Land Use and Land Cover Change-Induced Landscape Dynamics: a Geospatial Study of Durgapur Sub-Division, West Bengal (India) Sribas Patra*, Kapil Kumar Gavsker
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Original Article 79 Land use and land cover change-induced landscape dynamics: a geospatial study of Durgapur Sub-Division, West Bengal (India) Sribas Patra*, Kapil Kumar Gavsker Ravenshaw University, School of Regional Studies and Earth Sciences, Department of Applied Geography, India * Corresponding author: [email protected] ABSTRACT This article examines the factors and process of change in the land use and land cover change-induced landscape dynamics in the Durgapur Sub-Division region of West Bengal in 1989, 2003, and 2018 by employing the satellite imageries of Landsat 5 (1989 and 2003) and Landsat 8 (2018). The images of the study area were categorized into seven specific land use classes with the help of Google Earth Pro. Based on the supervised classification methodology, the change detection analysis identified a significant increase in built-up land from 11% to 23% between 1989 and 2003 and from 23% to 29% in 2003 and 2018. The areas under fallow land and vegetation cover have mainly decreased, while the areas of industrial activities and urbanization expanded during the study period. KEYWORDS change detection; geospatial; landscape dynamics; land use and land cover Received: 18 May 2020 Accepted: 6 January 2021 Published online: 8 March 2021 Patra, S., Gavsker, K. K. (2021): Land use and land cover change-induced landscape dynamics: a geospatial study of Durgapur Sub- Division, West Bengal (India). AUC Geographica 56(1), 79–94 https://doi.org/10.14712/23361980.2021.3 © 2021 The Authors. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0). 80 Sribas Patra, Kapil Kumar Gavsker 1. Introduction to decision-making of ecological management and environmental planning for future (Zhao et al. 2004; Dwivedi et al. 2005; Erle and Pontius 2007; Fan et al. changes caused by various factors and processes 2007). The accurate and timely land use and land cov- occurringLandscape thereon. of a region Almo is subject Farina tostates modifications that “[L]and and- er maps derived from remotely sensed images are the scape dynamics involve properties of the landscape, keys for monitoring and quantifying various aspects such as stability, persistence, resistance, resilience, of global and local climate changes, hydrology, biodi- and recovery, that operate along a broad range of versity conservation, and air pollution (Sellers et al. temporal and spatial scales, such as shifting mosa- 1995; Bonan 2008; Butchart et al. 2010; Schröter et ic steady-state, and equilibrium spatial properties” al. 2010). Remote Sensing (RS) and Geographic Infor- (Oxford Bibliographies 2017). Studying earth’s sur- mation System (GIS) are now providing new tools for face and environment has been one of the central advanced ecosystem management. The collection of themes of geographical research. Dynamics in land- remotely sensed data facilitates the synoptic analyses scape indicate to the fact that any land is not static of Earth – system function, patterning, and change at forever; rather it is changeable at different scale and local, regional and global scales over time; such data pace. Similarly, surface of the earth has been changing also provide an important link between intensive, since its origin. Various types of external and inter- localized ecological research and regional, national nal factors play their role in such a change. The land- and international conservation and management of scapes include the numerous features on the earth biological diversity (Wilkie and Finn 1996). like forest land, water bodies, built-upland (all type of settlements, roads etc.), agricultural lands etc. Land use and land cover are two separate terminol- 2. Objectives ogies which are often used interchangeably (Dimyati et al. 1996). In particular, land use and land cover (LULC) The present study addresses the following major changes in tropical regions are of major concern due to objectives: i) To study land use and land cover chang- the widespread and rapid changes in the distribution es and their impact on landscape dynamics in the Dur- and characteristics of tropical forests (Myers 1993; gapur Sub-Division by comparing three-time period Houghton 1994). However, changes in land cover and of year 1989, 2003, and 2018; and ii) To examine and in the way people use the land have become recog- detect factors of change of land use and land cover nized over the last 15 years as important global envi- during study period and resulting conditions in the ronmental changes in their own right (Turner 2002). Durgapur Sub-Division. Recent research on land use and land cover change detection has drawn attention of many researchers (Liang et al. 2002; Ayele et al. 2016). Change detection 3. Study Area monitoring natural resources and urban development The study area of Durgapur Sub-Division lies in the mainlyhas emerged due to as provision a significant of processquantitative in managing analysis and of eastern part of the Paschim Barddhaman District of the spatial distribution of the population of interest. West Bengal (shown in Figure 1). It is lies between There are a lot of available techniques that serve pur- 23°26′ N to 23°48′ N and 87°8′ E to 87°32′ E. The area pose of detecting and recording differences and might of Durgapur Sub-Division is 771.28 km2. The total also be attributable to change (Singh 1989; Yuan et population of the region is 1,209,372 as per the Cen- al. 1999). sus of India 2011. In this area the major city is Dur- The land use and land cover changes play an gapur. This is an industrial city of eastern India and important role in the study and analysis of glob- the second planned city (1955) of India after Chan- al changed scenario today as the data available on digarh. It consists of four Community Development such changes is essential for providing critical input Blocks: Durgapur–Faridpur; Kanksa; Andal; and Tab. 1 Showing administrative units and demographic profile of Durgapur Sub-Division. Panchayat Region C.D. Bock / M.C. Mouzas Inhabited Village Population Samity Gram Gram Sansad Andal 1 8 146 14 12 186,915 Faridpur-Durgapur 1 6 88 54 48 115,924 Durgapur Pndabeswar 1 6 112 17 14 161,891 Sub-Division Kanksa 1 7 132 86 77 178,125 Durgapur (MC) – – – – – 566,517 Source: http://www.sdodurgapur.org/blocks.php; and Census of India, 2011. Land use and land cover change-induced landscape dynamics 81 Fig 1 Location map of the study area. Pandabeswar and a Durgapur Municipal Corporation satellite imageries and data sensors used in the pres- as shown in the Table 1. In Durgapur Subdivision, ent research. Durgapur Municipal Corporation is the only statutory The matter of the fact is that remote sensing plat- urban area that comes within the ambit of the Asan- forms is a system used for collecting and analyzing sol-Durgapur Planning Area (ADPA). space features. It includes space-borne (satellite imagery), air-borne (aerial photographs, thermal, radar images, etc.) and ground-based techniques 4. Material and Methods The present study is based on a secondary source of as tools for the location and identification of the database. The research database here involves the use Tab. 2 Showing data types and sources for the study. of various methods, techniques and tools for the study Category Data type Data source Time period of land use and land cover to make a wider sense of 1989, 2003, Satellite data USGS landscape dynamics of the region. Geographic Infor- 2018 mation System and Remote Sensing tools are used to Spatial Administrative Durgapur 2018 collect, organize and analyze the spatial data. Remote map Sub-division website Sensing has greatly opened new vistas in deriving District Census factual information on natural and human resources Secondary Handbook, Statistical 2011 by virtue of its synoptic overview, multi-spectral and A-series – General multi-temporal coverage of the earth’s surface. The Attribute Population Table Table 2 and Table 3 show the types of data, sources, Source: Prepared by the authors, 2019. 82 Sribas Patra, Kapil Kumar Gavsker Tab. 3 Showing satellites and sensors data acquired for the present less controlled by the analyst. In this process, the ana- study. lyst selects training pixels that are representative of Sl. No Satellite Sensor Date the desired land use classes. In the present study, for each class around 40 training samples are taken into 1 LANDSAT 5 Thematic Mapper (TM) Dec 17, 1989 account. SPSS 22 is also used for analysis particularly 2 LANNDSAT 5 TM Nov 15, 2003 3 LANDSAT 8 OLI-TIRS Nov 18, 2018 and Multiple Linear Regression to understand the Source: Prepared by the authors, 2019. relationshipPearson’s product-moment among the classes. correlation coefficient (r) ( ) ( )( ) = (1) [ ( ) ][ ( ) ] biological, ecological and cultural characteristics of ∑ ∑ ∑ various features of the earth surface. In order to iden- ∑ ∑ ∑ ∑ tify the spatial pattern and the rate of change, it all yi = β0 + β1xi1 + β2xi2 + … +βpxip + ϵ (2) requires data analysis over a considerable time period or of sometime junctures. For data analysis purpose where, for i = n observations, the important software and tools used in the study yi = dependent variable, include ARC-GIS and ERDAS imagine 14. The ARC- xi = expanatory variables, GIS software is used to complement the display and β0 = y-intercept (constant term), processing of the acquired data. The ERDAS Imagine βp 14 is used for ‘image processing’ (layer stack, subset, variable, - ϵ = =the slope model’s coefficients error term for (also each known explanatory as the cy purposes of satellite images used in the research, residuals). theclassification) Google Earth purpose. system Foralso verification has been very and useful accura in the present study. Through this, images are used for land cover categories and their properties are provid- adopted in the present study for a detailed analysis ed Thein the description below given of Tableclassified 4.