ratio Street 0.5 1.5 2.5 3.5 4.5 5.5 ------Settlement Settlement Pattern 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5

- 210 210 210 210 210 430 430 430 430 430 210 210 1:1 SE

A - 210 210 430 430 430 430 430 210 210 210 210 210 1.5:1 SE

A 10

- 2 210 430 430 430 430 430 430 430 430 430 430 Dandaka 2:1 SE

- 210 210 210 210 210 210 210 210

1:1 SE

B ra - 210 210 210 210 210 210 210 210

1.5:1 SE

B 10

- 2 210 210 210 210 210 210 210

Sarvatobhad 2:1 SE

- 210 210 210 210 210 210 210 210

1:1 SE

- 210 210 210 430 430 430 430 210

1.5:1 SE

C 30

- 4 430 430 430 210 210 210 210

Nandyavarta 2:1 SE

- 210 210 210 210 210 430 430 430 1

1: SE

A - 430 430 430 210 210 210 210 210

1.5:1 SE

A 30

- 4 430 210 210 210 210 210 210

Swastika 2:1 SE

- 210 210 210 210 210 210 210 210 1

1: SE

C - 210 430 210 210 210 210 210 210

1.5:1 SE

C 10

- 2 210 210 210 210 430 210 210

Prastara 2:1 SE

120

4000

3500

] 3000 .day) 2 2500

2000 Wh/(m 1500 ation [ ation 1000 Insol 500

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6

Dandaka 1:1 Dandaka 1.5:1 Dandaka 2:1 Sarvatobhadra 1:1 Sarvatobhadra 1.5:1 Sarvatobhadra 2:1 Nandyavarta 1:1 Nandyavarta 1.5:1 Nandyavarta 2:1 Swastika 1:1 Swastika 1.5:1 Swastika 2:1 Prastara 1:1 Prastara 1.5:1 Prastara 2:1

a. Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of RP for 4th April

3500

3000

]

.day) 2500 2

2000 Wh/(m

1500

Insolation [ 1000

500

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6

Dandaka 1:1 Dandaka 1.5:1 Dandaka 2:1 Sarvatobhadra 1:1 Sarvatobhadra 1:1 Sarvatobhadra 2:1 Nandyavarta 1:1 Nandyavarta 1.5:1 Nandyavarta 2:1 Swastika 1:1 Swastika 1.5:1 Swastika 2:1 Prastara 1:1 Prastara 1.5:1 Prastara 2:1

b. Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of RP for 21st June

121

3500

3000

] 2500 .day) 2

2000 Wh/(m

1500

Insolation [ 1000

500

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6

c. Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of RP for 22nd December

3.22: Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of RP for all the settlement patterns

The Rajapathas (RP) for all the diagrams have a width of 4m except for Dandaka; which has a street width of 9m for the RPS. From the data shown in chart 3.13 and figure 3.22, it can be observed that in case of 4th April, the difference between the maximum (3890 Wh/(m2.day)) and minimum (320 Wh/(m2.day)) value of insolation level is 3570 Wh/(m2.day). The north-central portion of the street has the highest insolation level while the southern part receives relatively low insolation level. With a maximum value of 2690 Wh/(m2.day) and minimum value of 540 Wh/(m2.day), the difference of insolation level is 2150 Wh/(m2.day) in case of 21st June and the radiation is symmetrically distributed. The range of insolation varies between 430 Wh/(m2.day) and 210 Wh/(m2.day) in case of 22nd December. Insolation level is also evenly distributed in this case.

122

3.8.4 Vamanapatha (VP)

Vamanapatha (VP), the secondary street elongated in the north-south direction which has been identified earlier in this chapter in terms of connectivity values, also varies for each settlement pattern and the built environment parameter thus varies for each case. The average cumulative value for a given area for VP of all the settlement patterns for 4th April, 21st June and 22nd December are plotted in table 3.14. The corresponding street code is also mentioned in the table.

Table 3.14: Average Cumulative Value of Insolation Level (Wh/(m2.day)) for VP of all the settlement patterns.

Settlement 4th 21st Pattern Ratio Street April June 22nd December Dandaka 1:1 SE-1 1552.5 1758.3 686.7 1.5:1 SE-2 1850.0 1973.3 943.3 2:1 SE-3 1935.0 2152.5 925.0 Sarvatobhadra 1:1 SE-2 893.8 970.0 320.0 1.5:1 SE-2 1148.8 1185.0 375.0 2:1 SE-2 957.5 1023.8 402.5 Nandyavarta 1:1 SE-2 766.3 701.3 292.5 1.5:1 SE-4 1212.5 1561.3 622.5 2:1 SE-4 1276.3 1507.5 485.0 Swastika 1:1 SE-4 1021.3 1131.3 402.5 1.5:1 SE-4 1276.3 1400.0 677.5 2:1 SE-4 1212.5 1185.0 402.5 Prastara 1:1 SE-2 702.5 1023.8 402.5 1.5:1 SE-2 766.3 916.3 402.5 2:1 SE-2 957.5 970.0 402.5 Average 1168.6 1297.3 516.2

The accumulated data from table 3.14 is shown in the form of bar chart in figure 3.23. From the data it can be observed that the average cumulative insolation level (direct and diffused) for Vamanpatha (RP) of all the settlement patterns are varies drastically for each case as the height to width ratio is very different for each street. The average cumulative value for 4th April is 1168.6 Wh/(m2.day), which is similar to the value of 21st June which is 1297.3 Wh/(m2.day). The average insolation level for 22nd December is 516.2 Wh/(m2.day).

123

Insolation [Wh/(m2.day)]

a. Average insolation Level (Wh/(m2.day)) for VP on 4th April

Insolation [Wh/(m2.day)]

b. Average insolation Level (Wh/(m2.day)) for VP on 21st June

124

Insolation [Wh/(m2.day)]

c. Average insolation Level (Wh/(m2.day)) for VP on 22nd December

3.23 Average Cumulative Value of Insolation Level (Wh/(m2.day)) for VP of all the settlement patterns

The insolation value throughout the cross-section in transverse direction of the VPs are presented in table 3.15 for all the three days. The data presented in table 3.15 are plotted in figure 3.24 in the form of line chart, which will represent the level of insolation within the span of the street from west to east direction within an interval of 0.5m.

125

Table 3.15(a): Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of VP for 4th April

Distance (m)

Ratio Street Pattern

1 2 3 4 5 6 Settlement Settlement ------0.5 1.5 2.5 3.5 4.5 5.5 ------0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5

1 - 830 320 1:1 1340 1340 1850 1850 2360 2360 1850 1850 1340 1340 SE

2 - 830 1850 2360 2360 2360 2360 1850 1850 1850 1850 1340 1340 SE 1.5:1 Dandaka

3 - 2:1 1850 2360 2360 2360 2360 1850 1850 1850 1850 1850 1340 1340 SE

2 - 320 320 830 830 830 1:1 1340 1340 1340

2 - 830 3380 3380 2870 2360 1850 1850 1340 SE 1.5:1

Sarvatobhadra

2 - 830 830 320 320 2:1 1340 1340 1340 1340

2 - 320 320 320 830 830 830 1:1 1340 1340

4 - 830 830 320 1340 1850 1850 1340 1340

SE 1.5:1

Nandyavarta

4 - 830 830 2:1 1340 1340 1340 1850 1340 1340 SE

4 - 320 830 830 830 1:1 1340 1340 1340 1340

4 - 830 830 1340 1340 1850 1340 1340 1340

SE 1.5:1

Swastika

4 - 830 830 320 320 2:1 2360 1850 1850 1340 SE

2 - 320 320 830 830 830 830 830 830 1:1

2 - 320 830 830 830 830 830 830 830

SE 1.5:1

Prastara

2 - 830 830 320 320 2:1 1340 1340 1340 1340 SE

126

Table 3.15(b): Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of VP for 21st June

Distance (m)

Ratio Street Pattern

1 2 3 4 5 6 Settlement Settlement ------0.5 1.5 2.5 3.5 4.5 5.5 ------0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5

1 - 970 540 1:1 1400 1830 2260 2260 2690 2260 2260 1830 1400 1400 SE

2 - 2260 2260 2260 2260 2260 2260 1830 1830 1830 1830 1400 1400 SE 1.5:1 Dandaka

3 - 2:1 1830 2260 2260 2260 2260 2260 2260 2260 2260 2260 1830 1830 SE

2 - 540 540 970 970 970 970 1:1 1400 1400

2 - 970 970 540 1400 1400 1400 1400 1400 SE 1.5:1

Sarvatobhadra

2 - 970 970 970 540 540 2:1 1400 1400 1400

2 - 540 540 540 540 540 970 970 970 1:1

4 - 970 970 1830 2260 1830 1830 1400 1400 SE 1.5:1

Nandyavarta

4 - 970 2:1 1400 1400 1830 1830 1830 1400 1400

4 - 540 970 970 970 1:1 1400 1400 1400 1400

4 - 970 970 1400 1400 1830 1830 1400 1400 SE 1.5:1

Swastika

4 - 970 970 540 540 2:1 1830 1830 1400 1400

2 - 970 970 970 540 540 1:1 1400 1400 1400

2 - 540 970 970 970 970 970 970 970 SE 1.5:1

Prastara

2 - 970 970 970 970 970 970 970 970 2:1

127

Table 3.15(c): Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of VP for 22nd December

Distance (m)

Ratio Street

1 2 3 4 5 6 ------0.5 1.5 2.5 3.5 4.5 5.5 ------Settlement Settlement Pattern 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5

- 430 650 870 870 870 870 650 650 650 430 210 1090 1:1 SE

2 - 870 870 870 870 650 650 1090 1090 1090 1090 1090 1090 1.5:1 SE

- 870 870 870 870 870 650 650 1090 1090 1090 1090 1090 Dandaka 2:1 SE

- 210 210 210 210 430 430 430 430

1:1 SE

2 - 430 430 430 430 430 430 210 210

1.5:1 SE

- 650 650 430 430 430 210 210 210

Sarvatobhadra 2:1 SE

- 210 210 210 210 210 430 430 430

1:1 SE

- 870 870 870 650 650 430 430 210

1.5:1 SE

- 430 430 430 650 650 430 430 430

Nandyavarta 2:1 SE

- 210 210 430 430 430 430 650 430

1:1 SE

4 - 650 650 650 870 870 650 650 430

1.5:1 SE

- 650 650 430 430 430 210 210 210

Swastika 2:1 SE

- 650 650 430 430 430 210 210 210

1:1 SE

2 - 210 430 430 430 430 430 430 430

1.5:1 SE

- 430 430 430 430 430 430 430 210

Prastara 2:1 SE

128

4000

3500

] 3000 .day) 2 2500 Wh/(m 2000

1500 Insolation [ 1000

500

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6

Dandaka 1:1 Dandaka 1.5:1 Dandaka 2:1 Sarvatobhadra 1:1

Sarvatobhadra 1.5:1 Sarvatobhadra 2:1 Nandyavarta 1:1 Nandyavarta 1.5:1

Nandyavarta 2:1 Swastika 1:1 Swastika 1.5:1 Swastika 2:1

Prastara 1:1 Prastara 1.5:1 Prastara 2:1

a. Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of VP for 4th April

3500

3000

]

.day) 2500 2

2000 Wh/(m

1500 Insolation [ 1000

500

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6

Dandaka 1:1 Dandaka 1.5:1 Dandaka 2:1 Sarvatobhadra 1:1

Sarvatobhadra 1.5:1 Sarvatobhadra 2:1 Nandyavarta 1:1 Nandyavarta 1.5:1

Nandyavarta 2:1 Swastika 1:1 Swastika 1.5:1 Swastika 2:1

Prastara 1:1 Prastara 1.5:1 Prastara 2:1

b. Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of VP for 21st June

129

3500

3000

]

.day) 2500 2

Wh/(m 2000

1500 Insolation [ 1000

500

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6

Dandaka 1:1 Dandaka 1.5:1 Dandaka 2:1 Sarvatobhadra 1:1

Sarvatobhadra 1.5:1 Sarvatobhadra 2:1 Nandyavarta 1:1 Nandyavarta 1.5:1

Nandyavarta 2:1 Swastika 1:1 Swastika 1.5:1 Swastika 2:1

Prastara 1:1 Prastara 1.5:1 Prastara 2:1

c. Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of VP for 22nd December

3.24: Average Daily Insolation (Wh/(m.2 .day)) within the transverse section of VP for all the settlement patterns

Like the Rajapathas (RPs) the Vamanpathas (VP) for all the diagrams also have a width of 4m except for Dandaka; which has a street width of 9m for the VPs. From the data shown in chart 3.15 and figure 3.24, it can be observed that in case of 4th April, the difference between the maximum (3380 Wh/(m2.day)) and minimum (320 Wh/(m2.day)) value of insolation level is 3060 Wh/(m2.day). The north-central portion of the street has the highest insolation level while the eastern part receives relatively low insolation level. With a maximum value of 2690 Wh/(m2.day) and minimum value of 540 Wh/(m2.day), the difference of insolation level is 2150 Wh/(m2.day) in case of 21st June and the radiation is symmetrically distributed. The range of insolation varies between 1090 Wh/(m2.day) and 210 Wh/(m2.day) in case of 22nd December. Insolation level is also evenly distributed in this case.

130

3.8.5 Key observations from insolation analysis

For all four kinds of streets, the BrV. MhV, RP and VP; the insolation analysis results for the 4th April shows the most difference between the maximum and minimum value. In most cases, the difference is more than 3000 Wh/(m2.day). The insolation level throughout the transverse section of the street varies drastically.

In case of east-west oriented streets, the BrVs and RPs, the southern portion of the street receives the lowest insolation, while the north central portion receives the highest radiation. North-south oriented streets like the MhVs and VPs have relatively symmetric and uniform insolation level; even so, it can be marked that the eastern part of the street receives relatively low insolation, although not as much noticeable than the southern part of the east-west oriented streets.

Between BrVs and MhVs, the two principle streets with only difference in orientation, the cumulative average insolation level can be marked as similar in case of 4th April and 21st June. Although, the solar exposure hours are longest for 21st June, the average cumulative value of insolation level is higher than 4th April just in case of BrV; whereas, the RPs have significantly higher insolation level than the VPs for these two days.

The BrVs and RPs, being east-west oriented, receives a significant low amount of insolation in 22nd December. The average value of insolation for MhVs and VPs, the north-south oriented streets are more than twice the value of BrVs and RPs. It can be assumed that, in 22nd December, which is winter in Dhaka, the North-south oriented streets will be warmer, while the east-west oriented streets will remain cold.

Therefore, as a key observation it can be said that, the considering the above scenario, the north-south oriented streets are performing better than the east-west oriented streets. The north-south oriented streets has relatively lower cumulative average insolation value in 4th April and 21st June; the hot-dry and warm-humid season, while having higher value in case of 22nd December, during the cool-dry season.

131

3.9 Shadow analysis

3.9.1 Formation of 3d model for computer simulation

In order to conduct the shadow analysis of the outdoor spaces, the three dimensional model of the built environment of all the fifteen cases has been produced in Audodesk Ecotect using SI Decimal unit system. The basic information regarding the model has been shown in Table 3.16

Table 3.16: Basic Information for Shadow Analysis Sl No. Parameter Specification

1 Location Dhaka, Bangladesh

2 Latitude 23. 50°E

3 Longitude 90.20°N

4 Time Zone + 6.00 GMT

5 Unit Unit of Dimension: SI Decimal (m)

Unit for Analysis: Percentage (%)

6 Weather Data Dhaka (for parameters, refer to Table: 3.1)

3.9.2 Time-basis and other parameters

For shadow analysis, the street to be examined needs to be selected and the suth-path diagram needs to be run in order to calculate the shading percentage. The overshadowing accuracy has been considered to be ‘very high’. The time-basis and other parameters are shown in table 3.17.

Table 3.17: Time-basis and other parameters Sl No. Parameter Specification

1 Overshadow The percentage of shade and shadow casted over a surface percentage by surrounding built forms.

2 Specified Dates 04 April

21 June

22 December

132

3 Specified Time 05.30-18.30 hrs

4 Value The results are shown in percentage for every 0.5 hrs in table form and by means of stereographic diagram

3.10 Shadow analysis results

The simulation results represent the overshadowing percentage on the street surface for every half an hour from 05.30 hrs to 18.30 hrs. Due to the seasonal change in time form sunrise and sunset, the results for 4th April represents the data from 06.00 hrs to 18.00 hrs and for 22nd December, from 07.00 hrs to 17.00 hrs. The simulation results expressed in stereographic diagrams are shown in Appendix C. The shadow analysis results are of the four type of streets for the selected days are provided as follows.

3.10.1 Brahmavithi (BrV)

The overshadowing percentage of all the BrVs with hours for 4th April, 21st June and 22nd December are shown in table 3.18 and figure 3.25 expresses the data in the form of line chart. From the data, it can be observed in case of 4th April, the east-west oriented BrVs barely has shadows from 8.00-16.00 hrs. Within this period, the overshadowing percentage varies between 3%-11%. In 21st June, the line diagram is also symmetric. All the streets in this case has a critical period from 11.00-12.30 hrs, when the overshadowing percentage drastically drops from almost 65% to 0%. From 08.00-11.00 hrs and 12.30-15.30 hrs, the overshadowing percentage varies between 60%- 80%. Results of 22nd December shows that the streets remain in 65%-96% shaded condition within the day and the change in overshadowing percentage with hours is very nominal. In short, the BrVs are exposed to the sun for most of the time during the hot-dry season, have moderately shading condition during the warm-humid season and have nominal solar exposure during the winter. As all the BrVs have similar height to width ratio, the results are similar. The variation in result is induced by the number of streets that are crossed with them.

133

Table 3.18(a): Overshadowing percentage (%) of all the BrVs with hours for 4th April

Local Time (hrs)

Ratio Average 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30 Settlement Pattern Settlement

:1 1 7% 3% 96% 65% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 65% 73% 24%

7% 7% 3% 96% 73% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 11% 69% 73% 24% 1.5:1 Dandaka

2:1 7% 7% 3% 96% 73% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 11% 11% 69% 76% 24%

1:1 3%

69% 15% 11% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 69% 76% 25% 100%

7% 3% 73% 11% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 11% 73% 76% 24% 1.5:1 100%

Sarvatobhadra

2:1 7% 7% 3% 76% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 11% 11% 73% 80% 24% 100%

1:1 3% 69% 15% 11% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 11% 11% 69% 76% 24% 100%

N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 1.5:1 Nandyavarta

2:1 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

1:1 7% 7% 7% 69% 15% 15% 11% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 76% 92% 25% 100%

7% 3% 73% 11% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 73% 76% 25% 1.5:1 100% Swastika

2:1 7% 7% 3% 76% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 11% 11% 73% 80% 24% 100%

1:1 3% 69% 15% 11% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 69% 76% 25% 100%

7% 3% 73% 11% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 11% 73% 76% 24% 1.5:1 100% Prastara

2:1 7% 7% 3% 76% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 11% 11% 73% 80% 24% 100%

134

Table 3.18(b): Overshadowing percentage (%) of all the BrVs with hours for 21st June

Local Time (hrs)

Pattern

Ratio 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 Average 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30 Settlement Settlement

1:1 0% 96% 96% 92% 84% 69% 65% 61% 61% 61% 61% 57% 57% 57% 57% 57% 57% 61% 61% 61% 65% 65% 69% 84% 88% 92% 92% 68%

1 0% 1.5: 96% 96% 92% 88% 73% 69% 65% 65% 65% 65% 61% 61% 61% 61% 61% 61% 65% 65% 65% 65% 69% 73% 84% 88% 92% 92% 70% Dandaka

2:1 0% 96% 96% 92% 88% 76% 76% 73% 69% 61% 61% 61% 61% 61% 61% 65% 65% 65% 65% 65% 73% 73% 73% 84% 88% 92% 92% 72%

1:1 0% 96% 92% 80% 73% 69% 65% 65% 61% 61% 61% 57% 57% 61% 65% 65% 65% 69% 73% 73% 76% 88% 96% 96% 96% 73%

100% 100%

0% 92% 80% 80% 73% 73% 73% 69% 69% 69% 65% 65% 69% 69% 69% 69% 73% 73% 80% 80% 92% 96% 96% 96% 77% 1.5:1 100% 100% 100%

Sarvatobhadra

2:1 0% 96% 80% 80% 76% 73% 73% 73% 73% 69% 69% 73% 73% 73% 73% 73% 73% 80% 80% 80% 92% 96% 96% 96% 79% 100% 100% 100%

1:1 0% 92% 76% 73% 69% 65% 65% 65% 65% 65% 61% 61% 61% 65% 65% 65% 65% 69% 73% 76% 88% 96% 96% 96% 73% 100% 100% 100%

N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 1.5:1 Nandyavarta

2:1 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

1:1 0% 88% 73% 73% 69% 65% 65% 65% 65% 65% 61% 57% 61% 61% 61% 61% 65% 69% 73% 73% 80% 92% 96% 96% 72% 100% 100% 100%

0% 92% 80% 76% 73% 73% 73% 69% 69% 69% 65% 65% 69% 69% 69% 69% 73% 73% 76% 80% 88% 96% 96% 96% 76% 1.5:1 100% 100% 100% Swastika

2:1 0% 96% 80% 80% 76% 73% 73% 73% 73% 73% 69% 69% 73% 73% 73% 73% 73% 80% 80% 80% 88% 96% 96% 96% 78% 100% 100% 100%

1:1 0% 96% 92% 80% 73% 69% 65% 65% 65% 65% 65% 61% 61% 65% 65% 65% 65% 69% 73% 73% 80% 88% 96% 96% 96% 74% 100% 100%

0% 92% 80% 80% 73% 73% 73% 69% 69% 69% 65% 65% 69% 69% 69% 69% 73% 73% 80% 80% 92% 96% 96% 96% 77% 1.5:1 100% 100% 100% Prastara

2:1 0% 96% 80% 80% 76% 73% 73% 73% 73% 73% 69% 69% 73% 73% 73% 73% 73% 80% 80% 80% 92% 96% 96% 96% 79% 100% 100% 100%

135

Table 3.18(c): Overshadowing percentage (%) of all the BrVs with hours for 22nd December

Local Time (hrs)

Ratio Average 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30 Settlement Pattern Settlement

1:1 92% 92% 80% 73% 73% 76% 73% 73% 73% 73% 73% 69% 69% 69% 76% 73% 76% 76% 84% 88% 88% 77%

92% 92% 76% 76% 76% 73% 73% 73% 73% 73% 73% 73% 73% 76% 73% 73% 73% 76% 88% 92% 92% 78% 1.5:1 Dandaka

2:1 92% 92% 76% 76% 76% 76% 73% 73% 73% 73% 73% 76% 76% 76% 76% 76% 76% 73% 88% 92% 92% 79%

1:1 96% 96% 88% 88% 88% 88% 80% 84% 84% 80% 76% 80% 76% 76% 80% 80% 80% 84% 92% 92% 92% 85%

1 1.5: 96% 96% 88% 88% 88% 84% 88% 88% 84% 76% 76% 76% 76% 76% 80% 80% 80% 84% 96% 96% 96% 85%

Sarvatobhadra

2:1 96% 96% 88% 88% 84% 84% 84% 84% 80% 76% 76% 80% 76% 73% 80% 80% 80% 80% 96% 96% 96% 84%

1:1 96% 96% 92% 92% 88% 88% 73% 73% 69% 69% 73% 69% 73% 88% 88% 73% 84% 84% 92% 92% 92% 83%

N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 1.5:1 Nandyavarta

2:1 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

1:1 96% 96% 92% 92% 88% 88% 76% 88% 80% 80% 76% 76% 76% 80% 80% 76% 80% 84% 96% 96% 96% 85%

1 1.5: 96% 96% 92% 88% 88% 84% 76% 76% 76% 73% 73% 69% 65% 80% 80% 73% 80% 84% 96% 96% 96% 83% Swastika

2:1 96% 96% 88% 88% 84% 84% 69% 69% 69% 69% 69% 69% 65% 80% 80% 69% 80% 84% 96% 96% 96% 81%

1:1 96% 96% 92% 88% 88% 88% 84% 88% 88% 84% 76% 84% 80% 76% 80% 84% 84% 84% 92% 92% 92% 86%

96% 96% 92% 88% 88% 88% 88% 88% 88% 80% 73% 80% 84% 76% 80% 80% 84% 84% 96% 96% 96% 87% 1.5:1 Prastara

2:1 96% 96% 88% 88% 84% 84% 84% 84% 84% 80% 73% 80% 84% 76% 80% 80% 84% 84% 96% 96% 96% 86%

136

100%

90%

80%

70%

60%

50%

40%

Overshadowing Percentage 30%

20%

10%

0% 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30

a. Overshadowing percentage (%) of all the BrVs with hours for 4th April

100%

90%

80%

70%

60%

50%

40%

30% Overshadowing Percentage 20%

10%

0% 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30

b. Overshadowing percentage (%) of all the BrVs with hours for 21st June

137

100%

90%

80%

70%

60%

50%

40%

Overshadowing Percentage 30%

20%

10%

0% 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30

c. Overshadowing percentage (%) of all the BrVs with hours for 22nd December

3.25: Overshadowing percentage (%) of all the BrVs with hours

3.10.2 Mahakalavithi (MhV)

The overshadowing percentage of all the MhVs with hours for 4th April, 21st June and 22nd December are shown in table 3.19 and figure 3.26 expresses the data in the form of line chart. The data shows that the overshadowing percentage for all the three days drops for a brief period of two to three hours at the middle of the day. For 4th April, the percentage drops from approximately 70% at 12.00 hrs to 7% at 12.30 hrs and the streets remain exposed to the sun till 14.30 hrs. The percentage then increases up to 80% within the next one hour. 21st June also have almost similar scenario of 4th April. The street gets solar exposure from 12.30 to 14.30 hrs. In 22nd December, the solar exposure period shrinks down from 12.00-13.30 hrs, when the overshadowing percentage remains from 0%-20%. Apart from these critical period, the streets get sufficient shading condition for all the three days. The Like the BrVs, the MhVs also have similar height to width ratio. Therefore, the results in this case are also similar.

138

Table 3.19(a): Overshadowing percentage (%) of all the MhVs with hours for 4th April

Local Time (hrs)

Ratio 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 Average 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30 Settlement Pattern Settlement

1:1 5% 7% 92% 81% 83% 81% 89% 89% 87% 83% 77% 74% 74% 74% 69% 10% 10% 14% 31% 62% 63% 87% 89% 86% 92% 64%

1 7% 7% 1.5: 92% 80% 81% 80% 81% 83% 77% 75% 69% 68% 68% 62% 62% 10% 10% 15% 36% 62% 60% 80% 80% 87% 92% 61% Dandaka

2:1 7% 92% 81% 77% 77% 80% 77% 74% 69% 66% 63% 60% 57% 54% 10% 10% 14% 15% 36% 60% 60% 77% 80% 86% 92% 59%

1:1 7% 7%

93% 95% 93% 95% 93% 93% 93% 86% 81% 77% 75% 72% 14% 15% 21% 81% 81% 81% 93% 93% 74% 100% 100% 100%

7% 93% 92% 87% 93% 92% 92% 92% 81% 75% 72% 69% 66% 14% 15% 20% 21% 80% 81% 81% 92% 93% 72% 1.5:1 100% 100% 100% Sarvatobhadra

2:1 7% 98% 94% 90% 88% 94% 92% 90% 90% 78% 74% 70% 66% 62% 13% 17% 21% 27% 78% 78% 78% 92% 94% 98% 98% 71%

1:1 5% 7% 95% 92% 92% 92% 93% 93% 93% 83% 80% 77% 75% 72% 14% 14% 18% 66% 81% 81% 89% 87% 72% 100% 100% 100%

N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 1.5:1 Nandyavarta

2:1 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

1:1 7% 7% 94% 92% 94% 94% 94% 92% 92% 92% 83% 79% 77% 73% 71% 13% 15% 18% 58% 79% 79% 94% 94% 94% 94% 71%

7% 95% 89% 89% 92% 92% 93% 92% 80% 77% 72% 69% 66% 14% 15% 18% 23% 62% 86% 86% 95% 95% 98% 72% 1.5:1 100% 100% Swastika

2:1 7% 98% 92% 90% 90% 92% 94% 94% 92% 80% 76% 72% 68% 64% 13% 15% 23% 25% 64% 84% 84% 96% 96% 96% 98% 72%

1:1 7% 7% 95% 93% 92% 95% 93% 95% 95% 87% 83% 80% 77% 74% 14% 15% 21% 81% 83% 83% 93% 93% 98% 74% 100% 100%

7% 95% 89% 87% 92% 89% 93% 92% 81% 77% 74% 69% 66% 14% 15% 20% 23% 77% 80% 83% 93% 93% 98% 72% 1.5:1 100% 100% Prastara

2:1 7% 95% 87% 87% 92% 92% 93% 93% 80% 77% 72% 66% 62% 14% 18% 23% 25% 75% 77% 81% 92% 93% 72% 100% 100% 100%

139

Table 3.19(b): Overshadowing percentage (%) of all the MhVs with hours for 21st June

Local Time (hrs)

Ratio 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 Average 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30 Settlement Pattern Settlement

:1 1 7% 7% 93% 92% 87% 87% 83% 81% 80% 75% 69% 68% 66% 66% 63% 62% 10% 10% 10% 31% 31% 57% 60% 87% 87% 93% 93% 61%

7% 7% 93% 92% 89% 89% 81% 77% 77% 74% 66% 63% 63% 60% 57% 57% 10% 10% 14% 31% 36% 57% 57% 87% 87% 92% 93% 60% 1.5:1 Dandaka

2:1 7% 7% 93% 89% 87% 86% 86% 80% 80% 72% 66% 63% 62% 57% 56% 51% 10% 11% 15% 36% 40% 60% 60% 83% 83% 92% 92% 60%

1:1 7% 7% 98% 92% 92% 89% 83% 81% 80% 75% 72% 69% 14% 15% 18% 80% 77% 80% 81% 74% 100% 100% 100% 100% 100% 100% 100% 100%

5% 5% 98% 92% 92% 89% 80% 77% 74% 68% 66% 63% 14% 15% 21% 80% 80% 80% 83% 73% 1.5:1 100% 100% 100% 100% 100% 100% 100% 100% Sarvatobhadra

2:1 5% 5% 98% 98% 98% 98% 96% 92% 92% 88% 74% 74% 72% 64% 60% 60% 15% 19% 21% 78% 78% 82% 84% 98% 98% 98% 98% 72%

1:1 5% 5% 98% 93% 93% 89% 80% 80% 75% 74% 72% 69% 11% 14% 15% 66% 68% 87% 89% 73% 100% 100% 100% 100% 100% 100% 100% 100%

N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 1.5:1 Nandyavarta

2:1 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

1:1 7% 7% 94% 94% 94% 94% 94% 90% 90% 90% 79% 79% 73% 71% 67% 71% 13% 15% 15% 58% 58% 81% 81% 94% 94% 94% 94% 70%

7% 7% 98% 93% 93% 92% 80% 77% 74% 68% 66% 63% 15% 15% 23% 62% 63% 86% 86% 73% 1.5:1 100% 100% 100% 100% 100% 100% 100% 100% Swastika

2:1 7% 7% 98% 98% 98% 98% 96% 92% 90% 90% 76% 72% 70% 64% 60% 58% 15% 19% 23% 60% 64% 82% 84% 98% 98% 98% 98% 71%

1:1 5% 5% 98% 93% 93% 92% 83% 80% 80% 75% 72% 69% 11% 14% 15% 80% 77% 77% 83% 74% 100% 100% 100% 100% 100% 100% 100% 100%

5% 5% 95% 93% 93% 92% 81% 80% 74% 68% 66% 63% 14% 15% 20% 77% 77% 80% 83% 73% 1.5:1 100% 100% 100% 100% 100% 100% 100% 100% Prastara

2:1 5% 5% 95% 93% 93% 92% 77% 77% 72% 66% 60% 57% 15% 18% 20% 77% 77% 80% 86% 73% 100% 100% 100% 100% 100% 100% 100% 100%

140

Table 3.19(c): Overshadowing percentage (%) of all the MhVs with hours for 22nd December

Local Time (hrs)

Ratio 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 Average 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30 Settlement Pattern Settlement

1:1 0% 7% 7% 95% 95% 92% 92% 92% 86% 83% 80% 75% 75% 10% 36% 37% 68% 89% 89% 92% 95% 66%

1 1% 7% 1.5: 93% 93% 89% 89% 89% 83% 75% 75% 72% 66% 10% 10% 34% 41% 66% 89% 89% 92% 95% 65% Dandaka

2:1 0% 7% 93% 93% 89% 87% 86% 80% 74% 74% 68% 63% 10% 14% 37% 40% 62% 83% 87% 87% 95% 63%

1:1 0% 7% 98% 98% 98% 98% 98% 92% 89% 83% 80% 11% 15% 83% 83% 87% 77%

100% 100% 100% 100% 100%

0% 7% 98% 98% 98% 98% 98% 98% 89% 89% 80% 75% 11% 20% 83% 83% 86% 77% 1.5:1 100% 100% 100% 100%

Sarvatobhadra

2:1 0% 98% 98% 98% 98% 98% 98% 90% 86% 78% 70% 11% 11% 23% 80% 82% 84% 76% 100% 100% 100% 100%

1:1 0% 7% 98% 98% 98% 98% 98% 89% 87% 83% 80% 11% 15% 68% 74% 89% 76% 100% 100% 100% 100% 100%

N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 1.5:1 Nandyavarta

2:1 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

1:1 0% 7% 98% 98% 98% 98% 98% 90% 88% 84% 79% 11% 15% 60% 62% 84% 75% 100% 100% 100% 100% 100%

0% 7% 98% 98% 98% 98% 98% 98% 87% 86% 77% 75% 11% 18% 63% 63% 86% 74% 1.5:1 100% 100% 100% 100% Swastika

2:1 0% 98% 98% 98% 98% 98% 98% 88% 84% 78% 70% 11% 11% 23% 60% 66% 84% 74% 100% 100% 100% 100%

1:1 0% 7% 98% 98% 98% 98% 98% 92% 89% 83% 80% 11% 15% 81% 87% 89% 98% 77% 100% 100% 100% 100%

0% 7% 98% 98% 98% 98% 98% 98% 89% 87% 80% 75% 11% 20% 83% 87% 87% 77% 1.5:1 100% 100% 100% 100% Prastara

2:1 0% 98% 98% 98% 98% 98% 93% 87% 86% 77% 69% 11% 11% 23% 77% 83% 87% 76% 100% 100% 100% 100%

141

100%

90%

80%

70%

60%

50%

40%

Overshadowing Percentage 30%

20%

10%

0% 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30

a. Overshadowing percentage (%) of all the MhVs with hours for 4th April

100%

90%

80%

70%

60%

50%

40%

Overshadowing Percentage 30%

20%

10%

0% 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30

b. Overshadowing percentage (%) of all the MhVs with hours for 21st June

142

100%

90%

80%

70%

60%

50%

40%

Overshadowing Percentage 30% Overshadowing Percentage 20%

10%

0% 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30

c. Overshadowing percentage (%) of all the MhVs with hours for 22nd December

3.26: Overshadowing percentage (%) of all the MhVs with hours

3.10.3 Rajapatha (RP)

The overshadowing percentage of all the RPs with hours for 4th April, 21st June and 22nd December are shown in table 3.20 and figure 3.27 expresses the data in the form of line chart. The result for 4th April shows that the overshadowing percentage remains from approximately 7% to 30% during major period of daytime, which is quite low. The only exception is the SE-B of Nandyavarta (1:1). More than 60% area of this particular street remains shaded during the daytime except for sudden drop in the early morning and late afternoon. This particular street has the highest height to width ratio. Among the rest, with second highest height to width ratio, the SE-C for all the three diagrams of Prastara has the highest overshadowing percentage. On 21st June, the overshadowing percentage drops drastically at 12.00 hrs. Rest of the time, the overshadowing percentage remains from 62% to 85%. Surprisingly, the SE-B of Nandyavarta (1:1) drops more gradually than the rest. SE-A of Dandaka (1:1) can also be characterized as the same. On 22nd December, the overshadowing percentage for all the RPs stay between 85% -100%.

143

Table 3.20(a): Overshadowing percentage (%) of all the RPs with hours for 4th April

Local Time (hrs)

Ratio Average 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30 Settlement Pattern Settlement

1:1 7% 96% 61% 15% 15% 15% 19% 23% 23% 19% 23% 19% 19% 19% 15% 19% 15% 15% 15% 19% 19% 15% 15% 65% 27% 100%

4% 91% 75% 16% 16% 16% 16% 20% 16% 16% 16% 16% 16% 16% 16% 16% 16% 16% 16% 16% 16% 16% 12% 79% 27% 1.5:1 100% Dandaka

2:1 4% 8% 91% 75% 12% 16% 16% 16% 16% 16% 16% 16% 16% 16% 16% 16% 16% 16% 16% 16% 16% 16% 12% 83% 26% 100%

1:1 80% 19% 19% 26% 26% 26% 30% 26% 26% 26% 23% 23% 19% 26% 23% 23% 23% 26% 26% 19% 11% 19% 73% 34% 100% 100%

7% 80% 19% 19% 23% 26% 26% 26% 23% 26% 26% 23% 23% 15% 23% 23% 19% 23% 26% 23% 15% 15% 76% 32% 1.5:1 100% 100%

Sarvatobhadra

2:1 7% 84% 19% 19% 19% 23% 23% 26% 23% 23% 23% 19% 19% 11% 23% 19% 19% 19% 23% 19% 15% 15% 84% 31% 100% 100%

1:1 48% 40% 55% 77% 81% 77% 74% 77% 70% 70% 74% 62% 74% 70% 70% 70% 70% 70% 33% 18% 18% 68% 100% 100% 100% 100%

7% 7% 7% 7% 3% 0% 3% 84% 11% 11% 15% 11% 11% 11% 11% 11% 11% 11% 11% 11% 11% 11% 84% 22% 1.5:1 100% 100% Nandyavarta

2:1 7% 7% 7% 7% 7% 7% 7% 7% 7% 7% 7% 7% 7% 3% 0% 3% 84% 11% 11% 11% 11% 11% 84% 21% 100% 100%

1:1 7% 88% 23% 15% 19% 19% 19% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 11% 28% 100% 100% 100%

3% 80% 15% 11% 19% 19% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 73% 26% 1.5:1 100% 100% Swastika

2:1 3% 84% 15% 11% 19% 19% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 15% 11% 76% 27% 100% 100%

1:1 88% 26% 19% 26% 30% 30% 26% 26% 26% 26% 26% 26% 23% 23% 23% 19% 19% 26% 26% 19% 15% 15% 35% 100% 100% 100%

92% 19% 19% 23% 26% 26% 26% 23% 26% 23% 23% 26% 19% 23% 19% 19% 19% 23% 26% 15% 15% 15% 96% 34% 1.5:1 100% 100% Prastara

2:1 92% 19% 19% 19% 23% 23% 23% 19% 23% 19% 23% 23% 15% 19% 19% 19% 19% 23% 23% 15% 15% 11% 96% 32% 100% 100%

144

Table 3.20(b): Overshadowing percentage (%) of all the RPs with hours for 21st June

Local Time (hrs)

Ratio Pattern 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 Average 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30 Settlement Settlement

1:1 0% 96% 96% 96% 92% 73% 69% 61% 61% 57% 53% 46% 38% 42% 38% 42% 46% 53% 53% 61% 69% 73% 84% 67% 100% 100% 100% 100%

0% 95% 83% 75% 66% 62% 62% 62% 62% 62% 62% 62% 62% 62% 62% 62% 62% 66% 70% 79% 73% 1.5:1 100% 100% 100% 100% 100% 100% 100% Dandaka

2:1 0% 87% 79% 75% 66% 66% 66% 66% 66% 66% 66% 66% 66% 66% 66% 66% 75% 79% 79% 77% 100% 100% 100% 100% 100% 100% 100% 100%

1:1 0% 92% 80% 69% 69% 65% 65% 65% 65% 65% 65% 65% 65% 65% 73% 84% 88% 79%

100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

0% 92% 84% 73% 73% 73% 69% 65% 69% 65% 69% 69% 73% 73% 76% 84% 92% 81% 1.5:1 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

Sarvatobhadra

2:1 0% 96% 84% 80% 76% 73% 73% 69% 69% 69% 73% 73% 73% 73% 80% 84% 92% 83% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

1:1 7% 85% 70% 40% 37% 33% 29% 22% 22% 22% 22% 22% 25% 33% 33% 66% 74% 96% 61% 100% 100% 100% 100% 100% 100% 100% 100% 100%

0% 96% 88% 84% 84% 84% 84% 84% 84% 84% 84% 84% 84% 84% 84% 84% 84% 88% 96% 87% 1.5:1 100% 100% 100% 100% 100% 100% 100% 100% Nandyavarta

2:1 3% 96% 92% 84% 84% 84% 84% 84% 84% 84% 84% 84% 84% 84% 84% 84% 84% 92% 96% 87% 100% 100% 100% 100% 100% 100% 100% 100%

1:1 3% 88% 84% 80% 69% 65% 65% 65% 65% 65% 65% 65% 65% 65% 65% 65% 76% 80% 96% 77% 100% 100% 100% 100% 100% 100% 100% 100%

0% 92% 88% 80% 76% 73% 73% 69% 69% 69% 69% 69% 69% 73% 73% 76% 80% 92% 96% 81% 1.5:1 100% 100% 100% 100% 100% 100% 100% 100% Swastika

2:1 0% 96% 88% 84% 76% 76% 76% 73% 73% 73% 73% 73% 73% 76% 76% 76% 80% 92% 96% 83% 100% 100% 100% 100% 100% 100% 100% 100%

1:1 3% 88% 84% 80% 69% 65% 65% 65% 65% 65% 65% 65% 65% 65% 69% 65% 80% 84% 88% 78% 100% 100% 100% 100% 100% 100% 100% 100%

3% 88% 88% 84% 76% 73% 73% 69% 69% 69% 69% 69% 69% 73% 73% 73% 80% 84% 88% 80% 1.5:1 100% 100% 100% 100% 100% 100% 100% 100% Prastara

2:1 0% 88% 88% 84% 76% 76% 76% 73% 73% 73% 73% 73% 73% 76% 76% 76% 84% 84% 88% 82% 100% 100% 100% 100% 100% 100% 100% 100%

145

Table 3.20(c): Overshadowing percentage (%) of all the RPs with hours for 22nd December

Local Time (hrs)

Ratio 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 Average 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30 Settlement Pattern Settlement

1:1 96% 96% 96% 92% 88% 88% 92% 92% 92% 92% 92% 92% 92% 92% 92% 92% 96% 94% 100% 100% 100% 100%

95% 95% 95% 91% 95% 91% 95% 91% 91% 91% 91% 91% 91% 95% 91% 95% 1.5:1 100% 100% 100% 100% 100% 100% Dandaka

2:1 95% 95% 91% 91% 91% 91% 91% 87% 87% 87% 87% 87% 95% 87% 93% 100% 100% 100% 100% 100% 100% 100%

1:1 96% 96% 96% 96% 92% 96% 96% 96% 98% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

96% 96% 96% 96% 96% 96% 96% 99% 1.5:1 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Sarvatobhadra

2:1 96% 96% 96% 96% 96% 96% 96% 99% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

1:1 92% 96% 96% 96% 96% 96% 99% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

96% 96% 96% 92% 92% 96% 96% 96% 96% 96% 98% 1.5:1 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Nandyavarta

2:1 96% 96% 96% 96% 92% 96% 96% 96% 96% 96% 98% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

1:1 96% 96% 96% 96% 96% 96% 96% 96% 96% 98% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

96% 96% 96% 96% 96% 96% 96% 96% 96% 98% 1.5:1 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Swastika

2:1 96% 96% 96% 96% 96% 96% 96% 96% 98% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

1:1 96% 96% 96% 96% 96% 96% 96% 96% 98% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

96% 96% 96% 96% 96% 96% 96% 99% 1.5:1 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Prastara

2:1 96% 96% 96% 96% 96% 96% 99% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

146

100%

90%

80%

70%

60%

50%

40%

Overshadowing Percentage 30%

20%

10%

0% 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30

a. Overshadowing percentage (%) of all the RPs with hours for 4th April

100%

90%

80%

70%

60%

50%

40%

Overshadowing Percentage 30%

20%

10%

0% 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30

b. Overshadowing percentage (%) of all the RPs with hours for 21st June

147

100%

90%

80%

70%

60%

50%

40%

Overshadowing Percentage 30%

20%

10%

0% 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30

c. Overshadowing percentage (%) of all the RPs with hours for 22nd December

3.27: Overshadowing percentage (%) of all the RPs with hours

3.10.4 Vamanapatha (VP)

The overshadowing percentage of all the VPs with hours for 4th April, 21st June and 22nd December are shown in table 3.21 and figure 3.28 expresses the data in the form of line chart. All the three days shows brief solar exposure for an hour. For 4th April and 21st June, this period stays between 12.30-13.30 hrs and for 22nd December, this period lasts from 12.00-13.00 hrs. Rest of the time, the overshadowing percentage remains more than 60%. The SE-2 of Nandyavarta (1:1) and SE-2 of all the three diagrams of Prastara have the highest overshadowing percentage as they have similar height to width ratio. The SE-1 of all the three diagrams of Dandaka have the lowest shadow as they are wider than the rest of the streets and the height to width ratio is lowest among the VPs. The line chart of the percentage with hour for all the three days are quite uniform.

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Table 3.21(a): Overshadowing percentage (%) of all the VPs with hours for 4th April

Local Time (hrs)

Ratio Average 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30 Settlement Pattern Settlement

1:1 7% 94% 90% 96% 96% 96% 96% 86% 83% 79% 75% 73% 69% 67% 15% 16% 20% 50% 69% 94% 96% 96% 96% 94% 74% 100%

9% 97% 95% 95% 95% 95% 95% 82% 78% 75% 70% 68% 63% 60% 17% 24% 41% 48% 73% 75% 95% 95% 95% 95% 73% 1.5:1 100% Dandaka

2:1 97% 93% 95% 95% 95% 95% 85% 78% 72% 68% 63% 59% 55% 12% 17% 25% 51% 51% 76% 91% 95% 95% 95% 95% 74% 100%

% % % 1:1 100 100 100 95% 95% 95% 95% 98% 98% 98% 98% 87% 86% 80% 74% 10% 20% 95% 98% 98% 98% 98% 98% 95% 98% 88%

90% 96% 92% 96% 98% 98% 98% 96% 88% 86% 77% 69% 13% 22% 96% 98% 98% 98% 98% 98% 96% 98% 94% 88% 1.5:1 100% 100%

Sarvatobhadra

2:1 88% 96% 92% 96% 98% 98% 96% 96% 88% 83% 73% 64% 13% 24% 96% 96% 96% 98% 98% 98% 96% 98% 94% 87% 100% 100%

1:1 98% 98% 98% 89% 77% 69% 14% 23% 98% 98% 98% 98% 98% 90% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

7% 98% 98% 98% 95% 95% 95% 95% 86% 86% 81% 81% 80% 10% 14% 83% 83% 98% 98% 95% 95% 98% 83% 1.5:1 100% 100% 100% Nandyavarta

2:1 7% 98% 95% 95% 95% 95% 95% 95% 86% 83% 81% 80% 77% 14% 15% 81% 83% 98% 98% 95% 95% 95% 82% 100% 100% 100%

1:1 7% 94% 94% 90% 86% 84% 83% 79% 13% 15% 86% 88% 98% 98% 94% 84% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

7% 89% 86% 81% 75% 75% 15% 21% 87% 89% 85% 1.5:1 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Swastika

2:1 87% 81% 80% 75% 69% 10% 15% 23% 87% 87% 98% 84% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

1:1 9% 92% 94% 94% 96% 90% 88% 81% 77% 16% 90% 94% 94% 94% 94% 94% 92% 96% 94% 87% 100% 100% 100% 100% 100% 100%

90% 90% 90% 92% 96% 94% 94% 92% 84% 83% 73% 67% 13% 22% 90% 92% 92% 94% 94% 94% 88% 94% 94% 84% 1.5:1 100% 100% Prastara

2:1 86% 88% 86% 90% 94% 94% 92% 92% 84% 79% 67% 62% 13% 22% 90% 90% 92% 94% 94% 94% 90% 94% 94% 83% 100% 100%

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Table 3.21(b): Overshadowing percentage (%) of all the VPs with hours for 21st June

Local Time (hrs)

Ratio 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 Average 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30 Settlement Pattern Settlement

1:1 7% 92% 92% 90% 88% 84% 81% 73% 71% 69% 67% 64% 67% 11% 16% 20% 47% 64% 69% 92% 92% 92% 98% 72% 100% 100% 100% 100%

9% 97% 95% 95% 95% 82% 82% 80% 78% 70% 68% 63% 60% 14% 21% 24% 48% 68% 68% 95% 97% 95% 97% 74% 1.5:1 100% 100% 100% 100% Dandaka

2:1 95% 95% 93% 91% 80% 76% 70% 68% 65% 61% 59% 55% 12% 17% 25% 27% 48% 70% 74% 93% 93% 95% 97% 73% 100% 100% 100% 100%

1:1 95% 95% 95% 93% 93% 93% 86% 81% 77% 69% 10% 14% 93% 93% 93% 93% 93% 93% 98% 87%

100% 100% 100% 100% 100% 100% 100% 100%

94% 90% 90% 90% 88% 88% 88% 79% 73% 66% 67% 11% 15% 84% 86% 86% 86% 86% 86% 92% 94% 83% 1.5:1 100% 100% 100% 100% 100% 100%

Sarvatobhadra

2:1 94% 90% 88% 88% 86% 86% 86% 77% 69% 62% 60% 11% 16% 84% 84% 84% 84% 86% 86% 92% 94% 82% 100% 100% 100% 100% 100% 100%

1:1 86% 75% 72% 11% 15% 95% 95% 95% 95% 95% 98% 90% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

7% 98% 98% 98% 89% 87% 87% 83% 83% 81% 10% 14% 81% 81% 95% 98% 98% 85% 1.5:1 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Nandyavarta

2:1 7% 98% 98% 98% 87% 87% 83% 81% 80% 77% 10% 15% 81% 81% 95% 95% 98% 84% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

1:1 7% 94% 94% 94% 94% 94% 94% 84% 84% 81% 79% 77% 81% 11% 15% 83% 84% 94% 94% 94% 94% 94% 82% 100% 100% 100% 100% 100%

89% 86% 86% 80% 75% 75% 10% 14% 20% 87% 87% 95% 95% 95% 95% 85% 1.5:1 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Swastika

2:1 87% 86% 83% 75% 75% 72% 10% 14% 21% 87% 87% 95% 95% 95% 95% 84% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

1:1 94% 92% 92% 92% 86% 86% 86% 79% 75% 69% 71% 11% 13% 88% 88% 88% 88% 94% 94% 94% 94% 84% 100% 100% 100% 100% 100% 100%

94% 92% 92% 92% 86% 86% 86% 77% 71% 64% 64% 11% 15% 84% 83% 83% 83% 86% 88% 94% 94% 82% 1.5:1 100% 100% 100% 100% 100% 100% Prastara

2:1 94% 88% 88% 88% 83% 83% 83% 69% 60% 54% 56% 11% 16% 77% 83% 83% 83% 84% 86% 92% 94% 80% 100% 100% 100% 100% 100% 100%

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Table 3.21(c): Overshadowing percentage (%) of all the VPs with hours for 22nd December

Local Time (hrs)

Ratio 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 Average 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30 Settlement Pattern Settlement

1:1 0% 98% 98% 98% 98% 98% 88% 84% 81% 75% 73% 11% 13% 20% 69% 75% 75% 100% 100% 100% 100% 100%

1 % % % % % 4% 100 100 100 100 100 1.5: 97% 97% 97% 97% 97% 87% 80% 80% 70% 68% 14% 17% 48% 70% 73% 76% Dandaka

2:1 6% 97% 97% 97% 95% 93% 87% 78% 74% 68% 63% 14% 19% 46% 68% 76% 95% 97% 75% 100% 100% 100%

1:1 3% 98% 98% 98% 98% 98% 87% 81% 15% 21% 98% 98% 85% 100% 100% 100% 100% 100% 100% 100% 100% 100%

5% 98% 88% 79% 16% 22% 98% 98% 98% 86% 1.5:1 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Sarvatobhadra

2:1 5% 88% 77% 20% 28% 98% 98% 98% 98% 86% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

1:1 92% 80% 10% 21% 30% 87% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

0% 7% 98% 92% 89% 86% 86% 11% 80% 98% 95% 98% 83% 1.5:1 100% 100% 100% 100% 100% 100% 100% 100% 100% Nandyavarta

2:1 0% 7% 98% 98% 92% 89% 86% 83% 11% 80% 95% 83% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

1:1 0% 98% 98% 98% 98% 92% 90% 86% 83% 11% 13% 86% 98% 83% 100% 100% 100% 100% 100% 100% 100% 100%

1% 98% 98% 98% 98% 98% 98% 92% 89% 81% 75% 11% 14% 87% 98% 98% 83% 1.5:1 100% 100% 100% 100% 100% Swastika

2:1 1% 98% 98% 98% 98% 98% 98% 89% 87% 80% 75% 14% 15% 83% 98% 98% 82% 100% 100% 100% 100% 100%

1:1 3% 98% 98% 88% 81% 11% 20% 98% 98% 85% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

7% 98% 88% 77% 16% 18% 98% 98% 98% 86% 1.5:1 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Prastara

2:1 7% 98% 88% 77% 20% 26% 98% 98% 98% 98% 86% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

151

100%

90%

80%

70%

60%

50%

40%

Overshadowing Percentage 30%

20%

10%

0% 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30

a. Overshadowing percentage (%) of all the VPs with hours for 4th April

100%

90%

80%

70%

60%

50%

40%

Overshadowing Percentage 30%

20%

10%

0% 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30

b. Overshadowing percentage (%) of all the VPs with hours for 21st June

152

100%

90%

80%

70%

60%

50%

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Overshadowing Percentage 30%

20%

10%

0% 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30

c. Overshadowing percentage (%) of all the VPs with hours for 22nd December

3.28: Overshadowing percentage (%) of all the VPs with hours

3.10.5 Average shading condition

In this section, the average shading condition for a street for a particular day has been taken for discussion. Table 3.22 and Figure 3.29 shows the average shading condition for all the streets for 4th April, 21st June and 22nd December. The data for 4th April shows that the average overshadowing percentage remains significantly low for the east-west oriented streets, the BrVs and the RPs. The north-south oriented streets have more than twice the percentage for shadow coverage. In 21st June, all the streets have almost same average overshadowing percentage; even so, the VPs have slightly higher shaded areas. In 22nd December, the east-west oriented streets have higher overshadowing percentage than the north-south oriented streets. The BrVs are shaded more than 80% on average and the RPs have more than 90% overshadowing percentage. On the other hand, the MhVs and the VPs have overshadowing percentage ranging between 65-77% and 75- 86% respectively.

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Table 3.22 (a): Average overshadowing percentage (%) of all the types of street with hours for 4th April

Settlement 4th April Pattern Ratio BrV MhV RP VP Dandaka 1:1 24% 64% SE-A 27% SE-1 74% 1.5:1 24% 61% SE-A 27% SE-2 73% 2:1 24% 59% SE-A 26% SE-3 74% Sarvatobhadra 1:1 25% 74% SE-B 34% SE-2 88% 1.5:1 24% 72% SE-B 32% SE-2 88% 2:1 24% 71% SE-B 31% SE-2 87% Nandyavarta 1:1 24% 72% SE-B 68% SE-2 90% 1.5:1 N/A N/A SE-C 22% SE-4 83% 2:1 N/A N/A SE-C 21% SE-4 82% Swastika 1:1 25% 71% SE-A 28% SE-4 84% 1.5:1 25% 72% SE-A 26% SE-4 85% 2:1 24% 72% SE-A 27% SE-4 84% Prastara 1:1 25% 74% SE-C 35% SE-2 87% 1.5:1 24% 72% SE-C 34% SE-2 84% 2:1 24% 72% SE-C 32% SE-2 83%

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Dandaka Dandaka 1:1 Dandaka 1.5:1 Dandaka 2:1 Sarvatobhadra1:1 Sarvatobhadra1.5:1 Sarvatobhadra2:1 Nandyavarta 1:1 Nandyavarta 1.5:1 Nandyavarta 2:1 1:1Swastika 1.5:1Swastika 2:1Swastika Prastara 1:1 Prastara 1.5:1 Prastara 2:1

BrV MhV RP VP

Figure 3.29(a): Average overshadowing percentage (%) of all the types of street with hours for 4th April

154

Table 3.22(b): Average overshadowing percentage (%) of all the types of street with hours for 21st June

Settlement 21st June Pattern Ratio BrV MhV RP VP Dandaka 1:1 68% 61% SE-A 67% SE-1 72% 1.5:1 70% 60% SE-A 73% SE-2 74% 2:1 72% 60% SE-A 77% SE-3 73% Sarvatobhadra 1:1 73% 74% SE-B 79% SE-2 87% 1.5:1 77% 73% SE-B 81% SE-2 83% 2:1 79% 72% SE-B 83% SE-2 82% Nandyavarta 1:1 73% 73% SE-B 61% SE-2 90% 1.5:1 N/A N/A SE-C 87% SE-4 85% 2:1 N/A N/A SE-C 87% SE-4 84% Swastika 1:1 72% 70% SE-A 77% SE-4 82% 1.5:1 76% 73% SE-A 81% SE-4 85% 2:1 78% 71% SE-A 83% SE-4 84% Prastara 1:1 74% 74% SE-C 78% SE-2 84% 1.5:1 77% 73% SE-C 80% SE-2 82% 2:1 79% 73% SE-C 82% SE-2 80%

BrV MhV RP VP

Figure 3.29(b): Average overshadowing percentage (%) of all the types of street with hours for 21st June

155

Table 3.22(c): Average overshadowing percentage (%) of all the types of street with hours for 22nd December

21st June Settlement Pattern Ratio BrV MhV RP VP Dandaka 1:1 77% 66% SE-A 94% SE-1 75% 1.5:1 78% 65% SE-A 95% SE-2 76% 2:1 79% 63% SE-A 93% SE-3 75% Sarvatobhadra 1:1 85% 77% SE-B 98% SE-2 85% 1.5:1 85% 77% SE-B 99% SE-2 86% 2:1 84% 76% SE-B 99% SE-2 86% Nandyavarta 1:1 83% 76% SE-B 99% SE-2 87% 1.5:1 N/A N/A SE-C 98% SE-4 83% 2:1 N/A N/A SE-C 98% SE-4 83% Swastika 1:1 85% 75% SE-A 98% SE-4 83% 1.5:1 83% 74% SE-A 98% SE-4 83% 2:1 81% 74% SE-A 98% SE-4 82% Prastara 1:1 86% 77% SE-C 98% SE-2 85% 1.5:1 87% 77% SE-C 99% SE-2 86% 2:1 86% 76% SE-C 99% SE-2 86%

BrV MhV RP VP

Figure 3.29(c): Average overshadowing percentage (%) of all the types of street with hours for 22nd December

156

3.11 Wind flow analysis

The wind simulation has been conducted in this research for analyzing wind behavior in the outdoor spaces (streets in this particular case). The simulation has been done using ‘Autodesk Flow Design’, where the urban blocks were modelled as solids and the wind flow around these solids were observed. The software simulates the wind flow using a virtual wind tunnel with either a primary wind velocity or pressure value, which can be provided as needed. The simulation produces an animated image as output which represents the velocity or pressure with color-code and also shows the motion of the flow in three-dimension. It also possible to extract the result of a particular plane using any two axis.

For minimizing the simulation load, only the south-east quarter of all the settlement patterns has been modelled using SI unit and the model was reduced to a scale of 1:10. The model was imported in the software in 3ds format. No material or weather data is required for this virtual tunnel test. The basic information for wind flow simulation is shown in table 3.23.

Table 3.23: Basic information for wind simulation Sl No. Parameter Specification

1 velocity m/s

2 Unit SI

3 Input Velocity 2.78 m/s

4 Flow direction South to North

4 Scale 1:10

5 Output Plane Axis: XY

Height: 1.2 m

From topic 3.2.5 (Annual wind flow condition) it is found that the maximum wind flow comes from south with the wind speed of 2.78 m/s at10m height for more than 632 hours. Using this reference the model was oriented within the tunnel in a manner that the wind will flow from south to north of the model with an input velocity of 2.78 m/s. The software automatically adjusts the mesh size according to the resolution. For this research, the resolution was provided to 180%, for which the voxel sizes varies from

157

0.33 to 0.35m. The result was taken on a plane in XY axis at 1.2m above ground as this represents the human height.

Figure 3.30: Wind flow simulation in a virtual wind tunnel using ‘Autodesk Flow Design’

3.12 Wind simulation results

The output wind velocity against an input value of 2.78 m/s has been measured at the center of every street that are subject to this study. The results are shown in table 3.23 and plotted in figure 3.31 in the form of bar chart. From the data, it can be observed that the east-west oriented BrVs and RPs have noticeably low wind flow compared to the north-south oriented streets. The wind velocity for the BrVs range from 0.1-0.4 m/s, while the wind velocity for the RPs varies between 0.1-0.4 m/s. The north-south oriented streets are found to have significant wind flow through them at human height. The output wind velocity for the MhVs ranges from 2-3 m/s. In case of the VPs, the range is found to be 1.5-2.m m/s. Only the SE-2 of Sarvatobhadra (2:1) has been found to have 0.1 m/s, which is very low compared to the other diagrams. From the above scenario, we can assume that for southward wind, the orthogonal street patterns better facilitates the north-south oriented streets in terms of wind velocity at pedestrian level than the east-west oriented streets. The simulation results in the form of color coded image for all the diagrams are shown from figure 3.32-3.36.

158

Table 3.24: Output wind velocity in the streets of all the diagrams

Wind Velocity (m/s) Settlement Pattern Ratio BrV MhV RP VP Dandaka 1:1 0.3 2 SE-A 0.2 SE-1 1.5 1.5:1 0.1 2.5 SE-A 0.1 SE-2 2 2:1 0.2 2.5 SE-A 0.1 SE-3 1.75 Sarvatobhadra 1:1 0.2 2.2 SE-B 0.1 SE-2 2 1.5:1 0.2 2.3 SE-B 0.1 SE-2 0.5 2:1 0.2 2.2 SE-B 0.2 SE-2 0.1 Nandyavarta 1:1 0.3 2.9 SE-B 0.1 SE-2 2 1.5:1 N/A N/A SE-C 0.4 SE-4 2.3 2:1 N/A N/A SE-C 0.4 SE-4 2 Swastika 1:1 0.2 2 SE-A 0.2 SE-4 1 1.5:1 0.4 2.3 SE-A 0.1 SE-4 2 2:1 0.3 2.2 SE-A 0.1 SE-4 2 Prastara 1:1 0.3 2.4 SE-C 0.1 SE-2 1.5 1.5:1 0.3 3 SE-C 0.1 SE-2 0.75 2:1 0.2 2.4 SE-C 0.1 SE-2 1.5

3.5

2.5

1.5

0.5

0 Dandaka Dandaka 1:1 Dandaka 1.5:1 Dandaka 2:1 Sarvatobhadra1:1 Sarvatobhadra1.5:1 Sarvatobhadra2:1 Nandyavarta 1:1 Nandyavarta 1.5:1 Nandyavarta 2:1 1:1 Swastika 1.5:1 Swastika 2:1 Swastika Prastara 1:1 Prastara 1.5:1 Prastara 2:1

BrV MhV RP VP

Figure 3.31: Output wind velocity in the streets of all the diagrams

159

(a) Wind flow simulation of Dandaka 1:1

(b) Wind flow simulation of Dandaka 1:1

160

(a) Wind flow simulation of Sarvatobhadra 1:1

(b) Wind flow simulation of Sarvatobhadra 1:1

161

(a) Wind flow simulation of Nandyavarta 1:1

(b) Wind flow simulation of Nandyavarta 1:1

162

(a) Wind flow simulation of Swastika 1:1

(b) Wind flow simulation of Swastika 1:1

163

(a) Wind flow simulation of Prastara 1:1

(b) Wind flow simulation of Prastara 1:1

164

Considering southward wind covering most of the year, it is evident from the simulation results that the diagrams with more north-south oriented streets are facilitating wind flow within the village. Therefore, more perforated villages in terms of VPs and RPs induce more wind flow than the solid ones. For example, in Sarvaotobhadara, Nandyavarta (1:1) and Prastara, the RPs are intersected with several VPs with higher wind velocity. This situation induces wind flow in the RPs to some extent and street has avenue for wind flow at regular interval. Compared to that, the Dandaka have longer east-west oriented streets with relatively lower wind flow. Although, the Swastika is showing high wind velocity through the VPs, the diagram has different orientation of rectilinear urban blocks for each quarter. Therefore, the scenario may show the opposite result for the south-west quarter, which has three RPs and only one VP. In terms of built-environment parameter, the diagrams with higher surface to volume ratio have shown superior wind flow and velocity.

3.13 Performance indicator

In order to evaluate the performance of all the fifteen types of settlement in terms of the three dependent variable in a comprehensive manner, a quantitative performance indication method has been developed. The Performance Indicator uses a numeric rating scale which considers equal weightage for the average values of the three output variables, which are the solar insolation level, overshadowing percentage and wind velocity. For evaluating solar insolation and overshadowing percentage, strategic goals has been determined for each of the three sample days and numeric values has been deduced based on them. However, the strategic goals for wind velocity evaluation is irrespective of the sample days. The summation of all the values thus represents the overall rating of a particular pattern. The patterns are then ranked from highest to lowest based on their ratings. Since, Nandyavarta (1.5:1) and Nandyavarta (2:1) have no Brahmavithi and Mahakalavithi, they have not been considered to be evaluated with the other settlement patterns in the same scale; although, their performance has been taken into account and will be discussed in this section.

165

3.13.1 Solar insolation

The maximum value of average insolation for a particular day has been considered as the benchmark against which the performance of a specific street is to be measured. The following strategies has been considered for determining the numeric rating value for solar insolation level.

For 4th April: Being the hottest month of the year, April, as a month falls into category of hot-dry season. In terms of urban comfort, the street with higher average insolation level has been considered to be underperforming in this research. Therefore the numeric rating value of a particular street has been deducted as per following equation:

Inap = 1-(Inav / Inmax)

th Here, Inap represents the deduced rating value for 4 April, Inav represents the average insolation level of that street and Inmax represents the maximum insolation level for that day. The numeric value provides a rating in a scale of 0 to 1 and subtracting from 1 provides a negative rating. It means, if a street has average insolation level closer to the maximum, it will get a lower rating value than the one with insolation level distant from the maximum.

th In 4 April, the maximum insolation level (Inmax) has been identified to be 2657.5 Wh/(m-2.day). Based on that, the numeric rating for all the four type of streets are shown in table 3.25(a). As a the numeric rating value of a single street is presented in a scale of 0 to 1, the summation of the numeric values of all the four types of streets are deducted in a scale of 0 to 4.

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Table 3.25(a): Numeric Rating Value of All the streets in terms of Solar Insolation level for 4th April.

Settlement Ratio BrV MhV RP VP 4) Pattern -

Total av av av av 1) 1) 1) 1) - - - - In In In In (0 (0 (0 (0 .day) .day) .day) .day)

2 2 2 2 Street Street

- - - - ap ap ap ap In In In In Wh/(m Wh/(m Wh/(m Wh/(m Rating Scale (0 Scale Rating

Dandaka 1:1 1963.3 0.26 2246.7 0.15 SE-A 2317.5 0.13 SE-1 1552.5 0.42 0.96 1.5:1 1963.3 0.26 2218.3 0.17 SE-A 2317.5 0.13 SE-2 1850.0 0.30 0.86 2:1 1991.7 0.25 2218.3 0.17 SE-A 2657.5 0.00 SE-3 1935.0 0.27 0.69 Sarvatobhadra 1:1 1991.7 0.25 1566.7 0.41 SE-B 2232.5 0.16 SE-2 893.8 0.66 1.48 1.5:1 1991.7 0.25 2246.7 0.15 SE-B 2232.5 0.16 SE-2 1148.8 0.57 1.13 2:1 1991.7 0.25 1651.7 0.38 SE-B 2232.5 0.16 SE-2 957.5 0.64 1.43 Nandyavarta 1:1 1963.3 0.26 1878.3 0.29 SE-B 2232.5 0.16 SE-2 766.3 0.71 1.43 1.5:1 N/A N/A N/A N/A SE-C 2551.3 0.04 SE-4 1212.5 0.54 N/A 2:1 N/A N/A N/A N/A SE-C 2551.3 0.04 SE-4 1276.3 0.52 N/A Swastika 1:1 2048.3 0.23 2303.3 0.13 SE-A 2041.3 0.23 SE-4 1021.3 0.62 1.21 1.5:1 2048.3 0.23 1906.7 0.28 SE-A 2168.8 0.18 SE-4 1276.3 0.52 1.22 2:1 1963.3 0.26 2105.6 0.21 SE-A 2041.3 0.23 SE-4 1212.5 0.54 1.24 Prastara 1:1 1991.7 0.25 2246.7 0.15 SE-C 2423.8 0.09 SE-2 702.5 0.74 1.23 1.5:1 1991.7 0.25 1651.7 0.38 SE-C 2423.8 0.09 SE-2 766.3 0.71 1.43 2:1 1991.7 0.25 2246.7 0.15 SE-C 2423.8 0.09 SE-2 957.5 0.64 1.13

For 21st June: The consideration for 21st June is similar to the previous case. In this warm-humid period, lower insolation is desirable. Hence, the equation for numeric rating value is also the same:

Injn = 1-(Inav / Inmax)

Here, Injn and Inmax represents the deduced rating value and maximum insolation for a st specific street in 21 June respectively. Inav represents the average insolation level of -2 that street. The value of Inmax has been identified to be 2785.6 Wh/(m .day).Table 3.25(b) represents the numeric rating of all the four type of streets for 21st June.

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Table 3.25(b): Numeric Rating Value of All the streets in terms of Solar Insolation level for 21st June.

BrV MhV RP VP 4)

- av av av 1) 1) 1) 1) - - - - In In In

(0 (0 (0 (0

.day) .day) .day)

2 2 2 Street Street - - - jn jn jn jn In In In In Total .day) 2 - Wh/(m Wh/(m Wh/(m

Rating Scale (0 Scale Rating Settlement av Pattern Ratio In Wh/(m Dandaka 1:1 2379.4 0.15 2379.4 0.15 SE-A 1865.8 0.33 SE-1 1758.3 0.37 0.99 1.5:1 2618.3 0.06 2283.9 0.18 SE-A 1865.8 0.33 SE-2 1973.3 0.29 0.86 2:1 2618.3 0.06 2283.9 0.18 SE-A 2618.3 0.06 SE-3 2152.5 0.23 0.53 Sarvatobhadra 1:1 2642.2 0.05 1901.7 0.32 SE-B 1668.8 0.40 SE-2 970.0 0.65 1.42 1.5:1 2618.3 0.06 2116.7 0.24 SE-B 1883.8 0.32 SE-2 1185.0 0.57 1.20 2:1 2618.3 0.06 1925.6 0.31 SE-B 1131.3 0.59 SE-2 1023.8 0.63 1.60 Nandyavarta 1:1 2785.6 0.00 1901.7 0.32 SE-B 2098.8 0.25 SE-2 701.3 0.75 1.31 1.5:1 N/A N/A N/A N/A N/A SE-C 2206.3 0.21 SE-4 1561.3 0.44 2:1 N/A N/A N/A N/A N/A SE-C 1937.5 0.30 SE-4 1507.5 0.46 Swastika 1:1 2642.2 0.05 2188.3 0.21 SE-A 1991.3 0.29 SE-4 1131.3 0.59 1.14 1.5:1 2642.2 0.05 2236.1 0.20 SE-A 1185.0 0.57 SE-4 1400.0 0.50 1.32 2:1 2690.0 0.03 2068.9 0.26 SE-A 916.3 0.67 SE-4 1185.0 0.57 1.54 Prastara 1:1 2570.6 0.08 1877.8 0.33 SE-C 1185.0 0.57 SE-2 1023.8 0.63 1.61 1.5:1 2642.2 0.05 1925.6 0.31 SE-C 1722.5 0.38 SE-2 916.3 0.67 1.41 2:1 2642.2 0.05 2212.2 0.21 SE-C 2206.3 0.21 SE-2 970.0 0.65 1.12

For 22nd December: In cool-dry season, higher insolation value is desirable in terms of thermal comfort. Therefore, in case of 22nd December, the streets with higher insolation level are considered better performing. The equation for deducting the numeric rating system for a particular street for this day is:

Indc = Inav / Inmax

Here, Indc and Inmax represents the deduced rating value and maximum insolation for a nd specific street in 22 December respectively. Inav represents the average insolation -2 level of that street. The value of Inmax has been identified to be 1004.4 Wh/(m .day). Table 3.25(c) represents the numeric rating of all the four type of streets for 22nd December.

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Table 3.25(c): Numeric Rating Value of All the streets in terms of Solar Insolation level for 22nd December.

BrV MhV RP VP 4)

- av av av av 1) 1) 1) 1) - - - - In In In In

.day) .day) .day) .day) (0 (0 (0 (0 2 2 2 2 Street Street

- - - - dc dc dc dc Total In In In In Wh/(m Wh/(m Wh/(m Wh/(m

Settlement (0 Scale Rating Pattern Ratio Dandaka 1:1 430.0 0.43 882.2 0.88 SE-A 301.7 0.30 SE-1 686.7 0.68 2.29 1.5:1 381.1 0.38 980.0 0.98 SE-A 301.7 0.30 SE-2 943.3 0.94 2.59 2:1 381.1 0.38 1004.4 1.00 SE-A 393.3 0.39 SE-3 925.0 0.92 2.69 Sarvatobhadra 1:1 381.1 0.38 735.6 0.73 SE-B 210.0 0.21 SE-2 320.0 0.32 1.64 1.5:1 381.1 0.38 894.4 0.89 SE-B 210.0 0.21 SE-2 375.0 0.37 1.85 2:1 381.1 0.38 723.3 0.72 SE-B 210.0 0.21 SE-2 402.5 0.40 1.71 Nandyavarta 1:1 430.0 0.43 747.8 0.74 SE-B 210.0 0.21 SE-2 292.5 0.29 1.67 1.5:1 N/A N/A N/A N/A N/A SE-C 320.0 0.32 SE-4 622.5 0.62 2:1 N/A N/A N/A N/A N/A SE-C 320.0 0.32 SE-4 485.0 0.48 Swastika 1:1 393.3 0.39 967.8 0.96 SE-A 292.5 0.29 SE-4 402.5 0.40 2.05 1.5:1 393.3 0.39 760.0 0.76 SE-A 292.5 0.29 SE-4 677.5 0.67 2.11 2:1 381.1 0.38 735.6 0.73 SE-A 265.0 0.26 SE-4 402.5 0.40 1.78 Prastara 1:1 393.3 0.39 723.3 0.72 SE-C 210.0 0.21 SE-2 402.5 0.40 1.72 1.5:1 381.1 0.38 735.6 0.73 SE-C 237.5 0.24 SE-2 402.5 0.40 1.75 2:1 381.1 0.38 943.3 0.94 SE-C 237.5 0.24 SE-2 402.5 0.40 1.96

3.13.2 Overshadowing percentage

The average overshadowing percentage of a specific street for a particular day has been converted into a numeric rating scale of 0 to 1 in this stage. The following strategies has been considered for determining the numeric rating value for overshadowing percentage.

For 4th April: It is seen in the previous chapter that shadow condition of the streets represents ‘Tropism’, a behavioral determinant of thermal comfort. Within the same air temperature, people prefers to walk along the shaded streets in summer. Therefore, in case of 4th April, more shaded streets has been considered better performing. Hence, the numeric rating value of a particular street has been deducted as per following equation:

OPap = OPav / 100%

169

th Here, OPap represents the deduced rating value for 4 April, OPav represents the average overshadowing percentage of that street. Table 3.26(a) represents the numeric rating of all the four type of streets for 4th April.

Table 3.26(a): Numeric Rating Value of All the streets in terms of Overshadowing Percentage for 4th April.

4) - BrV MhV RP VP

1) 1) 1) 1) - - - - Total

(0 (0 (0 (0

Settlement av ap av ap av ap av ap %) %) %) %) Rating Scale (0 Scale Rating Pattern Ratio OP ( OP OP ( OP Street OP ( OP Street OP ( OP Dandaka 1:1 24% 0.24 61% 0.64 SE-A 27% 0.27 SE-1 74% 0.74 1.90 1.5:1 24% 0.24 60% 0.61 SE-A 27% 0.27 SE-2 73% 0.73 1.85 2:1 24% 0.24 60% 0.59 SE-A 26% 0.26 SE-3 74% 0.74 1.83 Sarvatobhadra 1:1 25% 0.25 74% 0.74 SE-B 34% 0.34 SE-2 88% 0.88 2.20 1.5:1 24% 0.24 73% 0.72 SE-B 32% 0.32 SE-2 88% 0.88 2.17 2:1 24% 0.24 72% 0.71 SE-B 31% 0.31 SE-2 87% 0.87 2.14 Nandyavarta 1:1 24% 0.24 73% 0.72 SE-B 68% 0.68 SE-2 90% 0.90 2.54 1.5:1 N/A N/A N/A N/A N/A SE-C 22% 0.22 SE-4 83% 0.83 2:1 N/A N/A N/A N/A N/A SE-C 21% 0.21 SE-4 82% 0.82 Swastika 1:1 25% 0.25 70% 0.71 SE-A 28% 0.28 SE-4 84% 0.84 2.09 1.5:1 25% 0.25 73% 0.72 SE-A 26% 0.26 SE-4 85% 0.85 2.08 2:1 24% 0.24 71% 0.72 SE-A 27% 0.27 SE-4 84% 0.84 2.07 Prastara 1:1 25% 0.25 74% 0.74 SE-C 35% 0.35 SE-2 87% 0.87 2.21 1.5:1 24% 0.24 73% 0.72 SE-C 34% 0.34 SE-2 84% 0.84 2.15 2:1 24% 0.24 73% 0.72 SE-C 32% 0.32 SE-2 83% 0.83 2.12

For 21st June: Being located in warm-humid season, in most the time of June overcast sky condition prevails. Nevertheless, the direct sun is still undesirable. Therefore, the equation for determining the numeric value of overshadowing percentage is the same as the previous case:

OPjn = OPav / 100%

st Here, OPjn represents the deduced rating value for 21 June for a specific street, while

OPav represents the average overshadowing percentage of that street. Table 3.26(b) represents the numeric rating of all the four type of streets for 21st June.

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Table 3.26(b): Numeric Rating Value of All the streets in terms of Overshadowing Percentage for 21st June.

BrV MhV RP VP 4) -

1) 1) 1) 1) - - - Total -

(0 (0 (0

Settlement av jn av jn av jn av jn %) %) %) %) Rating Scale (0 Scale Rating Pattern Ratio OP ( OP OP ( OP Street OP ( OP Street OP ( OP Dandaka 1:1 68% 0.68 61% 0.61 SE-A 67% 0.67 SE-1 72% 0.72 2.68 1.5:1 70% 0.70 60% 0.60 SE-A 73% 0.73 SE-2 74% 0.74 2.78 2:1 72% 0.72 60% 0.60 SE-A 77% 0.77 SE-3 73% 0.73 2.81 Sarvatobhadra 1:1 73% 0.73 74% 0.74 SE-B 79% 0.79 SE-2 87% 0.87 3.14 1.5:1 77% 0.77 73% 0.73 SE-B 81% 0.81 SE-2 83% 0.83 3.14 2:1 79% 0.79 72% 0.72 SE-B 83% 0.83 SE-2 82% 0.82 3.15 Nandyavarta 1:1 73% 0.73 73% 0.73 SE-B 61% 0.61 SE-2 90% 0.90 2.97 1.5:1 N/A N/A N/A N/A N/A SE-C 87% 0.87 SE-4 85% 0.85 2:1 N/A N/A N/A N/A N/A SE-C 87% 0.87 SE-4 84% 0.84 Swastika 1:1 72% 0.72 70% 0.70 SE-A 77% 0.77 SE-4 82% 0.82 3.01 1.5:1 76% 0.76 73% 0.73 SE-A 81% 0.81 SE-4 85% 0.85 3.15 2:1 78% 0.78 71% 0.71 SE-A 83% 0.83 SE-4 84% 0.84 3.16 Prastara 1:1 74% 0.74 74% 0.74 SE-C 78% 0.78 SE-2 84% 0.84 3.10 1.5:1 77% 0.77 73% 0.73 SE-C 80% 0.80 SE-2 82% 0.82 3.13 2:1 79% 0.79 73% 0.73 SE-C 82% 0.82 SE-2 80% 0.80 3.13

For 22nd December: In cool dry season, the angle of the sun remains closer to the horizon and the heat is not as much scorching as the hot-dry or warm-humid season. In terms of thermal comfort, direct sun in the outdoor spaces is welcomed. Therefore, the overshadowed situation has been considered as low performing in this case. Hence the equation is as follows:

OPdc = 1-(OPav / 100%)

nd Here, OPdc represents the deduced rating value for 22 December for a specific street, while OPav represents the average overshadowing percentage of that street. Table 3.26(c) represents the numeric rating of all the four type of streets for 22nd December.

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Table 3.26(c): Numeric Rating Value of All the streets in terms of Overshadowing Percentage for 22nd December

Ratio BrV MhV RP VP - Total

Settlement 1) 1) 1) 1) - - - -

Pattern (%) (%) (%) (%) (0 (0 (0 (0 av av av av

Street Street dc dc dc dc OP OP OP OP Rating Scale (0 Scale Rating OP OP OP OP

Dandaka 1:1 77% 0.23 66% 0.34 SE-A 94% 0.06 SE-1 75% 0.25 0.87

1.5:1 78% 0.22 65% 0.35 SE-A 95% 0.05 SE-2 76% 0.24 0.87

2:1 79% 0.21 63% 0.37 SE-A 93% 0.07 SE-3 75% 0.25 0.90

Sarvatobhadra 1:1 85% 0.15 77% 0.23 SE-B 98% 0.02 SE-2 85% 0.15 0.54

1.5:1 85% 0.15 77% 0.23 SE-B 99% 0.01 SE-2 86% 0.14 0.53

2:1 84% 0.16 76% 0.24 SE-B 99% 0.01 SE-2 86% 0.14 0.54

Nandyavarta 1:1 83% 0.17 76% 0.24 SE-B 99% 0.01 SE-2 87% 0.13 0.55

1.5:1 N/A N/A N/A N/A SE-C 98% 0.02 SE-4 83% 0.17 N/A

2:1 N/A N/A N/A N/A SE-C 98% 0.02 SE-4 83% 0.17 N/A

Swastika 1:1 85% 0.15 75% 0.25 SE-A 98% 0.02 SE-4 83% 0.17 0.58

1.5:1 83% 0.17 74% 0.26 SE-A 98% 0.02 SE-4 83% 0.17 0.62

2:1 81% 0.19 74% 0.26 SE-A 98% 0.02 SE-4 82% 0.18 0.64

Prastara 1:1 86% 0.14 77% 0.23 SE-C 98% 0.02 SE-2 85% 0.15 0.52

1.5:1 87% 0.13 77% 0.23 SE-C 99% 0.01 SE-2 86% 0.14 0.52

2:1 86% 0.14 76% 0.24 SE-C 99% 0.01 SE-2 86% 0.14 0.54

3.13.3 Wind velocity

The numeric rating value has also been determined as a ratio of the wind velocity in a center of a specific street to the maximum wind value found from all the settlement patterns. More wind velocity at the center of the street has been considered higher

172 performing as it welcomes air flow through the urban fabric. Therefore, the equation becomes:

WV=WVst/ WVmax

Here, WV represents the deduced rating value for for a specific street, while WVst represents the average overshadowing percentage of that street. The value of maximum wind velocity WVmax has been identified to be 2.9m/s. Table 3.27 represents the numeric rating of all the four type of streets.

Table 3.27: Numeric Rating Value of All the streets in terms of Wind Velocity

BrV MhV RP VP 4) -

1) 1) 1) 1) - - - - Total

(m/s) (m/s) (m/s) (m/s) st st st st st Settlement Rating Scale (0 Scale Rating Pattern Ratio WV (0 WV WV (0 WV Street WV (0 WV Street WV (0 WV Dandaka 1:1 0.3 0.10 2 0.69 SE-A 0.2 0.07 SE-1 1.5 0.52 1.38 1.5:1 0.1 0.03 2.5 0.86 SE-A 0.1 0.03 SE-2 2 0.69 1.62 2:1 0.2 0.07 2.5 0.86 SE-A 0.1 0.03 SE-3 1.75 0.60 1.57 Sarvatobhadra 1:1 0.2 0.07 2.2 0.76 SE-B 0.1 0.03 SE-2 2 0.69 1.55 1.5:1 0.2 0.07 2.3 0.79 SE-B 0.1 0.03 SE-2 0.5 0.17 1.07 2:1 0.2 0.07 2.2 0.76 SE-B 0.2 0.07 SE-2 0.1 0.03 0.93 Nandyavarta 1:1 0.3 0.10 2.9 1.00 SE-B 0.1 0.03 SE-2 2 0.69 1.83 1.5:1 N/A N/A N/A N/A N/A SE-C 0.4 0.14 SE-4 2.3 0.79 2:1 N/A N/A N/A N/A N/A SE-C 0.4 0.14 SE-4 2 0.69 Swastika 1:1 0.2 0.07 2 0.69 SE-A 0.2 0.07 SE-4 1 0.34 1.17 1.5:1 0.4 0.14 2.3 0.79 SE-A 0.1 0.03 SE-4 2 0.69 1.66 2:1 0.3 0.10 2.2 0.76 SE-A 0.1 0.03 SE-4 2 0.69 1.59 Prastara 1:1 0.3 0.10 2.4 0.83 SE-C 0.1 0.03 SE-2 1.5 0.52 1.48 1.5:1 0.3 0.10 3 1.03 SE-C 0.1 0.03 SE-2 0.75 0.26 1.43 2:1 0.2 0.07 2.4 0.83 SE-C 0.1 0.03 SE-2 1.5 0.52 1.45

3.13.4 Performance indicator calculation

The numeric value for performance indicator has been calculated by assimilating the scores of solar insolation, overshadowing percentage and wind velocity. The numeric rating for Inap, Injn and Indc has been determined individually in a scale of 0 to 4 for all the four types of streets considering the three case days. The outcomes has been averaged in order to get a numeric rating value in a scale of 0 to 1. The data of OPap , OPjn and

173

OPdc has also been averaged to get a result in scale of 0 to 1 for a single value for overshadowing percentage. Similarly, the Wind velocity value has also been determined. The summation of these values provides a rating score in a scale of 0-3, which is considered the numeric value of performance indicator comprehensively representing all the three dependent variables. As stated earlier, the Nandyavarta (1.5:1) and Nandyavarta (2:1), not having BrV and MhV will not have a numeric value as a total performance indicator. The performance indicator values are shown in table 3.28.

Table 3.28: Performance Indicator values for all the settlement patterns

1) -

3) -

1) - 1) -

Settlement

Pattern Ratio Rating ofAverage Numeric Insolation (0 Rating ofAverage Numeric Overshadowing(0 Percentage Rating ofAverage Numeric Wind Velocity (0 Indicator Performance (0 Dandaka 1:1 0.35 0.45 0.34 1.15 1.5:1 0.36 0.46 0.41 1.22 2:1 0.33 0.46 0.39 1.18 Sarvatobhadra 1:1 0.38 0.49 0.39 1.26 1.5:1 0.35 0.49 0.27 1.10 2:1 0.39 0.49 0.23 1.11 Nandyavarta 1:1 0.37 0.51 0.46 1.33 1.5:1 N/A N/A N/A N/A 2:1 N/A N/A N/A N/A Swastika 1:1 0.37 0.47 0.29 1.13 1.5:1 0.39 0.49 0.41 1.29 2:1 0.38 0.49 0.40 1.27 Prastara 1:1 0.38 0.49 0.37 1.24 1.5:1 0.38 0.48 0.36 1.22 2:1 0.35 0.48 0.36 1.19 Table 3.27 shows that with a performance indiacator value of 1.33 in a scale of 0-3, the highest performing settlement pattern is Nandyavarta (1:1), even though the results are quite close. Table 3.29 shows the settlement patterns in descending order based on their respective performance indicator values.

174

Table: 3.29: Settlement patterns in descending order based on performance indicator values

Settlement Pattern Performance Indicator (0-3) Nandyavarta (1:1) 1.33 Swastika (1.5:1) 1.29 Swastika (2:1) 1.27 Sarvatobhadra (1:1) 1.26 Prastara (1:1) 1.24 Dandaka (1.5:1) 1.22 Prastara (1.5:1) 1.22 Prastara (2:1) 1.19 Dandaka (2:1) 1.18 Dandaka (1:1) 1.15 Swastika (1:1) 1.13 Sarvatobhadra (2:1) 1.11 Sarvatobhadra (1.5:1) 1.10 Nandyavarta (1.5:1) N/A Nandyavarta (2:1) N/A

3.14 Causal-comparative analysis

In this section, the performance indicator values of the dependent variables has been discussed against the independent variables. Among the independent variables, the parameters of morphological dimension of urban design are length to width ratio, cadastral pattern and plot pattern. The built environment parameters that has been considered are built to unbuilt ratio and height to width ratio. All these parameters were essential for generating the settlement patterns and three dimensional built environments. However, the cumulative outcome of the dependent variables of just four types of streets for a specific quarter do not present sufficient data to evaluate the effects of all the independent variables. Evaluating parameters like length to width ratio, built to unbuilt ratio and height to width ratio will require broader spectrum of sample to come to a conclusion. This section thus discusses the outcome against cadastral pattern and height to width ratio of the streets as they are directly related with the dependent variables. As this research has followed an experimental method, other variables has been considered to be constant.

175

3.14.1 Cadastral pattern and orientation

From table 3.28 we can see that Nandyavarta (1:1), Swastika (1.5:1) and Swastika (2:1) have the first three ranks among all the patterns. These three diagrams are different from the other diagrams in terms of cadastral pattern in a sense that all these diagrams do not have simple orthogonal layout of Rajapathas (RP) and Vamanapathas (VP), which crisscross with each other to create evenly distributed and equal sized urban plots. The RPs and VPs in these patterns have compound system of plots arranged following alternative cardinal axes. However, this type of cadastral system cannot be conclusively said to be superior to others without holistic research. Also, Swastika (1:1) has a lower PI value compared to its counterparts, which indicates that the PI is also depended on the length to width ratio of the settlement which governs the length of the streets and size of the plots. Although, the PI score for same settlement with different length to width ratio varies, this research does not find a direct relationship with this variables within its limitation.

This research has the scope to evaluate the effect of orientation of the streets. The Performance Indicator values of the east-west elongated streets (BrV and RP) and the north-south elongated streets (MhV and VP) have been shown in table 3.30.

The data from table 3.30 have been shown in figure 3.37 in the form of bar chart. From this figure, we can see that the north-south elongated streets outperforms the east-west elongated streets by twice the value of performance index in case of all the patterns. The data from the table 3.30 also shows that the north-south elongated streets have higher indicator value in terms of every three dependent variables. Specifically, in terms of wind velocity, the east-west elongated streets has significantly lower value. Therefore, as an outcome of this research it can be stated that with the given parameters in the Vedic treaties, the Mahakalavithi and the Vamanapathas performs higher in terms of outdoor comfort than the Brahmavithi and the Rajapathas.

176

Table 3.30: Comparison between north-south and east-west oriented streets

BrV+RP MhV+VP

1) 1) - - 3) 3) - -

1) 1)

- - 1) 1) - -

Settlement

Pattern Ratio Insolation (0 Insolation (0 Wind Velocity Wind(0 Velocity Wind(0 Velocity Average Numeric Rating ofAverage Numeric Rating ofAverage Numeric Rating ofAverage Numeric Rating ofAverage Numeric Rating ofAverage Numeric Rating ofAverage Numeric Performance Indicator (0 Performance Indicator (0 Overshadowing Percentage Overshadowing(0 Percentage Overshadowing(0 Percentage 1:1 0.27 0.36 0.09 0.71 0.44 0.55 0.60 1.59 Dandaka 1.5:1 0.24 0.37 0.03 0.65 0.48 0.55 0.78 1.80 2:1 0.19 0.38 0.05 0.62 0.46 0.55 0.73 1.74 1:1 0.24 0.38 0.05 0.67 0.52 0.60 0.72 1.84 Sarvatobhadra 1.5:1 0.23 0.38 0.05 0.67 0.47 0.59 0.48 1.54 2:1 0.28 0.39 0.07 0.73 0.51 0.58 0.40 1.49 1:1 0.22 0.41 0.07 0.69 0.52 0.60 0.84 1.97 Nandyavarta 1.5:1 N/A N/A N/A N/A N/A N/A N/A N/A 2:1 N/A N/A N/A N/A N/A N/A N/A N/A 1:1 0.25 0.36 0.07 0.68 0.49 0.58 0.52 1.59 Swastika 1.5:1 0.29 0.38 0.09 0.75 0.49 0.60 0.74 1.83 2:1 0.31 0.39 0.07 0.76 0.45 0.59 0.72 1.77 1:1 0.27 0.38 0.07 0.71 0.49 0.59 0.67 1.76 Prastara 1.5:1 0.23 0.38 0.07 0.68 0.53 0.58 0.65 1.76 2:1 0.20 0.39 0.05 0.64 0.50 0.58 0.67 1.75

2.00 1.50 1.00 0.50

0.00 Dandaka1:1 Dandaka1.5:1 Dandaka2:1 Sarvatobhadra1:1 Sarvatobhadra Sarvatobhadra2:1 Nandyavarta 1:1 Swastika 1:1 Swastika 1.5:1 Swastika 2:1 Prastara 1:1 Prastara 1.5:1 Prastara 2:1 1.5:1

BrV+RP MhV+VP

Figure 3.37: Comparison between east-west (BrV and RP) and north-south (MhV and VP) oriented streets

177

3.14.2 Height to width ratio

Since the Brahmavithis and Mahakalapathas for all the diagrams have similar height to width ratio, these streets were not consider for this analysis. The Rajapathas and Vamanapathas has varied height to width ratios. The PI value of the RPs and VPs along with their respective H/W ratio has been shown in table 3.31. Eliminating BrV and MhV from this analysis has provided scope for considering Nandyavarta (1.5:1) and Nandyavarta (2:1) to comparatively analyze with the other patterns.

Table 3.31: PI for RP and VP along with H/W ratio

3) 3) -

3) - (0

Settlement Pattern RP H/W of RP PI of(0 RP VP H/W of VP PI of(0 VP VP+RP Dandaka 1:1 SE-A 1.75 0.66 SE-1 1.5 1.58 1.12 Dandaka 1.5:1 SE-A 1.75 0.64 SE-2 1.5 1.77 1.21 Dandaka 2:1 SE-A 1.75 0.55 SE-3 1.5 1.65 1.10 Sarvatobhadra 1:1 SE-B 2.625 0.67 SE-2 2.625 1.87 1.27 Sarvatobhadra 1.5:1 SE-B 2.625 0.65 SE-2 2.625 1.29 0.97 Sarvatobhadra 2:1 SE-B 2.625 0.77 SE-2 2.625 1.20 0.99 Nandyavarta 1:1 SE-B 3 0.67 SE-2 2.625 1.92 1.29 Nandyavarta 1.5:1 SE-C 1.875 0.70 SE-4 1.875 1.94 1.32 Nandyavarta 2:1 SE-C 1.875 0.73 SE-4 1.875 1.79 1.26 Swastika 1:1 SE-A 1.825 0.70 SE-4 1.825 1.49 1.09 Swastika 1.5:1 SE-A 1.825 0.75 SE-4 1.825 1.88 1.31 Swastika 2:1 SE-A 1.825 0.79 SE-4 1.825 1.82 1.30 Prastara 1:1 SE-C 2.25 0.71 SE-2 2.625 1.73 1.22 Prastara 1.5:1 SE-C 2.25 0.65 SE-2 2.625 1.46 1.06 Prastara 2:1 SE-C 2.25 0.60 SE-2 2.625 1.67 1.13

From table 3.30, it is evident that the RP and VP with same height to width ratio have different PI value as score. This is due to the fact that streets with similar H/W ratio have different length due to the change in settlement pattern or length to width ratio. Length of the street is directly related to urban wind flow (Soulhac, 2008). Difference in plot pattern as well as amount of vertical surfaces can influence direct and particularly diffused insolation levels. Therefore, overshadowing percentage, which is directly depended on the H/W ratio of the streets has been considered to examine the

178 effects of this parameter. The calculation process of overshadowing percentage analysis considers the average value of complete street. Hence, the results are more comprehensive than the other two variables.

Table 3.32 (a) shows the Descending scale from highest to lowest PI value in a scale from 0-1 for Overshadowing Percentage of RP with H/W ratio. The data has also been plotted in figure 3.38 (a). The information shows that the PI value for overshadowing percentage has a direct relationship with the H/W ratio. Higher H/W ratio provides better shading condition.

Table 3.32(a): Descending scale from highest to lowest PI (0-1) for Overshadowing Percentage of RP with H/W ratio

Settlement Pattern Street H/W Ratio PI of OPRP (0-1) Nandyavarta 1:1 SE-B 3 0.43 Sarvatobhadra 1:1 SE-B 2.625 0.38 Sarvatobhadra 1.5:1 SE-B 2.625 0.38 Sarvatobhadra 2:1 SE-B 2.625 0.38 Prastara 1:1 SE-C 2.25 0.38 Prastara 1.5:1 SE-C 2.25 0.38 Prastara 2:1 SE-C 2.25 0.38 Nandyavarta 1.5:1 SE-C 1.875 0.37 Nandyavarta 2:1 SE-C 1.875 0.37 Swastika 2:1 SE-A 1.825 0.37 Dandaka 2:1 SE-A 1.75 0.36 Swastika 1:1 SE-A 1.825 0.36 Swastika 1.5:1 SE-A 1.825 0.36 Dandaka 1.5:1 SE-A 1.75 0.35 Dandaka 1:1 SE-A 1.75 0.33

179

3.5 3 2.5 2 1.5 1 0.5

0 Nandyavarta 1:1 Sarvatobhadra 1:1 Sarvatobhadra 1.5:1 Sarvatobhadra 2:1 Prastara 1:1 Prastara 1.5:1 Prastara 2:1 Nandyavarta 1.5:1 Nandyavarta 2:1 Swastika 2:1 Dandaka 2:1 Swastika 1:1 Swastika 1.5:1 Dandaka 1.5:1 Dandaka 1:1

H/W Ratio PI of OPRP (0-1)

Figure 3.38(a): Descending scale from highest to lowest PI (0-1) for Overshadowing Percentage of RP with H/W ratio

Table 3.32(b) and figure 3.38(b) showing similar information in case of RPs also provides the same result. The north-south oriented streets with higher H/W ratio will provide better shading condition.

Table 3.32(b): Descending scale from highest to lowest PI (0-1) for Overshadowing Percentage of VP with H/W ratio

Settlement Pattern Street H/W Ratio PI of OPVP (0-1) Nandyavarta 1:1 SE-2 2.625 0.43 Sarvatobhadra 1:1 SE-2 2.625 0.38 Sarvatobhadra 1.5:1 SE-2 2.625 0.38 Sarvatobhadra 2:1 SE-2 2.625 0.38 Prastara 1:1 SE-2 2.625 0.38 Prastara 1.5:1 SE-2 2.625 0.38 Prastara 2:1 SE-2 2.625 0.38 Nandyavarta 1.5:1 SE-4 1.875 0.37 Nandyavarta 2:1 SE-4 1.875 0.37 Swastika 2:1 SE-4 1.825 0.37 Dandaka 2:1 SE-3 1.5 0.36 Swastika 1:1 SE-4 1.825 0.36 Swastika 1.5:1 SE-4 1.825 0.36 Dandaka 1.5:1 SE-2 1.5 0.35 Dandaka 1:1 SE-1 1.5 0.33

180

3 2.5 2 1.5 1 0.5

H/W Ratio PI of OPVP (0-1)

Figure 3.38(b): Descending scale from highest to lowest PI (0-1) for Overshadowing Percentage of VP with H/W ratio

Therefore, it can be said that for both east-west and north-south oriented streets, higher H/W ratio can contribute better in terms of shading condition.

The cumulative PI value of RP and VP has been shown in order from highest to lowest in table 3.33 and figure 3.39. In terms of the performance of the secondary streets, Nandyavarta (1.5:1) scores highest. Again, four diagrams from Nandyavarta and Swastika makes the top.

Table 3.33: PI value of RP+VP in a scale of 0-3

Settlement Pattern PI of RP+ VP (0-3) Nandyavarta 1.5:1 1.32 Swastika 1.5:1 1.31 Swastika 2:1 1.30 Nandyavarta 1:1 1.29 Sarvatobhadra 1:1 1.27 Nandyavarta 2:1 1.26 Prastara 1:1 1.22 Dandaka 1.5:1 1.21 Prastara 2:1 1.13 Dandaka 1:1 1.12 Dandaka 2:1 1.10 Swastika 1:1 1.09 Prastara 1.5:1 1.06 Sarvatobhadra 2:1 0.99 Sarvatobhadra 1.5:1 0.97

181

PI of RP+ VP (0-3) 1.40 1.20 1.00 0.80 0.60 0.40 0.20 0.00 Nandyavarta 1.5:1 1.5:1 Swastika 2:1 Swastika Nandyavarta 1:1 Sarvatobhadra 1:1 Nandyavarta 2:1 Prastara 1:1 1.5:1 Dandaka Prastara 2:1 1:1 Dandaka 2:1 Dandaka 1:1 Swastika Prastara 1.5:1 Sarvatobhadra 2:1 Sarvatobhadra 1.5:1

Figure 3.39: PI value of VP and RP in order from highest to lowest

3.15 Summary

Referring to the objectives of this research this chapter has accomplished the followings:

Objective (a): The settlement patterns have been generated according to the Vedic instructions and the built-environment parameters have also been incorporated to create a scale scenario, from which the most connected streets has been selected by means of axial connectivity study for measuring environmental performance.

Objective (b): The environmental performances of the selected streets in terms of solar insolation, shadow condition and wind velocity have been measured using simulation tools.

Objective (c): In order to measure the environmental performance a performance indicator value has been derived in terms of all the dependent variables which has been used to analyse and compare the performance of the outdoor spaces (streets) of different settlements and also to correlate with the built-environment parameters.

182

References

A.G.S. (2000). Architectural Graphic Standards, John Wiley & Sons, Inc. New York, CD-ROM Version.

Ahmed, Z. N. (1987). The effect of climate on the design and location of windows for buildings in Bangladesh. Unpublished M.phill thesis. Sheffeld city polytechnic.

Climate (2018), [online], available at: http://bmd.gov.bd/ [accessed: 08 March, 2018]

Debnath, K.B., (2014), A Parametric Study of Biomimetic Design of Highrise Office Building Façades In View of Optimizing Natural Ventilation Potential in The Humid Tropics, Thesis (M. Arch). Department of Architecture, BUET, Dhaka.

Dettlaff, W., 2014. Space syntax analysis: Methodology of understanding the space. PhD Interdisciplinary Journal, pp.283-291.

Flow Design, (2014), Flow Design Preliminary Validation Brief, [online] available at:http://download.autodesk.com/us/flow_design/Flow_Design_Preliminary_Validatio n_Brief_01072014.pdf [accessed: 01 Januray, 2018]

Hillier, B. and J. Hanson (1984), The social logic of space, Cambridge University Press, Cambridge.

Joarder, M.A.R, Ahmed, Z.N., Price, A.D.F. and Mourshed M.M. (2009a). A Simulation Assessment of the Height of Light Shelves to Enhance Daylighting Quality in Tropical Office Buildings under Overcast Sky Conditions in Dhaka, Bangladesh. 11th International Building Performance Simulation Association Conference and Exhibition, 27-30 July (IBPSA, 2009), Glasgow, UK, pp. 1706-13.

Joarder, M.A.R, Ahmed, Z.N., Price, A.D.F., and Mourshed M.M. (2009c). Daylight Simulation for Sustainable Urban Office Building Design in Dhaka, Bangladesh: Decision-making for Internal Blind Configurations. 2nd International Conference on Whole Life Urban Sustainability and its Assessment, 22-24 April (SUE-MoT 2009), Loughborough, UK, pp. 218-41.

183

Joarder, M.A.R., (2007). A Study of Daylight Inclusion in Luminous Environment of Offices in Dhaka City, Thesis (M. Arch). Department of Architecture, BUET, Dhaka

Mohamad, W., Said, I., (2014), Visibility in Street Connectivity Analysis Using UCL Depthmap Version 10, South East Asia Technical University Consortium (SEATUC) Symposium, At M-Suites Hotel, Johor Bahru, Malaysia, Volume: 8

Rahman, A. (2007) Performance Evaluation of Shading Devices Used in Tall Office Buildings of Dhaka City, M.Arch Thesis (unpublished), Department of Architecture, BUET, Dhaka.

Turner, A., (2004), Depthmap 4 | A Researcher's Handbook", Bartlett School of Graduate Studies, UCL, London.

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Chapter 4 DISCUSSION AND CONCLUSION

185

4. Discussion and conclusion

4.1 Preamble

The previous chapter determined the environmental performance of the outdoor spaces by means of experimental method and calculated the performance by developing performance indicator values. This chapter will present the key observations of the research followed by a discussion about the importance and impact of streets as social spaces. Further discussion will be presented to evaluate the key observations against the environmental rationales stated in chapter 2. The chapter will also provide a statement for prospects for the future research.

4.2 Key observations

The methodology followed by this research has several limitations. The Vedic treaties had provided a generic guideline for a vast range of landscape in the Indian subcontinent in terms of environmental considerations, whereas this research has considered the climate of Dhaka as a base parameter. The dependent variables in this research were limited to solar insolation, shadow condition and wind flow, as these variables are perceivable through senses or sensual experience rather than by way of measuring through scientific standards. Defining thermal comfort in outdoor spaces has several other criteria to be considered, which includes air temperature, relative humidity and radiant temperature as environmental determinants. Only, the orthogonal settlement patterns with specific cardinal orientation have been taken into considerations as radial and omnidirectional diagrams do not provide any cardinal direction. Although, planting specific kinds of trees in the streets as well as the outdoor spaces had been an important considerations suggested in the Vedic treaties, this research did not take trees or plantations into accounts as the study considers the influence or impact of man-made built forms. Field data were only limited to specifying material properties and cadastral layouts, as the output variables were not possible to determine as conditions with the derived physical parameters do not exist at present. The research considered only four types of streets based on the connectivity values determined by axial connectivity study. Comprehensive results would have been derived if the scope is broadened. Also, the urban plots or blocks has been considered as solids to minimize the scale of simulation,

186 whereas the Vedic treaties proposed specific instruction regarding building bye-laws. Considering the plots as solids also rendered only the streets as the outdoor spaces. The wind flow simulation only considered the wind direction from south towards the north. The research did not consider the parameters of indoor thermal comfort. Therefore, the key findings evaluated the independent variables in terms of outdoor comfort. The simulations has been tested in only one quarter of the settlement pattern. Although the patterns are symmetric, different quarters may provide varied results. Given the above limitations, the following key observations can be made:

a) The value found in the previous chapter indicates that in terms of the environmental performance considering the parameters affecting outdoor comfort, i.e. insolation, shadow condition and wind flow in both isolated and comprehensive manner, the north-south elongated streets, which are the Mahakalavithi (MhV) and Vamanapatha (VP) are higher performing than the east-west elongated Brahmavithi (BrV) and Rajapatha (RP). b) In case of insolation analysis, southern part of the east-west elongated streets are more favorable to human comfort as this portion is less exposed to direct solar radiation and remains in shade during most of the sunshine hours in the hot-dry season and warm-humid season. In case of north-south elongated streets, the both the eastern and southern part of the streets remain in shadow for a significant time during the daytime. Considering ‘Tropism’ and ‘Incident Solar Radiation’ as a behavioral and environmental determinant of thermal comfort respectively, a user will be less exposed to direct sun in these parts of the streets. c) The north-south elongated streets has a brief exposure to direct sun during the cool-dry season and also receives higher insolation. The east-west elongated streets has no solar exposure during the winter. Therefore, the north-south elongated streets invites the direct sun which can be considered to be positive given that in winter, direct exposure can induce the feeling of comfort. d) No apparent relation exists between the depth of a settlement and its environmental performance based on this research. The performance indicator values of the dependent variables both in cumulative and individual manner derived from this research shows no distinct effect of length to width ratio.

187

e) The diagrams with varied cadastral and plot pattern, such as Nandyavarta and Swastika outperforms the diagrams with regular orthogonal pattern like Sarvatobhadra, Prastara and Dandaka. Nandyavarta and Swastika have less continuous streets and plots of varied size elongated along both the cardinal axes. Unlike the others, the streets tend to end hit a block rather than being continued throughout the entire plan. The layout of Sarvatobhadra, Prastara and Dandaka has continuous streets along both axes intersecting with each other resulting in symmetric and equal sized plots. However, since the east-west streets are found to be more exposed to direct sun in terms of radiation and shadow and also susceptible to lower velocity of wind, the SW quarter for the diagram Swastika may not get as much performance indicator score as the SE quarter of the diagram has three RPs and only one VP. In that sense, Nandyavarta can be said to be diverse and higher performing in terms of outdoor comfort. f) The fine-grained cadastral patterns have been observed to have more avenues for winds to pass through than the coarse-grained ones. Also, the more connected RPs and VPs of fine-grained cadastral patterns have been found to score higher than the coarse-grained pattern. g) The outcome of the simulation results can directly relate the environmental performance with the height to width ratio. The level of urban canopy has been found to govern the environmental performance directly related to solar exposure.

A matrix of performance score for all the dependent variables in case of every street for each diagram individualy and cumulative manner has been expressed in terms of percentage along with respective independent variables in figure 4.1.

The findings can be further complemented with the remarks from a research paper titled ‘Effect of Street Morphology on Microclimate in Residential Areas Following FAR Rule in Dhaka City’ authored by Syed Abu Sufian Kushol, Dr. K. Shabbir Ahmed, Mohataz Hossain and Iftekhar Rahman. The paper observed that the north-south elongated canyons are cooler than the east-west elongated canyons. Higher H/W ratio is preferable for north-south elongated streets in terms of wind flow and lower H/W

188

Figure 4.1(a): Matrix of individual and cumulative percentage score of Solar Insolation, Overshadowing Percentage and Wind velocity of every street for the diagram Dandaka along with H/W ratio, orientation of streest and length to width ratio of settlement

189

Figure 4.1(b): Matrix of individual and cumulative percentage score of Solar Insolation, Overshadowing Percentage and Wind velocity of every street for the diagram Sarvatobhadra along with H/W ratio, orientation of streest and length to width ratio of settlement

190

Figure 4.1(c): Matrix of individual and cumulative percentage score of Solar Insolation, Overshadowing Percentage and Wind velocity of every street for the diagram Nandyavarta along with H/W ratio, orientation of streest and length to width ratio of settlement

191

Figure 4.1(d): Matrix of individual and cumulative percentage score of Solar Insolation, Overshadowing Percentage and Wind velocity of every street for the diagram Swastika along with H/W ratio, orientation of streest and length to width ratio of settlement

192

Figure 4.1(e): Matrix of individual and cumulative percentage score of Solar Insolation, Overshadowing Percentage and Wind velocity of every street for the diagram Prastara along with H/W ratio, orientation of streest and length to width ratio of settlement

193 ratio may induce wind velocity in the east-west elongated streets. The east-west elongated streets require further shading by means of plantation (Kushol et al., 2013). However, the paper suggests the north-south elongated streets to be continuous whereas, in this research, the diagrams with staggered north-south elongated streets are found to score higher than the others.

4.3 Evaluation of environmental rationales

The Vedic treaties described the planning strategies considering sun, rain and wind as the principle climatic features. These are the natural forces that are observable by human experience. The directives of the scriptures clearly stated the importance of solar exposure for the streets in the morning, especially the east-west elongated ones but also provided instructions for limiting too much exposure for minimizing the solar radiation.

The Shilpa Shastras’ descriptions regarding site selection were mentioned in terms of the sites slopes and angle of the sun. The books prescribed to provide declivity towards the east or north, whereas declivity towards the south and west are discouraged. This statement indicates that during the hot-dry and warm-humid seasons, when the altitude of the sun is high with small zenith angle, the site tilted towards the south will receive higher intensity of solar radiation than a horizontally levelled site. The same goes for the declination towards the west as the solar exposure will be greater from a levelled site during the noon and the afternoon during the hottest hours of the day. This research already showed that during the hot-dry season, the performance of the BrVs and RPs are lower in terms of comfort as they have significantly low overshadowing percentage with a horizontal site. If the site were tilted towards the south, these streets would have got lower shaded areas than the given scenario. The morning sun was welcomed for having lower intensive radiation and religious reasons as well. The building bye-laws also instructed to provide smaller windows on the southern façade to minimize solar radiation within the interior. Again, locating the settlement to the west of a mountain is prohibited as it will eliminate the morning sun.

The Vedic experts were well aware of the wind flow pattern throughout the year. The scriptures sayed about the wind flow from south and west during the summer and from the north during the winter. Surprisingly, wind flow from both south and north directions, had not been encouraged to be entered in the interior. The civic architects

194 were more concerned about the air-borne epidemic during the hot-dry and cool-dry seasons. This decision had impacted the building bye-laws. The buildings were instructed not to provide any windows on the façade adjacent to the streets, although this directive was later being limited to the ground floor. The upper floors were permitted to have small windows. However, the major openings were instructed to be provided in the inner courts. This tradition can be traced even in the cities of Indus- valley civilization (Ching et al., 2011). The buildings of a settlements were thus conceived as an introvert element. The disregard for indoor ventilation also indicates that people in Vedic era spent most of their time in the outdoors. Also, slope towards the south and west was discouraged as these are the major directions of rain and storm in the subcontinent. The ‘Padavinyasa’ also associates ‘south’ with the deity ‘Yama’ representing death.

Within the outdoors, the north-south oriented streets (MhVs and VPs) were found to have sufficient air flow during the hot-dry and hot-humid season when the wind flows from south to north for most of the time. The streets also showed efficiency in terms of insolation and overshadowing percentage. Now, as a policy or scheme, the Vedic treaties suggested to expand a settlement along the Brahmavithi and favorably towards the east (Dutt, 1925). This expansion scheme thus means that the number of north-south oriented streets will increase. Therefore, it can be stated as a hypothesis that, the Vedic architects were aware of the performance of the north-south streets as public or social spaces and thus encouraged to increase the number of these streets in case of future growth.

Given the above scenario, this research can state that the Vedic civic architects had deep understanding of the effect of climate and natural forces over the built environment. The effects of built environment for different design decisions are described in metaphors. Such as: ‘A southern declivity increases insanitation and brings about diseases; declivity towards north increases wealth; slope towards west is detrimental to peace and prosperity’.

As stated earlier, the streets were suggested to be adorned with specific trees. The city of Jaipur, being a capital had principle streets in both axes with greater width with lower height to width ratio resulting in scope for higher insolation and lower shaded areas.

195

The commercial activities along the streets were located within a colonnaded arcade to provide shade. The arcades and trees can play significant role for augmenting thermal comfort in the outdoor spaces (Ahmed, 1996).

Apart from these passive means of design, the Vedic architects had shown sensitivity for addressing drainage and public service facilities.

Figure 4.2: Shaded Arcades in Jaipur

In his treaties Vitruvius suggested the settlement patterns in the shape of polygon with radial cadastral pattern. The variety of patterns were not as vast as the Vedic ones. The scriptures also did not emphasize the outdoor activity of the citizens, whereas the Vedic treaties provided elaborate and specific characteristics of the streets and type of activity they can house within themselves. The Vedic villages were also considered as modules which can be used to expand the settlements by repetition. This method was again found to be adopted by the modern architects. This intelligent feature is also absent in the book of Vitruvius. Climatic features had been addressed by Vitruvius in terms of heat and wind.

A surprisingly common phenomenon in both kinds of architectural treaties from the east and the west is that the wind flow is not accepted in the interior although the streets were found to be laid out to favor the winds to pass through. The ancient architects in both the region were concerned about the air-borne diseases. But favoring wind flow in the outdoor spaces had been patronized perhaps to ensure comfort. All these leads to a more pressing question: whether the ancient designers consciously encouraged to spent time in the outdoors for well-being of the people in compact settlements?

196

4.4 Suggestion for future research

This research can be extended towards broader spectrum to include a number of areas for future exploration. Some of them are mentioned as follows:

a) This research considered the urban plots or blocks to be solids. The behavior of these plots associated with the building bye-laws can be further investigated to find out the environmental consideration at neighborhood and dwelling level. b) The environmental performance can further include the other variables of thermal comfort like air temperature, relative humidity, mean radiant temperature etc. c) The same methodology may be conducted in different geographic context to evaluate the environmental performance of the settlement patterns for that context. d) The omnidirectional settlement patterns with radial cadastral layout needs to be examined. e) Usually in an archaeological site, the capital web remains prominent within the ruins. The cadastral pattern and the bases of built forms are generally the first among the discoveries. Recently found settlements in Bhitargarh and Vikrampura may be analyzed in the light of the morphological considerations of Vedic treaties as the principles had long been practiced in this region. The settlements found in Wari-Bateshwar, Bhitargarh and Vikrampura already reveals the traces of orthogonal cadastral pattern and fortified boundaries. f) Further research may be conducted with a broader spectrum of variables. The range may include the relationship between spatial quality and zoning in the light of cultural paradigms, anthropological dimensions, religious beliefs, cosmological reasoning etc.

4.5 Conclusion

From literature review it is evident that the streets in Vedic India had been considered as public spaces. Both internal and inland commercial activity has been promoted to be taken place in the streets. The Brahmavithi and Mahakalavithi had been prescribed to be used for inland and internal trade respectively. The pedestrian street with small shops

197 had been specifically termed as Vithi. The pedestrian street has a specific term called Padya. These categorization clearly indicated that the streets in Vedic villages were considered as an amalgamated form of ‘movement space’ and ‘social space’ as defined by Carmona.

This research has dealt with the environmental variables that can be perceived directly with the senses and the findings showed a conscious design consideration in terms of outdoor comfort. The planning guideline and the building bye-laws played a significant role for determining the physical parameters of outdoor spaces or more specifically the streets. These parameters has defined that for streets elongated in cardinal axes, north- south elongated streets is favorable for outdoor comfort. The treaties also suggested the Mahakalavithi, which is the principle street elongated in north-south axis to be used for trade and commerce within the settlement. The results already reflected that this street had performed well in terms of outdoor comfort. Besides, the Rajapathas and the Vamanapathas selected by this research were the highest connected streets, which means these streets had better possibilities to house commercial activities in the outdoor spaces. This research with further refinement can thus contribute to identify the use of a street as well as the built forms through spatial and environmental rationale in case of an ancient ruin.

The outdoor spaces were compensated for thermal comfort by providing trees with large foliage and colonnaded arcades in later period for providing shade which is clear understanding of ‘Tropism’. By means of empirical knowledge, the civic architects tried to consider the environmental parameters without any standard for making the outdoor space to be used as an element of the public realm.

Whether the ancient architects made conscious decision to make the settlements compact keeping this is mind is a matter of further investigation. It is possible that the compactness of settlements had been introduced to minimize cost, footprint and defense but it may had contributed to the salubrity of the settlements.

198

References

Kushol, S.A., Ahmed, K.S., Hossain, M., Ahmed, I., (2013), Effect of Street Morphology on Microclimate in Residential Areas Following FAR Rule in Dhaka City, PLEA 2013 - 29th Conference, Sustainable Architecture for a Renewable Future, Munich, Germany.

Ching D. K., Jarzombek, M., Prakash V., (2011), A Global History of Architecture, John Wiley & Sons Inc.

Dutt, B. B., (1925), Town Planning in Ancient India, New Asian publishers.

]

199

Appendix A Axial connectivity analysis results

200

Appendix A1 Axial connectivity analysis results for Dandaka

1:1

1.5:1 LengthWidthto Ratio

2:1

201

Appendix A2 Axial connectivity analysis results for Sarvatobhadra

1:1

1.5:1 LengthWidthto Ratio

2:1

202

Appendix A3 Axial connectivity analysis results for Nandyavarta

1:1

1.5:1 LengthWidthto Ratio

2:1

203

Appendix A4 Axial connectivity analysis results for Swastika

1:1

1.5:1 LengthWidthto Ratio

2:1

204

Appendix A5 Axial connectivity analysis results for Prastara

1:1

1.5:1 LengthWidthto Ratio

2:1

205

Appendix B Insolation analysis results

206

Appendix B1.1 Insolation Analysis Results for Dandaka

Days

th st nd

4 April 21 June 22 December

1:1

1.5:1 Length to width ratio

2:1

207

Appendix B1.2 Insolation Analysis Results for Sarvatobhadra

Days

th st nd

4 April 21 June 22 December

1:1

1.5:1 Length to width ratio

2:1

208

Appendix B1.3 Insolation Analysis Results for Nandyavarta

Days

th st nd

4 April 21 June 22 December

1:1

width ratio 1.5:1 Length to

2:1

209

Appendix B1.4 Insolation Analysis Results for Swastika

Days

th st nd

4 April 21 June 22 December

1:1

1.5:1 Length to width ratio

2:1

210

Appendix B1.5 Insolation Analysis Results for Prastara

Days

th st nd

4 April 21 June 22 December

1:1

1.5:1 Length to width ratio

2:1

211

Appendix B2.1 Insolation analysis results for streets of Dandaka (1:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

A) -

RP (SE

1) - VP (SE

212

Appendix B2.2 Insolation analysis results for streets of Dandaka (1.5:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

A) -

RP (SE

1) - VP (SE

213

Appendix B2.3 Insolation analysis results for streets of Dandaka (2:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

A) -

RP (SE

1) - VP (SE

214

Appendix B2.4 Insolation analysis results for streets of Sarvatobhadra (1:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) B -

RP (SE

) 2 - VP (SE

215

Appendix B2.5 Insolation analysis results for streets of Sarvatobhadra (1.5:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) B -

RP (SE

) 2 - VP (SE

216

Appendix B2.6 Insolation analysis results for streets of Sarvatobhadra (2:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) B -

RP (SE

) 2 - VP (SE

217

Appendix B2.7 Insolation analysis results for streets of Nandyavarta (1:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) B -

RP (SE

) 2 - VP (SE

218

Appendix B2.8 Insolation analysis results for streets of Nandyavarta (1.5:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

Street

) C -

RP (SE

) 4 - VP (SE

219

Appendix B2.9 Insolation analysis results for streets of Nandyavarta (2:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

Street

) C -

RP (SE

) 4 - VP (SE

220

Appendix B2.10 Insolation analysis results for streets of Swastika (1:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) A -

RP (SE

) 4 - VP (SE

221

Appendix B2.11 Insolation analysis results for streets of Swastika (1.5:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) A -

RP (SE

) 4 - VP (SE

222

Appendix B2.12 Insolation analysis results for streets of Swastika (2:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) A -

RP (SE

) 4 - VP (SE

223

Appendix B2.13 Insolation analysis results for streets of Prastara (1:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) C -

RP (SE

) 2 - VP (SE

224

Appendix B2.14 Insolation analysis results for streets of Prastara (1.5:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) C -

RP (SE

) 2 - VP (SE

225

Appendix B2.15 Insolation analysis results for streets of Prastara (2:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) C -

RP (SE

) 2 - VP (SE

226

Appendix C

Stereographic diagrams of overshadowing percentage calculation results

227

Appendix C1 Insolation analysis results of Dandaka (1:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) A - RP (SE

) 1 - VP (SE

228

Appendix C2 Overshadowing Percentage Calculation Results for the streets of Dandaka (1.5:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) A - RP (SE

) 1 - VP (SE

229

Appendix C3 Overshadowing Percentage Calculation Results for the streets of Dandaka (2:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) A - RP (SE

) 1 - VP (SE

230

Appendix C4 Overshadowing Percentage Calculation Results for the streets of Sarvatobhadra (1:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) B - RP (SE

) 2 - VP (SE

231

Appendix C5 Overshadowing Percentage Calculation Results for the streets of Sarvatobhadra (1.5:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) B - RP (SE

) 2 - VP (SE

232

Appendix C6 Overshadowing Percentage Calculation Results for the streets of Sarvatobhadra (2:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) B - RP (SE

) 2 - VP (SE

233

Appendix C7 Overshadowing Percentage Calculation Results for the streets of Nandyavarta (1:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) B - RP (SE

) 2 - VP (SE

234

Appendix C8 Overshadowing Percentage Calculation Results for the streets of Nandyavarta (1.5:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

) C - Street RP (SE

) 4 - VP (SE

235

Appendix C9 Overshadowing Percentage Calculation Results for the streets of Nandyavarta (2:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

) C - Street RP (SE

) 4 - VP (SE

236

Appendix C10 Overshadowing Percentage Calculation Results for the streets of Swastika (1:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) A - RP (SE

) 4 - VP (SE

237

Appendix C11 Overshadowing Percentage Calculation Results for the streets of Swastika (1.5:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) A - RP (SE

) 4 - VP (SE

238

Appendix C12 Overshadowing Percentage Calculation Results for the streets of Swastika (2:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) A - RP (SE

) 4 - VP (SE

239

Appendix C13 Overshadowing Percentage Calculation Results for the streets of Prastara (1:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) C - RP (SE

) 2 - VP (SE

240

Appendix C14 Overshadowing Percentage Calculation Results for the streets of Prastara (1.5:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) C - RP (SE

) 2 - VP (SE

241

Appendix C15 Overshadowing Percentage Calculation Results for the streets of Prastara (2:1)

Length to Width Ratio

th st nd

4 April 21 June 22 December

BrV

MhV

Street

) C - RP (SE

) 2 - VP (SE

242