Effect of Land Use Land Cover Changes on Farmers Income in Farta Woreda, North Westethiopa

DSpace Institution DSpace Repository http://dspace.org

Environment and climate change Thesis and Dissertations

2020-12-25 EFFECT OF LAND USE LAND COVER CHANGES ON FARMERS INCOME IN FARTA WOREDA, NORTH WESTETHIOPA

Mesfin Abebaw http://hdl.handle.net/123456789/11790 Downloaded from DSpace Repository, DSpace Institution's institutional repository

BAHIR DAR UNIVERSITY COLLEGE OF AGRICUTLURE AND ENVIRONMENTAL SCIENCES DEPARTMENT OF NATURAL RESOURCE MANAGEMENT M.Sc. IN ENVIRONMENT AND CLIMATE CHANGE GRADUATE PROGRAM

EFFECT OF LAND USE LAND COVER CHANGES ON FARMERS INCOME IN FARTA WOREDA, NORTH WESTETHIOPA M.Sc. Thesis By Mesfin Abebaw SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE (M.Sc.) IN ENVIRONMENT AND CLIMATE CHANGE

July 2020 Bahir Dar, Ethiopia

BAHIR DAR UNIVERSITY COLLEGE OF AGRICUTLURE AND ENVIRONMENTAL SCIENCES DEPARTMENT OF NATURAL RESOURCE MANAGEMENT M.Sc. IN ENVIRONMENT AND CLIMATE CHANGE GRADUATE PROGRAM

July 2020 Bahir Dar, Ethiopia

THESIS APPROVAL SHEET

As member of the Broad of Examiners of the Master of Science (M.Sc.) thesis open defense examination .We have read and evaluated this thesis prepared by Mister Mesfin Abebaw Yalew entitled “Analysis of Land Use Land Cover Change on Farmers Income in Farta District, Ethiopia”. We hereby certify that, the thesis is accepted for fulfilling the requirements for the award of the degree of Master of Science (M.Sc.) in Environment and Climate Change.

Board of Examiner

------Name of External Examiner Signature Date

------Name of Internal Examiner Signature Date ------

Name of Chairman Signature Date

DECLARATION This is to certify that this thesis entitled “Analysis of Land Use Land Cover Change on Farmers Income in Farta District, Ethiopia “submitted in partial fulfillment of the requirements for the award of degree of Master of Science in Environment and Climate Change to Graduate Program of College of Agriculture and Environmental Sciences, BahirDar University my Mr Mesfin Abebew Yalew (ID BDU 1108010) is an automatic work carried out by him under our guidance. The matter embodied in this project work has not been submitted earlier for award of any degree or diploma to the best of our knowledge and belief.

Name of the Student

------

Signature &date------

Name of the Supervisors

1. ------(Major Supervisors)

Signature &date------

2. ………………………………………….Co. Supervisors)

Signature &date------

ACKNOWLEDGEMENT First, I would like to express my gratitude to my advisor, Mulatie Mekonnen (PhD) for his time and academic guidance throughout the entire period of this thesis and allowing me financial assistance of the Science Technology Information commination commission.

I am also pleased to extend my gratitude to my friends: farta kebele agricultural experts, Mr.Fenta, Mr. Dessie, Mr. Melaku, Mr.Belete, Miss Birkie and Miss Lideta Tilahun for their support, sharing their knowledge and motivating.

It requires much space to list all individuals who contributed, in one way or another, to the successful completion of my study. However, I am much indebted to acknowledge all of my classmates, my colleagues who were encouraging me while I got stress.

Finally, my appreciation goes to my family for their moral support throughout the study, and everybody who contributed in making this research work a success.

iii

DEDICATION This thesis is dedicated to my lovely father Ato Abebaw Yalew.

Dear Dadi, I am very thankful because I had a strong, wonderful and adorable father like you. You sacrificed all of your things to make me happy, strong and concerned in the walk of life. Even though you are not here by my side now, I know your soul and your blessing is always with me. This is all your result you should deserve a great credit for my presence here today.

ABBREVATION ANRS Amhara National Regional State ETB Ethiopian Birr CSA Central statistical Agency DEM Digital Elevation Model EHRS Ethiopian Highland Reclamation Study ERDAS Earth Resources Data Analysis System ETM+ Enhanced Thematic Mapper FAO Food and Agriculture organization GCP Ground control point GIS Geographic Information System GPS Global Positioning System

LULCC Land Use and Land Cover Change

MA Master of Art Sciences MLC Maximum Likelihood Classifier Mm Millimeter

MSS Multi Spectral Sensor

NRM Natural Resource Management

OLI/TIRS Operational Land Imager/Thermal Infrared Sensor

RS Remote Sensing

ABSTRACT

Land use/cover change dynamics influences many aspects of the natural environment. It’s shifting patterns as a component of many existing climate change problems has been gaining recognition as key cause and consequences of environmental problems and livelihood changes. This research was conducted in Amhara region located in the south Gondar zone specifically in Farta district to investigate the land use/cover changes between the years 1989-2019 and to assess the economic advantage of Eucalyptus globulus based land use in contrast to cropland and grazing land uses. In this study, both primary and secondary data collection methods were used. GPS was used for collecting ground control points, ArcGIS 10.3.1 for spatial analysis and mapping, ERDAS Imagine 2010 for land use classification and change detection, Satellite images of Landsat 8 for OLI 2019 and Landsat 5 TM for 1989 and 1999 Landsat 7 ETM 2009 were used to generate land use/cover maps by using Supervised Classification technique with Maximum Likelihood classifier. Total of 60 samples (20 cropland, 20 grazing land and 20 Eucalyptus globulus land) were taken to estimate the amount of production. The production amount of each land use was converted into Birr value for comparison purpose. The land use and land cover change study result showed that forest ,grazing, wetland and bare lands were declining by 6.71%, 3.68%, 1.98% &3.32%, respectively from1989-2019 years. Whereas plantation, cultivated land, water body, and settlement lands were expanding by 6.82%, 4.44%, 0.18% & 4.24%, respectively from1989-2019 years. From the observed changes plantation was the most increased land use/cover type by 6.82% (5663.3ha). The overall classification accuracies of this study for 1989, 1999, 2009 and 2019 were found to be 85.3%, 85.1%, 85.3%& 85.5%respectively. Total productivity and economic benefits of the three land use types (Eucalyptus globulus based land use, grazing land use and cropland use mainly cropped by wheat) were compared. The net benefit gained from Eucalyptus globulus based land was found to be higher and it gives extra 86,244ETBha-1yr-1to cropping & 106,158ETBha-1yr-1 compared to grazing lands .Therefore, Eucalyptus globulus significantly increase income 4.1% and14.57% fold greater than crop and grazing land system respectively. Based on land equivalent ratio value Eucalyptus globulus based land was 301% better than crop land use system. . Out of this study, it is concluded that Eucalyptus globulus production with in a five-year rotation time could benefit farmers in huge incomes. Keywords Eucalyptus globulus, land use change, wheat, Eucalyptus, pasture land use system

TABLE OF CONTENTS THESIS APPROVAL SHEET ...... i DECLARATION ...... ii ACKNOWLEDGEMENT ...... iii DEDICATION ...... iv ABBREVATION ...... v ABSTRACT ...... vi TABLEOFCONTENTS………………………………………………………………………vii LIST OF TABLE ...... viii LIST OF FIGURE ...... ix LIST OF APPENDIX ...... x CHAPTER ONE………………………………………………………………………………1 1. INTRODUCTION…………………………………………………………………………..1 1.1. Background and Justification...... …..1 1.2. Statement of the problem ...... - 3 - 1.3. OBJECTIVES OF THESTUDY…………………………………………………………….-4. 1.3.1 General Objective ………………………………………………………..- 4 - 1.3.2 Specific Objectives ...... - 4 - 1.4 Research Questions ...... - 4 - 1.5 Limitation of the Study ...... - 4 - 1.6 Scope of the Study ...... - 4 - 1.7 Organization of the thesis ...... - 5 - CHAPTER TWO……………………………………………………………………………- 6 - Literature Review…………………………………………………………………………..- 6 - 2.1. Land, Land use, and Land cover, definition…………………………………………………- 6 - 2.2. Land-use and land-cover (LULC) change ...... - 6 - 2.3 Causes and Effects of Land Use/Cover Change ...... - 8 - 2.3.1 Proximate Causes ...... - 8 - 2.3.2 Underlying Causes ...... - 8 -

vii

2.3.3 Effects of Land Use/Cover Change ...... - 10 - 2.4 Role of GIS and RS in Land Use/Cover Mapping ...... - 11 - 2.5 Image classification ...... - 11 - 2.6 Over view of Eucalyptus globulus ...... - 12 - 2.7 Importance of Eucalyptus globulus ...... - 13 - 2.7.1 Industrial importance ...... - 13 - 2.7.2 Ecological importance ...... - 13 - 2.7.3 Environmental importance ...... - 14 - 2.7.4 Economic importance ...... - 14 - 2.8 Negative impact Eucalyptus globulus ...... - 14 - CHAPTER THREE. ………………………………………………………………………..16 MATERIALS AND METHODS ………………………………………………………………16 3.1 Description of the Study Area ………………………………………………………………16 3.1.1 Geographical location ...... - 16 - 3.1.2 .Climate and Soil...... - 16 - 3.1.3 Farming System, vegetation and population ...... - 17 - 3.2 Materials and Software Used ...... - 17 - 3.3 Satellite Image Data Acquisition and Analysis ...... - 18 - 3.3.1 Sources of data ...... - 18 - 3.3.2 Satellite image processing ...... - 19 - 3.3.3 Classification of land use/cover ...... - 19 - 3.4 Accuracy Assessment ...... - 20 - 3.5 Methodology and Analysis for Economic Benefits of Land Use Changes ...... - 22 - CHAPTER FOUR. ………………………………………………………………………………..26 RESULT AND DISCUSSION ……………………………………………………………………26 4.1 Land UseTrende Change ...... - 26 - 4.2 Trend and Magnitude of LULC Change ...... - 26 - 4.3 Accuracy Assessment ...... - 31 - 4.4 Tree Based Land Use Changes on Household Incomes and Land Productivity ...... - 31 - 4.4.1 Productivity of crop based land use ...... - 31 - 4.4.2 Productivity of grazing based land use ...... - 32 - 4.4.3 Productivity of Eucalyptus globulus based land use ...... - 33 -

4.5 Cost-benefit analysis (CBA) ...... - 34 - 4.6 Land Equivalent Ratio (LER) ...... - 35 - CHAPTER FIVE…………………………………………………………………………..- 37 - CONCLUSIONS AND RECOMMENDATIONS- 37 - 5.1 Conclusions...... - 37 - 5.2. Recommendations ...... ……..- 38 - 6. REFERENCES…………………………………………………………………………- 39 - Author’s Biography………………………………………………………………………..- 59 -

LIST OF TABLE Table 3.1Satellite Image used in this study and their characteristic ...... - 18 - Table3.2 Software and material used in the course of the study ...... - 18 - Table 3.3 Land use land cover classes of farta district ...... - 20 - Table 4.1 Area coverage and Land use land cover changes of Farta district for the year 1989, 1999 2009and 2019 ...... - 27 - Table 4.2 Productivity of wheat yield, straw yield and its monetary value in Ethiopian Birr . - 32 - Table 4.3 Grazing land productivity and its monetary value in Ethiopian Birr. ….…..- 33 -

Table 4.4 Productivity of Eucalyptus globulus land use and its monetary value in Ethiopian Bir- 33 -

Table 4.5 Cost benefit analysis of different land uses …...... 35

Table 4.6 Land equivalent ratio of different land use type…………...……………………. 35 -

viii

LIST OF FIGURE Fig.3.1 Location map of the study area, Farta district,in the northwest highlands of Ethiopia- 16 - Fig.3.2 Mean annual rainfall and maximum temperature of Farta district from1989 to 2019.17 Fig 3.3schematic diagram showing steps of land use /cover classification and change analysis…- 22 - Fig 3.4 Schematic diagram showing sampled kebeles and sampling techniques………………...- 25 - Fig. 4.1 Land use/cover map of Farta district in the year 1989-2019………………………- 26 -Fig. 4.2 Trend of land use/cover change from 1989- 2019 at Farta district……………………..- 28 -

LIST OF APPENDIX

Appendix 1.Estimated value of wheat and wheat straw yield as crop ...... - 52 - Appendix 2. Estimated value of pasture yield for grazing land ...... - 52 - Appendix 3. Estimated value of Eucalyptus globulus yield for plantation land ...... - 52 - Appendix 4 Cost Benefit analysis of crop land (wheat) ...... - 53 - Appendix 5 Cost Benefit analysis of grazing land ...... - 54 - Appendix 6 Cost analysis of E. globulus based land ...... - 55 - Appendix 7 Wheat crop in Awuzet kebele ...... - 56 - Appendix 8 grazing area in wowamagerat kebele ...... - 56 - Appendix 9 Eucalyptus globulus Awuzet kebele...... - 56 - Appendix 10 Confusion Matrix ...... - 57 -

CHAPTER ONE

1. INTRODUCTION

1.1. Background and Justification Globally, Land use and land cover (LU/LC) change is a major issue of environment change (Prakasam, 2010). Forest resources decreased from 53 million km2 to 43.5 million km2 with an annual deforestation rate of 0.073 km2 from 2000-2005 (FAO, 2005).The trends of land use/cover change have been studied by different scholars in different parts of the world. For example: Kanyamanda et al. (2010) Shown that forest and urban land uses reduced by 15.6% and 8.7% respectively, at the expense of cultivated (16.9%) and water (7.4%) land uses in Wuhan (China) from 1987-2006. Forest cover (land use) reduced by 3368.2 ha (38.9%) in Owabi catchment, Ghana, due to human activities or population growth (Frimpong, 2011).Forest and cultivated reduced by16.66% to12.14% and 27.24% to 23.58%) respectively, in Vishav drainage basin from1990-2010 (Nanda et al, 2014). Selçuk Reis (2008) shown that Agriculture and urban land cover/use increased by36.2%) and 117% respectively, at the decrease of pasture (72.8%) and forestry (12.8%) land use in North-East Turkey from1976 and 2000. cultivated reduced from 31 % in the year 2000 to 24 % in 2010 be due to slow and steady growth of urbanization (residential and commercial constructions) (Jiya George et al. 2016).

In Ethiopia ,land use/cover showed significant changes occurred in the last century, due to anthropogenic activities, population increase and due to land use changes, including deforestation, over grazing, and improper cultivation of agricultural land which led to accelerated soil erosion and associate soil nutrient deterioration (FAO, 1998)). In Ethiopia, the second half of 19th century, governments promoted plantations, to compensate for the declining supply of woods from natural forests (Demel et al. 2010). Currently Smallholder farmers have taken the main share in increasing tree plantings in the form of farm forests (Negussie 2004; Tesfaye 2005; Jagger et al. 2005)

Most of the population of Ethiopia have settled on the highlands, with the northern and central highlands being the oldest settled regions of the country. These regions are the most exploited and environmentally degraded areas in the entire country. In the highlands, due to the shortage of arable land, land is continuously utilized year after year thus leading to diminishing yields (Assefa and Zegeye, 2003). Ethiopia is suffering enormous LU/LCC due to high population pressure and cultivated for long period of time (Kindu et al., 2013). These changes are mainly from natural vegetation land to agricultural land and settlement. The LU/LCC problem is more severe in the highlands of Ethiopia (Eshetu and Hogberg, 2000).

Extensive land use/cover changes have occurred in Ethiopia during the second half of the 20th century (Kebrom and Hedlund, 2000).In Ethiopia, different research results on land use and land cover change showed substantial increment in cultivated land and settlement but substantial decrement in natural vegetation including forests. Eyayu M. et al (2010) shown that the cultivated and settlement land coverage increased by 90.60%. at the decline of woodland, dense forest, riverine vegetation, shrub and grasslands coverage by 97.87, 71.04, 37.00, 9.02 and 3.03%, respectively in Tara Gedam and Adjacent Agro-Ecosystem, Northwest Ethiopia from 1957 - 2003. The annual rate of forest cover change was 120ha/year in Banja district Ethiopia from 1973 – 2003 (Abyot et al 2014) .Fetene et al (2014) shown that cropland had increased by 206%, whereas forest, grasslands and shrub lands have decreased by 79, 40 and 17%, respectively, from 1986 - 2011.Adane (2016) shown that agriculture/settlement increased by 173369 ha, at the decline of wood 296692ha and forest 85184 ha land use in Bale Eco-Region from1986 - 2016.

Land use and land cover change (LULCC) are associated with large negative impacts on ecosystems observed at local, regional and global scales. High rates of water, soil and air pollution are the consequences of observed LULCC. Biodiversity is reduced when land is changed from a relatively undisturbed state to more intensive uses like farming, livestock grazing, selective tree harvesting, etc. (Ellis, 2011).

Many land-use changes are due to ill-defined policies and weak institutional enforcement, as showed by the widespread illegal logging in Indonesia linked to corruption and to the devolving

2 of forest management responsibilities to the district level (Jepson P. et al.2001).On the other hand, recovery or restoration of land is also possible with appropriate land-use policies.

In Amhara national regional state has been approved a proclamation No.252/2017 that can assist achieve mismanagement of land resource Moreover, the land use policy of the country should be effectively implemented to reverse the trend of LU/LC changes and land degradation and at the same time to enhance the livelihood of farming households.

1.2. Statement of the problem The LU/LCC problem is more severe in the highlands of Ethiopia (Eshetu and Hogberg, 2000). It is because these areas were characterized by high population pressure and cultivated for long period of time (Kindu et al.2013) .In the Ethiopian highlands Eucalyptus globulus (Nechbahir zafi) is the major species grown as small-scale forestry by smallholder farmers. At present, due to its high adaptability, tolerance of severe periodic moisture stress, low soil fertility, tolerance of fire, insect and browsing animal damages, and wide distribution even on degraded lands and socio-economic contribution as a short rotation and high yielding cash crop, it became the primary species to many farmers and wood lot growers of Ethiopia (Gil L.et al. 2010).

Eucalyptus globulus plantation in Farta district has been started around 1984 in the state plantations on different hilly places however due to plantation by farmers started around 1993 with forest package it is expanding at alarming rate. Eucalyptus globulus is more desirable tree species in the district because it is a fast growing species, highly adapted to the area and provide the community more wood, cash and construction of house (BoA,2019).

Farmers in the highland of south Gondor zone, including Farta, are currently applying organic fertilizers and lime to decrease the soil acidity and improve its productivity. However, applying inorganic fertilizers and lime are expensive to smallholder farmers. Also, the soils of the highlands of Farta are not responding to inorganic fertilizers due soil acidity problem and depletion of soil organic matter. Therefore, farmers are converting their land use system, from farmland to plantation, by planting Eucalyptus globulus supposing that the tree based farming land use change can influence the agricultural productivity and socio-economic conditions.

In the Ethiopian highlands, although studies have been conducted on the LU/LC changes (Woldeamlak 2002; Tefera, 2011; Kindu et al., 2013; Molla, 2014; Alemu et al., 2015), there is no detail research conducted on the economic benefits of the different land use/cover types. Therefore, the main concern of this study is to analyze land use/cover change of farmer’s incomes and consider the LUCC predicting future changes to design appropriate land use planning policies.

1.3. OBJECTIVES OF THE STUDY 1.3.1 General Objective

The major objective of the study was to investigate the land use/cover dynamics and the economic benefits of the different land use/cover types, in Farta district, in the northwest highlands of Ethiopia

1.3.2 Specific Objectives The specific objectives of the research was:

 To assess the land use/cover dynamics for the past thirty years (1989-2019),

 To measure the productivity of the different land uses and land equivalent ration (LER),

 To investigate economic advantages of the different land use/cover types 1.4 Research Questions  Is there any land use cover change at Farta district within thirty years (from 1989- 2019)?  What is the magnitude and trend of the land use/cover change?  What is the economic benefit and productivity of land use e systems at Farta district

1.5 Limitation of the Study

The study of limitations were materials (hypsometer, caliper, meter GPS and sensitive balance).Inappropriately, due to access and resource limitations,

1.6 Scope of the Study

The study was spatially restricted in the Farta district which covers about 82982ha. The study was restricted to investigate the land use/cover dynamics and the economic benefits of the

- 4 - different land use/cover types, in Farta district between 1989 and 2019. To achieve the study field observations, planned objectives, satellite imagery, and collection of primary and secondary data were done.

1.7 Organization of the thesis

This paper is organized into five chapters; the first chapter has an introduction part where the background, statement of the problem, objectives of the study, research questions, limitations and scope of the study are discussed. Review of related literatures provided in the second chapter. The third chapter focuses on the general methodology which presents; description of the study area, types of data, methods of data collection and analysis. The fourth chapter describes with the detail result and discussion part. Finally, chapter five, provided conclusions and recommendations of the study including key findings and critical points that need further treatment has been forwarded as a recommendation.

- 5 -

CHAPTER TWO

Literature Review

2.1. Land, Land use, and Land cover, definition Land is a delineable area of the earth’s terrestrial surface, encompassing all attributes of the biosphere immediately above or below this surface, including those of the near-surface climate, the soil and terrain forms, the surface hydrology (including shallow lakes, rivers, marshes, and swamps), the near-surface sedimentary layers and associated groundwater reserve, the plant and animal populations, the human settlement pattern and physical results of past and present human activity (terracing, water storage or drainage structures, roads, buildings, etc.) (FAO, 1995) .

Land use is a more complicated term. Natural scientists define land use in terms of conditions of human activities such as agriculture, forestry and building construction that alter land surface processes including biogeochemistry, hydrology and biodiversity. Social scientists and land managers define land use more broadly to include the social and economic purposes and contexts for and within which lands are managed (or left unmanaged), such as subsistence versus commercial agriculture, rented vs. owned, or private vs. public land (Ellis, 2007).

Land cover is the observed (bio) physical cover on the earth's surface, including water surfaces. When considering land cover in a strict sense, it should be confined to the description of vegetation and man-made features. However, in practice it also includes the areas of bare rock or bare soil (which describe land itself rather than land cover) and water surfaces. The latter is the more common use of the (FAO, 2000) .Water surfaces include inland water (e.g., rivers, lakes and ponds), coastal water bodies and inter-tidal areas but not marine water

2.2. Land-use and land-cover (LULC) change Land cover or land use change indicates the changes occurring to the land cover or land use over time. These may be natural successional changes, natural events or due to climate change or human intervention (Global Strategy to Improve Agricultural and Rural Statistics 2016).

- 6 -

Land-use and land-cover (LULC) change also known as land change, is a general term for the human modification of Earth's terrestrial surface. Though humans have been modifying land to obtain food and other essentials for thousands of years, current rates Application of Remote Sensing and GIS for Forest Cover Change Detection extents and intensities of LULC change are far greater than ever in history, driving unprecedented changes in ecosystems and environmental processes at local, regional and global scales (Ellis, 2007) . Different studies show that there has been a marked land use and land cover change in different parts of the world.

Kanyamanda. et al (2010) Shown that forest and urban land use reduced by 15.57% and 8.66% respectively, at the expense of cultivated (16.88%) and water (7.35%) land use in Wuhan (China), 1987-2006. Forest cover (land use) reduced by 3368.16 ha (38.9 %.) in Owabi Catchment, Ghana due to human activities or population growth (Frimpong, 2011). Forest and Agriculture land use reduced by16.66% to12.14% and 27.24% (289.59 Sq. Km) to 23.58% (250.59 Sq. Km) respectively, in Vishav drainage basin from1990-2010 (Nanda et al, 2014).

Extensive land use/cover changes have occurred in Ethiopia during the second half of the 20th century (Kebrom and Hedlund, 2000).In Ethiopia, different research results on land use and land cover change showed substantial increment in cultivated land and settlement but substantial decrement in natural vegetation including forests. Kebrom Tekle and Hedlund, L. (2000) shown that shrub lands, decrease of 15.5 km2 (–51%), at the expense of open areas (i.e., excluding cultivated and settlements), 14.3 km2 (+333%) land use in Kalu District, southern Wello, Ethiopia from 1958 -1986. Belay, T. (2002) shown that natural vegetation cover decreased, at the expense of cultivated 7 % land uses in the Derekolli Catchment, South Wolo Zone of Amhara Region, Ethiopia1957 from1986. Fisseha et al (2011) shown that the natural forest cover declined by 91.74%, the shrub land by 60.79%, and the grazing land by 39.47%, at the expense of the cultivated 14.75% land uses in Debre-Mewi watershed the Blue Nile Basin, Northwest Ethiopia from(1957 -2008) . Fetene et al (2014) shown that crop land use increased by 206%, whereas forest, grasslands and shrub land use/cover decreased by 79, 40 and 17%, respectively from 1986 - 2011. Cultivated and settlement land

- 7 - use/cover increase by 41 % and 13 % respectively in Azezo Tekle Haymanot Kebele, due to resettlement (Worku M, Deribew S. 2018).

2.3 Causes and Effects of Land Use/Cover Change

Causes of Land Use/Land Cover Change

The LU/LC is related with several natural and human induced factors (Rahdary et al., 2008). The natural or biophysical causes of LU/LCC include: slop, climate change, soil type, wildfire, pest infestation, flood and drought (Garedew, 2010; Shiferaw, 2011). Human induced or anthropogenic driving forces of LU/LCC grouped as the direct effects of human activity (proximate causes) and indirect effects of human activity (underlying driving forces) (EPA, 1999). The earlier includes agricultural expansion, wood extraction and infrastructure expansion while the later includes demographic, economic, technological, policy and institutional and cultural factors (Geist and Lambin, 2002). The human prompted causal factors increasingly recognized as a dominant force in LU/LCC (Lamichhane, 2008; Chang- Martínez et al., 2015). One-third to one-half of the global land surface change due to logging, agricultural expansion, over grazing, fire management, forest harvesting and urban and suburban construction and development (Briassoulis 2011).

2.3.1 Proximate Causes Proximate causes of LU/LCC are immediate actions of local communities and directly exerted on land resources due to different underlying causes such as economic, social, political, etc. (Geist and Lambin, 2002; Shiferaw, 2011). According to Geist and Lambin (2002) agricultural expansion, wood extraction and infrastructure expansion are major proximate causes of LU/LCC. De Sherbinin (2002) explained that agricultural expansion is the dominant proximate cause for LU/LCC. Agricultural expansion comprises permanent cultivation (large scale, smallholder subsistence and commercial), shifting cultivation (slash & burn) and cattle ranching (large-scale and smallholder) (Geist and Lambin, 20020).

2.3.2 Underlying Causes Underlying causes of LU/LCC involves the structural (or systemic) factors that trigger the proximate causes (Geist and Lambin, 2002; Lambin et al., 2003). They operate at the regional (districts, provinces, or country) or even global levels by changing one or more proximate

- 8 - causes (Lambin et al., 2003; Lambin and Geist, 2007). They are external to the local communities and not controlled at the local level. According to De Sherbinin (2002) and Geist and Lambin (2001, 2002) underlying causes of LU/LCC originate from a complex interaction of social, policy and institutional, economic, demographic, technological, cultural and biophysical factors. Economic factor is one of the major underlying causes of LU/LCC particular for tropical deforestation (Geist and Lambin, 2002). Economic variables such as low domestic costs (for land, labor, fuel or timber), increase in product price (mostly for cash crops) influence land use decision making, thereby impacting the land cover (Geist and Lambin, 2002). Besides these, change in prices, taxes, and subsidies on land use inputs and products, change in the costs of production and transportation and access to credit, market, and technology also plays vital role in LU/LCC (Lambin and Geist, 2007).Political, legal, economic and traditional institutions and their interaction with individual decision making also influence LU/LCC (Lambin and Geist, 2003; Lambin and Geist, 2007). ). Institutional causes of LU/LCC must be considered both at large scale (international or national level) and local level (Lambin et al., 2003). This is because the implementation of large scale policies is practiced at local level and local people’s access to land, capital, technology and information influenced by the structure of both local and large scale policies (Lambin and Geist, 2003).

- 9 -

Most developing countries including Africa, Asia and L/America countries population growth and LU/LCC have a strong statistical correlation Turner and Meyer (1994). In agreement to these different studies undertaken in different parts of Ethiopia also reported population growth as a major cause for LU/LCC. Population growth was the major cause for the expansion of agriculture and reduction of vegetation covers in Ethiopian highlands (Muluneh, 2010), Borena Wereda South Wello highland. (Shiferaw, 2011), Nono Wereda, Central Ethiopia (Tefera, 2011), West Guna Mountain South Gondar (Minale, 2012). (Tsegaye, 2014) and Northwest lowland of Ethiopia (Alemu et al., 2015). In Ethiopia expansion of agricultural land and loss of natural vegetation are associated with population growth, poor economic condition, unclear land tenure right and several other biophysical and socio- political factors (Melaku, 2003).

2.3.3 Effects of Land Use/Cover Change Hydrological cycle

Land under little vegetative cover is subject to high surface runoff and low water retention. The increased runoff causes sheet erosion to intensify and rills and gullies to widen and deepen. The masses of sedimentary materials removed from hill slopes accumulate in low- lying areas downstream, where they create problems of water pollution, reservoir siltation, and problematical sediment deposition on important agricultural lands (Woldeamlak Bewket, 2002).

Loss of Biodiversity

Biodiversity has been diminishing considerably by land change. While lands change from a primary forested land to a farming type, the loss of forest species within deforested areas is immediate and huge (Ellis and Pontius 2006). According to Ellis and Pontius (2006): the habitat suitability of forests and other ecosystems surrounding those under exhaustive use are also impacted by the fragmenting of existing habitat into smaller pieces, which exposes forest edges to external influences and decreases core habitat area.

LU/LCC can affect soil fertility, land productivity and the sustainability of environmental service provision (Burka, 2008; Molla, 2014). Apart from these, it also contributes to global

- 10 - warming (Molla, 2014).Land use changes affect watershed runoff, groundwater tables, processes of land degradation and landscape level biodiversity (Lambin & Geist, 2008) . Loss of land cover results in high rate of soil erosion, loss of soil fertility, and degradation of water resources (Mulatie Mekonnen et al., 2016). Land use/cover dynamics and successive conversion lead to loss of biodiversity, deterioration in the physical and chemical properties of soil which causes degradation of the land (Emadodin et al., 2009). Gete and Hurni (2001) shown that the radical land use and land cover change effect in the Ethiopian highlands into regional implications will affect countries downstream because of the water and sediment carried from Ethiopia by the trans-boundary Rivers especially the Blue Nile. Therefore, studying about LULC change is one of the most detailed techniques to recognize how land was used in the past, what types of changes are predictable in the future, as well as the forces and processes behind the changes (Lambin et al., 2001).

2.4 Role of GIS and RS in Land Use/Cover Mapping Remote sensing is Science and art of obtaining information about an object, area or phenomenon through the analysis of data acquired by a device that is not in physical contact with the object, area or phenomenon under investigation (Lille sand, T. M., and Kiefer, R. W. 1987). GIS is a powerful set of tools for collecting, storing, retrieving, transforming and displaying spatial data from the real world for a particular set of purposes” (Burrough and McDonnell 1998 p. 11).

2.5 Image classification Classification is the process of sorting pixels into a finite number of individual classes, or categories of data based on their data file values. In this study, both supervised and unsupervised classification methods were adopted. Unsupervised classification method was used first to have an idea representing overall land use and land cover cluster of pixels. Thereafter, supervised classification method was used with Maximum Likelihood Classification algorithm. This process different others considers the spectral variation within each category and the overlap covering the different classes (.Mathewos Muke1 and Bewuketu Haile (2018) Knowledge of the data, the classes desired, and the system used was required before selecting training samples. Every pixel in the whole image was then classified as belonging to one of the themes depending on how close its spectral features are to the spectral features of the training areas. Finally, the classified image was verified for its

- 11 - accuracy or acceptance having gone through different mechanisms assuming that resulting class corresponds against ground truth field samples often obtained with a GPS.

2.6 Over view of Eucalyptus globulus Eucalyptus globulus was discovered in islands of Tasmania in 1792 by French Explorers. Eucalyptus amygdalin (Labille) is the tallest known tree, specimens attaining as much as 480 feet, beyond in height even the Californian Big Tree (Sequoia gigantea). Many species yield valuable timber, others oils,kino, etc. Genus Eucalyptus contains about 600 species of all the species, Eucalyptus globules is the most widely cultivated in subtropical and Mediterranean regions (Vishin et al 2014).

Eucalyptus globules is Kingdom- Plantae – Plants Subkingdom -Tracheobionta – Vascular plants Superdivision-Spermatophyta – Seed plants Division- Magnoliophyta – Flowering plants Class- Magnoliopsida – Dicotyledons Subclass-Rosidae Order- Myrtales Family- Myrtaceae – Myrtle family Genus -Eucalyptus L'Hér. –gum (Vishin et al 2014).

Eucalyptus globules a tall tree to 55 m, rather narrow, the crown rounded and open, the main stems straight. Bark: Blue‑grey, smooth, rough at base. Leaves: Young leaves, opposite, oval, blue‑grey without stalks, mature leaves deep blue‑green, shiny, very long and thin to 30 cm, slightly curved, stalked, smelling of camphor if crushed, tip sharp. Flowers: Bud’s grey‑green, wrinkled, 2.5 cm, usually 1, rarely 2 or 3, together, the white ﬂowers to 4 cm across. Fruit: Woody, half spheres, rough, 3 cm across, four‑angled, no stalks. Dull black seeds escape from slits Eucalyptus globules grows in the cooler and wetter parts of south‑west Australia. A tree suitable for high‑altitude areas as it tolerates frost. It performs well in upper Dry, Moist and Wet Weyna Dega and Dega agro climatic zones in Tigray, Gonder, Welo, Shoa, Gojam, Wolega, Kefa, Arsi and Harerge, 1,700– 2,800 m (Azene Bekele, 2007).

Ethiopia has a long history of tree planting activities. According to historical records, afforestation started in the early 1400s by the order of King Zera‐Yakob (1434‐1468). Modern tree planting using introduced tree species (mainly Australian Eucalyptus) started in 1895 when Emperor Menelik II (1888‐1892) looked into solutions for alleviating shortage of firewood and construction wood in the capital city, Addis Ababa (Nawir et al., 2007). Forest plantation practices in Ethiopia are mainly of exotic tree species with Eucalyptus covering the largest area of hardwood plantations (EPA, 2007).Amhara region has wide biodiversity

- 12 - composition of flora and fauna species (BoA, 2012). Plantation forests are mainly found in Awi, North Shewa, South Gonder, South Wollo, East and West Gojam zones of the region. These plantation forests are ranging from large scale to woodlots and homesteads. Eucalyptus species, Acacia decurrence and Cypresses’ lusitanica are the most common tree species widely planted in community woodlots and private tree investments in Amhara region (Fentahun et al 2016).

2.7 Importance of Eucalyptus globulus

2.7.1 Industrial importance Eucalyptus globulus is a rich source of phytochemical compounds as flavonoids, alkaloids, tannins and propanoids, extracted in the leaf, stem and root of the plant. Eucalyptus globulus which has different vernacular names (eucalyptus in Bengali and in Hindi; blue-gum eucalyptus in English and Karpuramaram in Tamil(Dixit A, et al., 2012), is considerably used in the pulp industry, as well as for the production of eucalyptus oil (henceforth EO), Beneficial and Healthy Properties of Eucalyptus The Open Agriculture Journal, 2016, 53extracted on commercial scale in many countries and adopted in perfumery, cosmetics, food, beverages, aromatherapy and phototherapy (Buchbauer G.,2000).

Eucalyptus globulus is a source of oil used for several purposes. The oil is extracted from leaves, fruits, buds and bark showing antibacterial, antiseptic, antioxidant, anti-inflammatory, anticancer activities (Egawa H et al.,,1977,Dixit A, et al., 2012) . For this reason used in the treatment of respiratory diseases, common cold, influenza, and sinus congestion] Silva J et al., 2003)

2.7.2 Ecological importance Control of soil erosion to conserve soil are physical conservation measures (e.g. terraces, check dams) and biological conservation measures (e.g. tree planting). (Davidson 1989). Eucalyptus as one of the most important commercial plantation and found tree species in successful ecological restoration of degraded lands (Zhou et al. 2001). Trees protect water resources by enhancing hydrological functions of landscapes and help combat the drying of the land (desertification). (Gil L, et al, 2010).

- 13 -

2.7.3 Environmental importance

Plantations are increasingly being recognized as a key component of mitigating global climate change. Plantations play a strategic role in maintaining balance. Forests emit and sequester CO2: about 20% of global CO2 emissions are contributed by deforestation while trees are also contributing to reduce atmospheric carbon dioxide, which is mostly responsible for global warming (the greenhouse effect). Carbon dioxide from the atmosphere is captured by the planted trees and converted into high-value wood and oxygen (Gil L, et al, 2010).Eucalyptus globulus used to Environmental planting (water and wind erosion control), ((Elliot WR, Jones DL, 1984).

2.7.4 Economic importance Eucalyptus trees balancing economic development with environmental sustainability is a global challenge. This balance becomes more complex as the world’s population grows and people demand goods whose production involves the use of natural resources. The growing of Eucalyptus, especially in the ANRS is largely motivated by the scarcity of construction wood, fuel wood as well as, to generate cash income (Gil L, et al, 2010). Mekonnen et al (2007) reported Eucalyptus contribute 92 %, 74 %, 85 %, 40 %, 83 % and 91 % of construction poles, timber, firewood, charcoal, posts and farm implements wood sources for rural livelihoods Lode Hetosa District, Central Ethiopia .Eucalyptus globulus is used in forestry (timber, fuel, paper pulp), as a source of essential oil (medicinal, perfumery oils), for arts and craft (Elliot WR, Jones DL, 1984)

2.8 Negative impact Eucalyptus globulus Recently, however, experts and policy makers at various levels have started discouraging farmers to plant Eucalyptus because of its presumed negative environmental impact. The main debates are focused on its aggressive extraction of water resource, impoverishment of soil fertility under Eucalyptus, and finally its allelopathic property, which excludes and restricts germination and growth of other species. It has been argued that Eucalyptus takes up a great amount of water from the soil and ground water, and when grown in plantations it lowers the groundwater level more than other trees and crops (Prabhakar 1998). Boundary planting of Eucalyptus globulus in Ethiopian Nitosols a significant reduction of wheat yield in

- 14 - the first 8 to 12m across the tree crop interface (Kidanu et al. 2004). Eucalyptus leaves have phenolic acids, tannins, and flavonoids and that these chemicals inhibit the growth of crops and trees (Babu and Kandasamy 1997).Eucalyptus released toxic allele chemicals into the soil system mainly through litter decomposition products (May and Ash, 1990; Lisanework and Michelson 1993) .Reduced germination and radical growth of chickpea, field pea, maize, and tef (Lisanework and Michelson 1993) Eucalyptus globulus depleted soil nutrients in the central highlands of Ethiopia (Kindu et al. 2006).

- 15 -

CHAPTER THREE. MATERIALS AND METHODS 3.1 Description of the Study Area 3.1.1 Geographical location The Farta district is located between 11˚32'00"N to 12˚03'00"N latitudes and 38˚02'00"E to 38˚05'00"E longitudes in the South Gondar Administrative Zone of Amhara National Regional State (ANRS), Ethiopia, It is about 660km north of the Addis Ababa and 100km northwest of Bahir Dar,the Capital city of ANRS.The total coverage of the area is 82,982ha.Cultivated land, grazing land ,natural forest ,settlement, wet land, plantation and others constitutes 57.43% , 10.8%,3.93%, 7.1%,4.34%,10.07% and 6.33%, respectively (source Farta BoA,).

Fig.3.1 Location map of the study area, Farta district, in the northwest highlands of Ethiopia 3.1.2 .Climate and Soil According to Abayneh, (2017), the study area has seven soil types, such as Alisols, Nitisols, Luvisols, Vertisols, Cambisols, Regosols and Lepthosols. Major agro ecological zone is (cool and humid) Dega 42.5%) and the remaining is Temperate (cool sub-humid)( woyena Dega) (57.5%)with an altitude ranged from 2600 to 3100 meter above sea level .The average minimum and maximum temperature of the area is 7.44 °C and 24.22 °C, respectively The mean annual rainfall ranged from 900 to 1800 millimeter.

- 16 -

Rainfall

600

400

200 Milimeter 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec . .

30 20 10 0

Degree grid Degree centi Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month maxTemp min Temp

Fig.3.2 Mean annual rainfall and maximum temperature of Farta district from1989 to 2019 (Source; Bahir Dar Meteorology Agency

3.1.3 Farming System, vegetation and population

Agriculture in the study area is characterized by mixed crop–livestock production and subsistence farming. The major rainfed cereal crops grown in the area include barley (Hordeum vulgare), wheat (Triticum vulgare), tef (Eragrostis tef), maize (Zea mays), and oats (Avena sativa) and legumes like beans (Vicia faba) and pea (Pisum sativum) vegtable like Potato (Solanumtuberosum). The common types of domestic animals raised in traditional farming include cattle, goats, sheep, donkeys, horses, mules, and chickens. The main sources of food for livestock production are communal and private grazing lands. .However, vegetation like Treelucern (Chamaecytisus proliferus) Girangire (Sesbania sesban) planted in the district, and farmers concentrated on Tasmanian blue gum (Eucalyptus globulus) in order to improve their income and livelihood assets and for construction Farta district. Population of the district has 111,259 male, 107,871 female and total 219,330. (Source, Farta BoA, 2019).

3.2 Materials and Software Used

For this study both Primary and secondary data were collected. GCPs and land use bear productions were collected as primary data. Whereas, population data and satellite images

- 17 - were collected as secondary data. GPS was used to collect ground control points in UTM format with WGS 84 as a datum for image classification and accuracy assessment of the resulting land cover map ArcGIS 10.3.1 for spatial analysis and mapping, ERDAS Imagine 2010 for image classification and change detection, Google Earth Pro to see and collect time series training points, Microsoft Office Excel 13were used to analyze the descriptive statistics and produce graphs.

3.3 Satellite Image Data Acquisition and Analysis

3.3.1 Sources of data

Table 3.1Satellite Image used in this study and their characteristic No. Image Sensor Acquisition date Path/Row Resolution No. Of bands

1 Landsat 5 TM 4/1/ 1989/ 169/52 30x30 7

2 Landsat 5 TM 5/3/1999 169/52 30x30 7

3 Landsat 7 ETM 19/1/2009 169/52 30/30 7

4 Landsat 8 OLI-TIRS 23/1/2019 169/52 30x30 11

(Source; http://www.usgs.gov.et)

Table3.2 Software and material used in the course of the study Software /materials/ Application

ARCGIS 10.3.1 Image processing and map preparation

ERDAS EMAGINE 2010 Image preparation and processing

MS EXCEL Statistical analysis and Chart and graphs preparation

MS WORD Word processing

Caliper Measure tree diameter

Hypsometer Measure tree height

Meter tape Measure sample area

Sensitive balance (0.01 digits) Measure Wheat biomass, grain yield, grass biomass,

- 18 -

3.3.2 Satellite image processing To reduce variability due to difference in timing, all the images used were taken in January and March. Satellite images taken during this period also helps to get better data on Eucalyptus globulus plantations since other green vegetation’s like crops are not found. Satellite image pre-processing is vital for radiometric and geometric corrections, which helps to geo-reference and transform the image data into a format that can be readily interpreted in terms of earth surface attributes. After the satellite images are ready for interpretation they were layer staked; the single bands combined together into one file to use the spectral information of different bands of the images. Layer stack technique was performed to group the needed bands together. Image enhancement was also done to improve the appearance of the image to make image interpretation easier in general. After all these processes, image classification was conducted.

3.3.3 Classification of land use/cover Image classification involves categorizing raw remotely sensed satellite images into a fewer number of individual LU/LC classes, based on the reflectance values (Adedeji et al., 2015). This study used a hybrid classification method involving both unsupervised and supervised image classification techniques. First unsupervised classification was carried out before field work to understand the general LU/LC classes of the study area and to select sample training sites for data collection during field work. This is because unsupervised classification is automatic and requires little knowledge of the study area. And then after the field work maximum likelihood supervised classification was carried out to categorize the images using training sites. Training sites were defined by using original images, the results of unsupervised classification, field study knowledge and secondary data (Google Earth pro). Image classification was performed by using ERDAS IMAGINE 2010 software. Ground control Points and secondary data (Google Earth) were used to define training sites for the recent image (OLI/TIRS) classification. Training sites for classification of older images (TM and ETM+) were defined based on the result of unsupervised classification, spectral values of recent image and information obtained from elder peoples. In this study A total of 290 ground control points were collected at representative sites that is 60 points from grazing land, 65 points from cultivated lands, 21 points from wetlands, 37 points from bare land, 36 points

- 19 - from settlement, 6 points from water body 25points from forest and 40 points from plantation (57 points in1989, 71points in1999, 83 points in 2009 and 82 points in 2019) For classification accuracy assessment of older images (TM and ETM+) a total test samples of 208 were randomly selected from the original mosaic image of the respective years Based on the satellite images, training points and field observation eight land use/cover classes were identified: Grazing Land, Cultivated Land, wetland ,Forest, water body, Bare Land, Plantation and Settlement (Table 3.3). Categorizing the land use/cover classes was done based on visual interpretation of the satellite images and field observation.

Table 3.3 Land use land cover classes of farta district LULC classes Characterization of features

Forest Areas covered with dense trees, which include both Eucalyptus and conifer tree and riveren trees Cultivated land Areas used for rain fed crop production and scattered rural settlement usually associated with cultivated land. Bare land Areas that are with little or no vegetation cover and waste land

Wetland An area of lands with frequent flooding event during the rainy season & the water table is near by the surface throughout the year

Plantation Areas covered with regularly harvested planted trees, exotic tree species

Water Areas covered by Lake in the catchment permanently

Grassland Land covered by grasses and used for grazing, as well as bare land that have little grass or no grasses cover (Source; Abebe, (2018).

3.4 Accuracy Assessment It was performed on unsupervised and supervised classification to determine how well the classification process accomplished the task (Campbell, J. B., 2006). A set of reference points were taken from field observations to assess its accuracy. These points were verify and

- 20 - labeled against the reference data. Then error matrices were designed to assess the quality of the classification accuracy. The Kappa coefficient were also use to assess the classification accuracy. It expresses the proportionate reduction in error generated by a classification process compared with the error of a completely random classification (Congalton, 1991). The Kappa statistic incorporates the off-diagonal elements of the error matrices (i.e., classification errors) and represents agreement obtained after removing the proportion of agreement that could be expected to occur by chance

The Kappa statistic incorporates the off-diagonal elements of the error matrices (i.e., classification errors) and represents agreement obtained after removing the proportion of agreement that could be expected to occur by chance

The formula for kappa is :( Congalton, 1991).

Khat = (Obs – exp)/ (1 – Exp) Equation. 1 Where, Obs = Observed correct, it represents accuracy reported in error matrix(overall accuracy) Exp = Expected correct, it represents correct classification

Overall accuracy which is the number of correctly classified pixels (sum of major diagonal cells in the error matrix) divided by total number of pixels checked. Though, overall accuracy is a measure of accuracy for the entire image across all classes, it ignores off-diagonal elements (Campbell, J. B., 1987).Producer’s accuracy is defined as the probability that any pixel in that category has been correctly classified. It is the values in column accuracy (producer’s accuracy) present the accuracies of the categories in the classified image (Campbell, J. B., 1987).

Equation.2

User’s accuracy is defined as the probability that a pixel classified on the image actually represents that category on the ground (Campbell, J. B., 1987).

- 21 -

Equation.3

Following the accuracy assessment a table containing area in hectare and the percentage change for each year (1989, 1999, 2009 and2019) was developed for the comparison of land use/cover by identifying the percentage change, trend and rate of change between 1989 and

2019. (Ejemeyovwi, Danny Ochuko 2015).

Land sat image of TM (1989), TM+ (1999), ETM+ (2009) and

OLI (2019) Field work

Image classifications Field observations and GPS (unsupervised and supervised ground truth training points

)

Accuracy assessment

Change detection matrix Analysis impact of

LULCC map of 1989, 1999, 2009 static LULCC and its driver and2019

Fig 3.3schematic diagram showing steps of land use /cover classification and change analysis

3.5 Methodology and Analysis for Economic Benefits of Land Use Changes The study district Farta has 33 kebeles (lower administrative units), four kebeles Hiruy AbaArgawi, Wowmagrate, Siharna and Awuzet were selected purposefully. The experiment was designed in three treatments with four replications (at four kebeles). The treatments were;

- 22 -

(i) a cultivated field with wheat (Triticumaestivum), (ii) a grazing land, and (iii) a field with Eucalyptus plantation.

(i) A farmer field with wheat crop grown was selected (appendix 7) in June 2019, when wheat crop gets matured in October 2019, grain yield and straw biomass were collected. Three samples were taken from a single experimental field to make an average grain yield and straw biomass using a quadrant of 2 m * 2 m (4 m2). The crop was harvested when it was ready for harvest and grain yield was separated from the straw by hand and weighed. The straw biomass was determined by taking the sun dry weight of wheat The wheat and straw a of each sample is weight using a sensitive balance having two decimal digit precision .The yield obtained from the quadrant is converted to kilogram per hectare and converted to the Ethiopian Birr (ETB) value using current average price of variables. Lastly, the value are multiply by five to get the five years (2019-2015) cumulative financial benefits in hectare basis and compare with the five years Eucalyptus globulus based farming system.

(ii) A farmer grazing field (appendix 8) was selected in June 2019 and grass biomass was collected when the grass was at its maximum vegetative growth stage in October 2019 using a quadrant of 4 m * 4 m (16 m2) at three locations to make an average grass biomass yield. The

grass/pasture biomass was determined by taking the sun dry weight of the grass. The pasture weight sample is weighting using a sensitive balance having two decimal digit precision .The yield obtained from the quadrant is converted to kilogram per hectare and converted to the Ethiopian Birr (ETB) value using current average price of varibles.Lastly, the value are multiply by five to get the five years (2019-2015) cumulative financial benefits in hectare basis and compare with the five years Eucalyptus globulus based land system

(iii) A farmer field in which a five year old Eucalyptus globulus grown was selected (appendix 9). The product were estimated harvesting the tree from a quadrant of radius 5.64m (100m 2) sample taken from plantation to make production by measuring the sample tree height and diameter at breast height to get the volume of the tree in meter 3 each quadrant and converted to hectare basis and calculated in Ethiopian Birr value.

- 23 -

All the data (i-iii) were collected from the four locations (Kebeles) that means, replicated four times. Net benefit or Cost-benefit-analysis (CBA) of each land use was assessed by accounting total required costs such as seed, seedling cost, fertilizer costs, labour cost and other costs. Land equivalent Ratio (LER) &Cost benefit Ratio (CBR) are calculated by considering total cost of each land use system(Finally compare five years each land use total cost).

LER= x land use where, x is grazing and Eucalyptus globulus based land use

Cropland use

- 24 -

From Farta district four Namely kebeles were selected 1. HiruyAbaArgawi purposefully

2. Wowmagrat

3. Siharna

Five farmers at each kebele and 4. Awuzet each land use type selected purposefully

Land use type

1. Eucalyptus globulus based land Three land use type are use system deliberately selected within 2. crop based land use system each Kebele (wheat) 3. Grass (grazing) based land use system

Sample from crop based Samples from grazing Sample from plantation LUs (grass) based LU (Eucalyptus globules)

-pasture biomass yield (Wheat) crop and residue -production (yield) yield

Land equivalent Ratio (LER) &Cost benefit Ratio (CBR) are calculated by considering total cost of each land use system

)

- Fig 3.4 Schematic diagram showing sampled kebeles and sampling techniques

- 25 -

CHAPTER FOUR. RESULT AND DISCUSSION 4.1 Land Use Trends Change Figure 4.1, A. showed the LULC of the year 1989 in which. Cultivated land is the dominant land cover followed by forest land. Settlement showed the least coverage. Figure 4.1.B. showed the LULC of the year 1999 in which cultivated land is the dominant land cover

followed grazing wet land showed the least coverage. Figure 4.1.C.showed the LULC of the year 2009 in which. Cultivated land is the dominant land cover followed by bare land and grazing. Wet land showed the least coverage. Figure 4.1.D.showed the LULC of the year 2019 in which. Cultivated land is the dominant land cover followed by plantation .Water body showed the least coverage.

Legend

Cultivated land Settlement Grazing land Eucalyptus plantation Wetland Bare land Forest land A . B. Water body

C . D.

Fig. 4.1 Land use/cover map of Farta district in the year 1989-2019.

4.2 Trend and Magnitude of LULC Change Table 4.1 shows the LULC change of the four studied years in percentage in relation to the total land area of the study district. The cultivated land is the dominant land use type which accounts 55.9 %, 61.71%, 62.6 %, and 60 .34% from the total

- 26 - land area of the district in 1989, 1999, 2009 & 2019, respectively. Similar study conducted Samuale Tesfaye et al.(2014), cultivated land is the dominant land use type which accounts 50.63%, 64.98%and 66.12% from the total land area of the district in 1972, 1986 & 2008, respectively Gilgel Tekeze Catchment, Northern Ethiopia. Similarly Eyayu Molla et al (2010), shown that cultivated and settlement land coverage increased by 90.60% Tara Gedam and adjacent agro-ecosystem, northwest Ethiopia from. 1957 – 2003.

Table 4.1 Area coverage and Land use land cover changes of Farta district for the year 1989, 1999 2009and 2019 Area coverage Land use land cover changes in Area 1989- 1999- 2009- 1989- 1989 1999 2009 2019 1999 2009 2019 2019 land use Area (%) Area(%) Area (%) Area(%) Area (%) Area(%) Area(%) Area(%) forestland 10.52 5.40 4.05 3.82 -5.13 -1.35 -0.23 -6.71 plantation 3.56 4.12 7.19 10.39 0.56 3.06 3.20 6.82 settlement 2.65 5.19 5.74 6.89 2.54 0.55 1.15 4.24 grazing 11.46 10.53 8.17 7.78 -0.93 -2.36 -0.39 -3.68 Cultivated 55.9 61.71 62.63 60.34 5.81 0.92 -2.29 4.44 bare land 12.29 11.07 10.42 8.97 -1.22 -0.65 -1.45 -3.32 Wetland 3.61 1.97 1.80 1.63 -1.64 -0.17 -0.17 -1.98 water body 0 0.00 0.00 0.18 0.00 0.00 0.18 0.18 Total 100 100 100 100

- 27 -

8.00 6.82

6.00 4.24 4.44 4.00

2.00 0.18 0.00

percentage change(%) percentage -2.00 -1.98 -4.00 -3.32 -3.68

-6.00

-6.71 -8.00 LULC class

Fig. 4.2 Trend of land use/cover change from 1989- 2019 at Farta district

Table 4.1 shows that, cultivated land increased by 4825ha (5.81%), 762ha (0.9%) during the period between 1989 and 1999, 1999 to 2009 respectively. whereas in general cultivated land was increased by 4.44 % over the study period from 1989to 2019. This finding agrees with that of Fisseha et al. (2011), shown cultivated land increased by 14.75%.,in Debre-Mewi watershed of the Blue Nile Basin, Northwest Ethiopia from 1957 - 2008. Similarly Worku M, Deribew S, (2018) also shown Cultivated land increase by 41 % Azezo Tekle Haymanot Kebele. On the other hand, it differs from Hussien , (2009)the cultivated land has decreased by 0.2% in Lenche Dima Of Blue Nile And Awash Basins Of Ethiopia from 1972 - 2005.

- 28 -

Total area coverage of grazing land was about 11.45% in 1989, which decreased to 0.9% in 1999, to 2.36% in 2009, to 0.39%and 2019. During the study period between 1989 and 2019, the area under grazing land decreased by around 3.68%. This finding agrees with that of Eyayu Molla et al (2010) also shown that grasslands coverage declined by 3.03%. Between 1957 and 2003. On the other hand, it differs from Nurelegn. M. and Amare S. (2014) shows the, grazing lands increased by 50.9% in Rib Watershed, North Western Ethiopia between 1973 and 2011.

The area coverage of plantation increased by 0 .55%, increased to 3%between1999 and2009 It also increased to 2.85% between 2009 and 2019. The expansion of plantation during the past 30 years was 6.82% compared to the original area in 1989. This increment in plantation established by most individual farmers planted Eucalyptus globules in their farmlands and other land uses as a source of fuel wood, construction material, for income generation. Similar study conducted by Daniel (2008) plantations, increased at a rate of 2.8, % In the Upper Dijo River Catchment, Silte Zone, Southern Ethiopia from1972 - 2004. Also Similar study conducted by Fisseha et al (2011) Eucalyptus plantation increased by 1.28% due to a source of fuel wood, construction material and income generation, Debre-Mewi watershed ,Blue Nile Basin, Northwest Ethiopia from1982-2008.

Settlement areas were expanded by 4.24% an increased in settlement areas is due to population pressure and towns expansion from 1989-2019. Similar study conducted by. Samuale Tesfaye et al. (2014), reported settlement expanded by 9.99 % Gilgel Tekeze Catchment, Northern Ethiopia from 1976–2008.SimilarlyMohammed Mussa1 et al. (2017),also shown that settlement expanded by 14.3% in the lowland of Bale rangelands, Southeast Ethiopia from 1986 – 2016. Total area coverage of Water body was increased about 0.18% 2019 due to construction of Rib Dam.

- 29 -

The entire period of this study between 1989 and 2019, the area coverage under forest land minimized by around 6.71%. This result is similar to Adane Mezgebu (2016), shown that forest land use shrink by 17% in bale eco-region, Ethiopia from 1986 -2016. similarly Fisseha et al. (2011), also shown that natural forest cover declined by 91.74% Debre-Mewi watershed Blue Nile Basin, Northwest Ethiopia from 1957 -2008. Abyot Yismaw et al. (2014) shown that the annual rate of forest cover change was 120ha/year in Banja district, Amhara region, Ethiopia from 1973 - 2003. Forest cover (land use) reduced by 3368.2 ha (38.9%) in Owabi catchment, Ghana, due to human activities or population growth (Frimpong, 2011). In general, over the last 30 years (between 1989 and 2019), there was a negative change i.e. a reduction in forest land by 6.71 %.( table.4.1).

Grazing land decreased by around 3.68% most probably due to low productivity of grazing land; as a result farmers were forced to planting and reallocated to landless farmers and changed to crop land from 1989 - 2019.This finding agrees with that of. Samuale Tesfaye et al. (2014), reported Grazing land declined by 6.91 % Gil gel Tekeze Catchment, Northern Ethiopia from1976–2008.

Bare land decreased by around 3.32% due to Eucalyptus globules plantation on degraded bare lands from 1989 -2019. Similar study conducted by Hussien Ali Oumer (2009), the bare land has decreased by 0.3% in the period from 1972 to 2005 From Kuhar Michael of Blue Nile Basins of Ethiopia. wet land decreased by around 1.98% most probably due to drying (reduce water table) and to planting and to cropland from 1989 – 2019.2 Similar study conducted by Hussien Ali Oumer (2009) the wet land has decreased by 0.4% in Kuhar Michael watershed From Kuhar Michael and Lenche Dima of Blue Nile and Awash Basins of Ethiopia from 1972 - 2005. On the other hand, it differs from Nurelegn and Amare (2014) shows the, wet lands increased by 66.3% in Rib Watershed, North Western Ethiopia from 1973 - 2011.

- 30 -

4.3 Accuracy Assessment

To verify to what extent the produced classification is compatible with what actually exists on the ground it is important to evaluate the accuracy of classification results. Accordingly error matrix was produced for all images in this study. An error matrix is a square array of rows and columns and presents the relationship between the classes in the classified and reference data. The reference data used for accuracy assessment were obtained from GPS points during field work and original mosaic image. The GPS points used in classification accuracy assessment were independent of the ground truths used in the classification. Based on the error matrix overall accuracy and kappa statistics were used to illustrate the classification accuracy. Therefore an overall accuracy of 85.06%, 85.1%, 85.3% and 85.5% was achieved for the Landsat TM of 1989 and 19999; Landsat ETM+ of 2009 and Landsat OLI/TIRS of 2019 respectively. Cohen suggested the Kappa result be interpreted as follows: values ≤ 0 as indicating no agreement and 0.1–0 .20 as none to slight, 0 .21–0 .40 as fair, 0. 41–0 .60 as moderate, 0 .61–0 80 as substantial, and 0 .81–1 .00 as almost perfect agreement (McHugh M L, 2012). For this study the kappa coefficient values of 1989, 1999, 2009 and 2019 were 0.81, 0.822, 0 .82 &0.81, respectively which was as almost perfect agreement (Appendix10).

4.4 Tree Based Land Use Changes on Household Incomes and Land Productivity

Productivity was measured as total biomass production and total income obtained from each land use types. This total productivity of different land uses were quantified based on samples taken after each land use stands production. In this study the total productivity of crop land, grazing land and the Eucalyptus globules based) land use system were analyzed.

4.4.1 Productivity of crop based land use

Productivity of wheat yield and straw yield was sampled to calculate total productivity of crop land on different location of the study area. Table 4.2 shows that the estimated mean value of wheat yield 32.925(quintal /ha) and wheat straw 69.765(quintal/ ha) and its average monetary value in Ethiopian Birr were calculated. The minimum value for wheat yield was found to be30.9quntal/ha-1yr-1 and the maximum yield was 32.5 quintal/ ha-1yr-1.

- 31 -

Whereas,65quntal /ha-1yr-1was recorded as a lowest wheat straw yield and 73.8 /quintal /ha-1yr-1 as a highest straw yield Table 4.6 shows the maximum value of wheat grain yield and wheat straw yield were 35,100birr ha-1yr-1& 6,642 birrha-1yr-1, respectively, Whereas, the minimum monetary values of wheat yield and straw yield in 2019 was 33,372 birrha-1 and 5850 birrha-1, respectively.

Table 4.2 Productivity of wheat yield, straw yield and its monetary value in Ethiopian Birr Wheat wheat wheat yield wheat yield strawyield strawyield Cases (quintal/ha/yr. (birr/ha/5yr (quintal/ha/yr. (birr/ha/5yr total birr Awuzet 30.9 166860 69.96 31482 198342 Siharina 32.3 175500 73.8 33210 208710 Wowmagerat 31 167400 65 29250 196650 Hiruyabaargawi 32.5 175500 70.3 31635 207135 Mean 31.725 171315 69.765 31394.25 202709.25

*One quintal is equivalent of 100 kg. The dried straw is densely packed in sheet /leather or skin),

NB; Current Average price of 1quntal wheat =1080 birr; average price of 1 quintal (100kg) straw yield = 90 birr

4.4.2 Productivity of grazing based land use Productivity of grazing land was analyzed by sampling of pasture/grass yield on different location of the district. Table 4.8shows that the mean value of pasture yield (quintal/ha) and the corresponding values of each case in Ethiopian Birr. As the Table 4.3 indicates for one year rotation of pasture yield the lowest value was 57 quintal/ha with a highest value of 85 quintal /ha. The total productivity of grazing land for a single year resulted in minimum amount of 8,550 birr ha-1yr-1, maximum value of 12.750 birr ha-1yr-1 and average value of 11,118.75 birr ha-1yr-1 (Table 4.3; Appendix 4)

- 32 -

Table 4.3 Grazing land productivity and its monetary value in Ethiopian Birr. pasture yield pasture yield pasture yield Cases (quintal/ha/yr. (birr/ha/yr (birr/ha/5yr Awuzet 76 11400 57000 Siharina 78.5 11775 58575 Wowmagerat 85 12750 63750 Hiruyabaargawi 57 8550 45750 Mean 74.125 11118.5 55593.75 N.B; Current Average price of one Quintal fodder or pasture yield is 150 birr.

4.4.3 Productivity of Eucalyptus globulus based land use

Productivity of plantation land was analyzed by sampling of Eucalyptus globulus yield on different location of the district. Table 4.9 shows that the mean value of Eucalyptus globulus meter3/ha) and the corresponding values of each case in Ethiopian Birr. As the Table 4.4 indicates for five year rotation of Eucalyptus globulus the lowest value was108 meter3/ha) with a highest value of 126 meter3/ha). The total productivity of Eucalyptus globulus land for a five year resulted in minimum amount of 532,116 birr ha-5-5, maximum value of 620,802 birr ha-5yr-5 and average value of 580154 birr ha-5yr-5.\.

Table 4.4 Productivity of Eucalyptus globulus land use and its monetary value in Ethiopian Birr

Cases Eucalyptusglobulus Eucalyptusglobulus yield (meter3/ha/5yr yield (birr/ha/5yr

Awuzet 126 620,802

Siharina 115 566,605

Wowmagerat 122 601,094

Hiruyabaargawi 108 532,116

Mean 117.75 580,154

N.B; Current Average price of one meter 3 Eucalyptus globulus be is 4927 birr

- 33 -

4.5 Cost-benefit analysis (CBA) During cost-benefit analysis, total costs required for the production of valuable products at each land use was accounted. The considered costs of the production of crops at cropland was seed cost, labour cost (from land preparation to harvesting and threshing) and fertilizer costs. (Appendix, 4).Cost of grazing land was mainly labor in harvesting and transporting the fodder (Appendix, 5). Similarly costs for Eucalyptus globulus land was includes cost of seedling, land preparation, planting, managing the trees in the field, and others (Appendix, 6).

Based on Table 4.5 the net benefit gained from Eucalyptus globulus land was as large as 431,224.75 birrha-15yr-1 and 530,490.25 birrha-15yr-1 (4.1% and14.57% over the wheat (crop) land and over the grazing land, respectively. Therefore, Eucalyptus globulus significantly increase income 4.1% and14.57% fold greater than crop grazing land system. This study is similar with Jagger et al. (2005) shown that Eucalyptus globulus yields benefit was higher by 20% than producing annual crops in Tigray. Similarly Daba, (1998) also shown that Net Present Value from Eucalyptus globulus range from 11,945 – 749,665 Birr/ha financially 10 fold greater than barley and wheat. Therefore, the role of Eucalyptus globulus has a vital role on total productivity and household income of farmers in the Farta district.

- 34 -

Table 4.5 Cost benefit analysis of different land uses

Eucalyptus Crop Land use Grazing Land use globulus Land use

Gross income birr/5yr) 202,708.25 55,593.75 580,154

Gross cost ((birr/5yr) 64,050 16,500 10,270

Benefit (birr/5yr) 138,659.25 39,093.75 569,884

Income per year 27,731.85 7,818.75 113,976.80 (See Appendix 1-6 for the detail)

4.6 Land Equivalent Ratio (LER)

Table 4.6 Land equivalent ratio of different land use type

Net income Remark Land use (ETB)(GMP-GMC) LER LER values

Cropland (wheat) land use 138,659.25 1 =1, no change

Grazing land use 39,093.75 0.28 <1, crop land is better

E. globulus based land use 569,884 4.1 >1, crop land is lesser

N.B; GM p-Gross Mean Profit, GM c-Gross Mean Cost

LER -land equivalent ratio

LER= x land use / Cropland use

Where, x is grazing and Eucalyptus globulus based land use

- 35 -

LER is a ratio that indicates the amount of land required to grow both crops together relative to the amount of land needed to grow sole crop of each and give the same yield (Amanullah et al, 2016). A LER value of 1.0, indicates no difference in yield between the intercrop and the collection of mono cultures. The LER with value greater than 1.0 indicates that intercropping is advantageous .whereas the LER less than 1.0 shows that intercropping is disadvantageous .A LER of 0.28, indicates that grazing land use was having -0. 72% disadvantageous of the sole crop land wheat) land use system. Therefore, grazing based land use system is less efficient/economical than the crop land (wheat) land use system. While, LER of 4.1, indicates that Eucalyptus globulus based cropping was having 301% advantage over the sole crop land wheat) land use system. Therefore, Eucalyptus globulus based land use system is more efficient/economical than the crop land (wheat) land use system.

- 36 -

CHAPTER FIVE.

CONCLUSIONS AND RECOMMENDATIONS

5.1 Conclusions

Eucalyptus globulus taken a land use change in farta district that is from crop based land use farming system to Eucalyptus globulus based farming system. Land use/cover changes that have been occurring in the last 30 years indicated that the area under, wetland, grazing land, natural forest and bare lands were declining. On the other hand, cultivated land, plantation, water body and settlement lands were expanding. Therefore, Eucalyptus globulus is changing the land use system of the district.

, Based on land equivalent ratio values Eucalyptus globulus based cropping was found to be the leading land use type in securing profitable income for the farmers. Due to this farmers are now changing their various land uses to Eucalyptus globulus land use. Also, many studies confirmed that planting Eucalyptus globulus in degraded farm and bare lands had multiple advantages including successful ecological restoration, Trees protect water resources by enhancing hydrological functions of landscapes and help combat the drying of the land (desertification) and foster species that nurse the rapid re-colonization of native species. Currently much of the farm lands are changed to Eucalyptus globulus tree plantation and this could have serious competition on the production of food crops and on the country’s food security program. Therefore, evaluating and making continuous land use/cover change studies is very important to forecast future developments and finding new alternative initiatives that have more advantage to the farmers’ income, ecological and environmental sustainability and acceptable by the community.

- 37 -

5.2. Recommendations  Later the expansion of the Eucalyptus globulus tree based plantation has serious competition on the food crop production and further impact the food security goal of the district, researchers shall develop another initiatives that meet the sustainable functions of lands .  . Policy makers and development actors need to consider credit provision to farmers to fill the income gap that will be created during the transformation of land use from crop to tree farming.

- 38 -

6. REFERENCES

Aadil Manzoor Nanda, Rafiq Ahmad Hajam, Aadil Hamid and Pervez Ahmed. 2014. Changes in land-use/land-cover dynamics using geospatial techniques: A case study of Vishav drainage basin Vol. 7(4), pp. 69-77.

Abate Shiferaw and K.L.Singh.2011.Evaluating Land Use and Land Cover Dynamics in BorenaWoreda, SouthWollo Highlands, and EthiopiaEJBEVol.2 No.

Abayneh, .2017. Characterization and Mapping of Soils of Farta.

Abebe Senamaw Kebede 2018 Assessment of Land Use/ Land Cover Change Using GISand Remote Sensing Techniques: A Case Study of Dendi District, Oromiya Regiona State, Ethiopia Department of Disaster Risk Management and Sustainable Development, Ambo University, Ethiopia journal of Environment and Earth Science www.iiste.org ISSN 2224- 3216 (Paper) ISSN 2225-0948 (Online) Vol.8, No.1, 123

Abyot Yismaw, Birhanu Gedif, Solomon Addisu Ferede Zewudu .2014 .Forest cover change detection using remote sensing and GIS in Banja district, Amhara region, Ethiopia International Journal of Environmental Monitoring and Analysis; 2(6): 354-360

Adane Mezgebu Nigussie .2016. Land Use/Land Cover Changes and Associated Driving Forces In Bale Eco-Region, Ethiopia M.Sc. Thesis

Adubofour Frimpong. 2011 .Application of Remote Sensing and GIS for Forest Cover Change Detection (A case study of Owabi Catchment in Kumasi, Ghana)

Adedeji, O. H., Tope-Ajayi, O. O. and Abegunde, O. L. 2015.Assessing and Predicting Changes in the Status of Gambari Forest Reserve, Nigeria Using Remote Sensing and GIS Techniques. Journal of Geographic Information System (7): 301-318

Amanullah KF, Muhammad H, Jan AU, Ali G.2016. Land Equivalent Ratio, Growth, Yield and Yield Components Response of Mono-cropped vs. Intercropped Common Bean and Maize

- 39 -

With and Without Compost Application. Agriculture and Biology Journal of North America, 7(2), 40-49 Amare, B. 2007. Landscape transformation and opportunities for sustainable land management along the eastern escarpment of Wello (EEW). Doctoral thesis, University Bern.

Alemu, B., Garedew, E., Eshetu, Z. and Kassa, H. 2015. Land Use and Land Cover Changes and Associated Driving Forces in North Western Lowlands of Ethiopia. International Research Journal of Agricultural Science and Soil Science 5(1): 28-44.

Anderson. J. 1976. A Land use and land cover classification system for use with Remote Sensor Data. Geological Survey Professional Paper No. 964, U.S. Government Printing Office, Washington D.C.

Aramde Fetene, Demelash Alem and Yosef Mamo .2014. Effects of Land use and Land Cover Changes on the Extent and Distribution of Afroalpine Vegetation of Northern Western Ethiopia: The Case of Choke Mountains Volume 8 (1): 17-28,

Assaye Asnake. 2002. Yield and Economics of Growing Eucalyptus camaldulensis by Small holder Farmers of Amhara Region: The Case of Gondar Zuria District, North Gondar,Ethiopia. MSc thesis, ISSN 1402-201X (2002:57). Swedish University of Agricultura Sciences, Skinnskatteberg, Sweden.

Assefa, Sisay and Zegeye, Tesfaye. 2003. Rural Poverty, Food Insecurity and Environmental Degradation in Ethiopia: A case Study from South Central Ethiopia, Paper for Presentation at the 2nd EAF/IDR International Symposium on Contemporary Development Issues in Ethiopia, Addis Ababa, Ethiopia

Azene Bekele. 2007. Useful trees of Ethiopia: Identification, Propagation and Management in 17 Agro Ecological Zones. Nairobi: RELMA in ICRAF project, 552p

Babu RC, OS Kandasamy. 1997. Allelopathic effects of Eucalyptus globulus Labill on Cyperus Rotundus L. and Cynodol dactaylon L. Pers. Journal of Agronomy and Crop Science 179, 123-126.

- 40 -

Behailu assefa.2010. Land Use and Land Cover Analysis and Modeling in South Western Ethiopia: The Case of Selected Resettlement Kebles in Gimbo Woreda MSc. thesis, Addis Ababa University, Ethiopia. Belay, T. 2002. Land cover/land use change in the Derekolli Catchment, South Wolo Zone of Amhara Region, Ethiopia. Eastern Africa Social Science Research Review XVIII, No.1:1-20 Billah M. and Anisur R. Gazed .2004. Land Cover Mapping of Khulna City Applying Remote Sensing Technique. Proc. 12th Int. Conf. on Geo-informatics − Geospatial Information Research: Bridging the Pacific and Atlantic University of Gävle, Sweden, 7-9 Burka, A. 2008. Land Use /Land Cover Dynamics in Prosopis juliflora invaded area of Metehar and the Surrounding Districts Using Remote Sensing & GIS Techniques. MSc. thesis, AddisAbaba University, Ethiopia. Briassoulis, H. 2000. Analysis of Land Use Change: Theoretical and Modeling Approaches. Regional Research Institute, West Virginia University, Morgantown, WV. Bierregaard, R., Gascon, C., Lovejoy, T.E. and Mesquita, R. 2000. The Regional Research Institute, West Virginia University, Morgantown, WV.ecology and conservation of Fragmented forest, Lesson from Amazonia Briassoulis, H. 2011. Factors Influencing Land Use Land Cover Change. Journal of Land Use, Land Cover and Soil Science1. Brown, D. G., Pijanowski, B. C. and Duh, J. D. 2000. Modeling the Relationships between LandUse and Land Cover on Private Lands in the Upper Midwest, USA. Journal of Environmental Management (59): 000–000, available onlineathttp://www.idealibrary.com Buchbauer G. 2000.The detailed analysis of essential oils leads to the understanding of the Properties. Perfumer and flavourist. Burrough, P. A., and McDonnell, R. (1998). Principles of geographical information systems, Oxford University Press, Oxford. Campbell, J. B., 1987, Introduction to Remote Sensing. The Guilford Press, New York Codjoe Samuel N.A. 2007. Integrating Remote Sensing, GIS, Census, and Socioeconomic Data in studying the Population. Land Use/Cover Nexus in Ghana: A Literature Update. Africa Development, Vol. XXXII, No. 2

- 41 -

Campbell, J. B., 2006, Introduction to Remote Sensing. Taylor and Francis, London Development, Vol. XXXII, No.1 Congalton, R.G., 1991. A review of assessing the accuracy of classifications of remotely sensed data, Remote Sensing of Environment, 37:35-46. Crummey, D. 1998. Deforestation in Wollo: Process or illusion? Journal of Ethiopian Studies31No. 1: 1–4 Daba Wirtu. 1998. The economics of growing E. globulus (labill.) in the highlands of OromiyaEthiopia. MSc thesis, Swedish University of Agricultural Sciences, Skinnskatteberg, Sweden. Daniel Ayalew Mengistu.2008.Remote sensing and GIs-based Land use and land cover change detection in the upper Dijo river catchment, Silte zone, southern Ethiopia. Demamu Mesfin. 2002. Economic analysis of E. globulus plantation in the former Dessie fuel wood project, South Wollo, Ethiopia. MSc thesis, Swedish University of Agriculture Sciences, Skinnskatteberg, Sweden . Demel Teketay, 2000. Facts and experiences on eucalypts in Ethiopia and elsewhere: Ground for making wise and informed decision. Walia 21, 25-46. Demel Teketay, Mulugeta Lemenih, Tesfaye Bekele, Yonas Yemshaw, Sisay Feleke, Wubalem Tadesse, Yitebitu Moges, Tesfaye Hunde, Demeke Nigussie. 2010. Forest Resources and Challenges of Sustainable Forest Management and Conservation in Ethiopia. In: Bongers F,,Tennigkeit T (Eds). Degraded forests in Eastern Africa: management and restoration. Earth scan Publ. Pp. 19-63. Demers, M. N. 2005. Fundamentals of Geographic Information Systems, John Wiley&Sons, Inc.,Newyork, USA Dereje Jenbere. 2009. The expansion of Eucalyptus plantation by small holder farmers and its drivers: the case of Arsi Negelle district, southern Oromia Ethiopia. MSc thesis, Hawassa University, Wondo Genet College of Forestry and Natural Resources, Awassa. De Sherbinin, A. 2002. Land-Use and Land-Cover Change, A CIESIN Thematic Guide, Palisades, .Dixit A, Rohilla A, Singh V. 2012; Eucalyptus globulus: A new perspective in therapeutics. Int J Pharm Chem Sci 1(4): 1678-83.

- 42 -

Dwivedi, R.S.; Sreenivas K.; Ramana, K.V. 2005, Land-use/land-cover change analysis in part of Ethiopia using Landsat Thematic Mapper data. International Journal of Remote Sensing 26 (7). 1285-1287 Egawa H, Tsutsui O, Tatsuyama K, Hatta T.2001.Antifungal substances found in leavesofEucalyptuspecies.Experientia1933. Ejemeyovwi, Danny Ochuko .2015. Change Detection in Land use / Land cover Mapping In Asaba, Niger Delta B/W 1996 And 2015. A Remote Sensing and GIs Approach Faculty of the Social Sciences, Department of Geog. & Reg. Planning, Delta State University, P.M.B. Abraka, Delta State, Nigeria Vol.3, No.3, pp.42-61 Elliot WR, Jones DL. 1984. Encyclopedia of Australian plants suitable for cultivation. Melbourne. Ellis, E. 2007 Conserving Nature in an Anthropogenic Biosphere. Date modified November 30th, 2007. Ellis, E.; Robert P. and Cutler J. 2009. "Land-cover". In: Encyclopedia of Earth.Eds.Cleveland Washington, D.C.: Environmental Information Coalition, National Council for Science and the Environment). First published in the Encyclopedia Ellis E, Pontius Jr RG (2006) land-use and land-cover change encyclopedia of earth. Available at: http://www.eoearth.org/article/land-use_and_land-cover_change Ellis E.2011. Land-use and land-cover change. Encyclopedia of Earth. Available at http://www.eoearth.org/article/Land-use_and_land-cover_change. Emadodin, L., Reiss, S., & Bork, H.R.2009 .A Study of the Relationship between Land Management and Soil Aggregate Stability: Case Study near Albersdorf, Northern Germany. J. Agrie. Biol. Sci., 4, 48-53. Environment Protection Authority (EPA). 2007. “Ethiopia Environment Outlook: Environment For Development”, Addis Ababa, Ethiopia Eshetu, Z. and Hogberg, P. 2000. Reconstruction of forest site history in Ethiopian highlands based On C13 natural abundance of soils. Ambio (29): 83–89. Eyayu Molla, Heluf Gebrekidan , Tekalign Mamo and Mohammed Assen .2010 .Patterns Of Land Use/Cover Dynamics in the Mountain Landscape of Tara Gedam and Adjacent Agro- Ecosystem, Northwest Ethiopia Ethiop. J. Sci., 33(2): 75–88.

- 43 -

FAO, 1988. The Eucalypt Dilemma. FAO, Rome Food and Agriculture Organization (FAO). 1995. Planning for Sustainable Use of Land Resources. FAO Land and Water Bulletin 2. Rome: Food and Agriculture Organization of the United Nations. FAO .1998. Rural Non-Farm Income in Developing Countries. In: Tucker, R. (Ed.) the State of Food and Agriculture, Rome: The Food and Agriculture Organization of the United Nations. pp. 283-351 FAO .2000. Land Cover Classification System (LCCS): Classification Concepts and User Manual,FAO:Rome,http://www.fao.org/docrep/003/x0596e/X0596e00.htm#P-1_0 FAO .2005. Global Forest Resources Assessment. Progress towards sustainable forest Management. FAO forestry paper 147[online]. Rome: Food and Agriculture Organization ofTheUnitedNatio[online].Availablfromhttp://www.fao.org/DOCREP/008/a0400e/a0400e00. htm. Fentahun, Surafel, Berihun and Habtemariam: 2016 Impacts of Smallholder Tree Plantation in Amhara Region of Ethiopia: The Case of Lay Gayint and Fagta Locuma Districts Ethiopian Journal of Economics Vol. XXV No 1. Garedew, E. 2010. Land-Use and Land-Cover Dynamics and Rural Livelihood Perspectives, in the Semi-Arid Areas of Central Rift Valley of Ethiopia. Doctoral thesis, Swedish University Of Agricultural Sciences, Umea. Gashaw, T. and Dinkayoh, T. 2015. Land use/land Cover Dynamics in Hulet Wogedamea Kebele Northern Ethiopia. Current Research in Agricultural Sciences 2(1): 36-4 Gebrekidan Worku1, Amare Bantider and Habtamu Temesgen. 2014. Land use and land cover Change in Ameleke Watershed, South Ethiopia Journal of Natural Sciences Research www.iiste.org ISSN 2224-3186 (Paper) ISSN 2225-0921 (Online) Vol.4, No.14, Geist, H. J. and Lambin, E. F. 2002. Proximate Causes and Underlying Driving Forces of Tropical. Deforestation. Bioscience 52(2): 143-150. Getachew Fisseha, Heluf Gebrekidan, Kibebew Kibret, Birru Yitaferu, Bobe Bedadi 2011, Analysis of land use/land cover changes in the Debre-Mewi watershed at the upper Getecatchment of the Blue Nile Basin, Northwest Ethiopia Vol. 1, No. 6, p. 184-198, .

- 44 -

Gete, Z. 1997. Land Use/Land Cover Maps of Dembecha Area, Gojam, Ethiopia. Centre for Development and Environment, University of Berne, Berne. Gil L. Tadesse W, Tolosana E & López R, Eds .2010. Eucalyptus Species Management, History, Status and Trends in Ethiopia. Proceedings from the Congress held in Addis Ababa. September 15th-17th, 2010 Global Strategy to Improve Agricultural and Rural Statistics .2016. Information on Land in the Context of Agricultural Statistics, http://gsars.org/en/information-on-land-in-the-context-of Agricultural-statistics/. Guerschman J.P.; Paruelo, J.M.; Bela, C.D.; Giallorenzi, M.C.; Pacin, F. 2003. Land cover assification in the Argentine Pampas using multi-temporal Landsat TM data. International Journal of Remote Sensing 24, 3381–3402. Haileab Zegeye1, 2010 .Environmental and Socio-economic Implications of Eucalyptus in Ethiopia Hurni, H., 1985. Soil Conservation Manual for Ethiopia. First Draft. Ministry of Agriculture, Natural Resources Conservation and Development Department, Community Forests and Soil Conservation Development Department. Addis Ababa. Houghton, R. A. 1994. The world wide of extent of land-use change. Bioscience (44): 305-313 Hussein Ali Oumer, 2009. Land Use and Land Cover Change, Drivers and Its Impact: A Comparative Study from Kuhar Michael and Lenche Dima of Blue Nile and Awash Basins Of Ethiopia Thesis Presented to the Faculty of the Graduate Schoo of Cornell University. Jagger P, J Pender, Berhanu Gebremedhin. 2005. Trading Off Environmental Sustainability Empowerment and Income: Woodlot Devolution in Northern Ethiopia. World Development 33: 1491–1510.

Jarvie JK, MacKinnon K, MonkKA. 2001. The end for Indonesia’s lowland forests? Science292:859–6. Jiya George, Linda Baby, Anjaly P Arickal, Jose Dev Vattoly.2016. Land Use/ Land Cover, Mapping With Change Detection Analysis of Aluva Taluk Using Remote Sensing and GIS International Journal of Science, Engineering and Technology, Volume 4 Issue 2ISS (Online): 2348-4098.

- 45 -

Joseph. M. Maitima, J.M Olson, S. M. Mugatha, S. Mugisha and I. T. Mutie, 2010. Land Use Changes, Impacts and Options for Sustaining Productivity and Livelihoods in the Basin O Lake Victoria. Journal of Sustainable Development in Africa: 12:3. Clarion University o Pennsylvania, Clarion, Pennsylvania. Kanyamanda Kasereka Gu Yansheng Innocent Ndoh Mbue Mamadou Samake .2010 .Remote Sensing and Geographic Information System for Inferring Land Cover and Land Use Change In Wuhan (China), 1987-2006 Vol. 3, No. 2; Kebrom Tekle and Hedlund, L., 2000. Land Cover Changes between 1958 and 1986 in Kalu District, southern Wello, Ethiopia. Mountain Research and Development. 20: 42-51.

Kidanu S, T Mamo, L Stroosnijder. 2004. Eucalyptus–wheat interaction on Ethiopian Nitosols.Agricultural Systems 80, 151–170.

Kindu M, G Glatzel, Y Tadesse, A Yosef. 2006. Tree species screened on Nitosols of Central Ethiopia: biomass production, nutrient contents and effect on soil nitrogen. Journal of Tropical Forest Science 18(3), 173–180.

Kindu, M., Schneider, T., Teketay, D. and Knoke, T. 2013. Land Use/Land Cover Change Analysis Using Object-Based Classification Approach in Munessa-Shashemene Landscape of the Ethiopian Highlands. Journal of Remote Sensing (5): 2411-2. Lambin. E.F., Geist. H.J. and Lepers. E. 2003.Dynamics of land-use and land cover change in tropical regions. Annu. Rev. Environ. Resour28: 205–241. Lambin, E.F. & Geist, H. (2006). Land-use and land-cover change: local processes and global Impacts. The IGBP series 1619-2435. Berlin: Sprin. Lambin, E. F. and Geist, H. J. 2007. Causes of land-use and land-cover change. Retrieved from http://www.eoearth.org/view/article/51cbed2f7896bb431f6905af. Lambin, E. F., & Geist, H. J. 2008. Land-use and land cover change: Local processes and global Impacts .Springer Science & Business Media, Germany. Lamichhane, B. B. 2008. Dynamics and Driving Forces of Land Use/Forest Cover Change and Indication of Climate Change in a Mountain Sub-watershed of Gorkha. MSc. thesis, Tribhuvan University, Institute of Forestry, Nepal.

- 46 -

Leh M., S. Bajwa, and I. Chaubey, 2011. Impact of Land Use Change on Erosion Risk: AnIntegrated Remote Sensing, Geographic Information System and Modeling Methodology. Land Degradation & Development. John Wiley & Sons, Ltd. Lillesand, T. M., and Kiefer, R. W. 1987. Remote Sensing and Image Interpretation,Wiley, New York) Lille sand, T.M.; Kiefer, R.W.and Chipman, J.W.2004.Remote sensing and image interpretation,John Wiley & Son, New York, USA

Lisanework N, A Michelsen. 1993. Allelopathy in agroforestry systems: the effect of leaf extracts of Cupressus lustanica and three Eucalyptus spps. on four Ethiopian crops. groforestry Systems 21, 63-74..

Mathewos Muke1 and Bewuketu Haile .2018. Land-use/cover change analysis using Remote Sensing techniques in the landscape of Majang Zone of Gam.

May F, A Ash. 1990. An assessment of the allelopathic potential of Eucalyptus. Australian Journal of Botany 38, 245–254.

McHugh M L, 2012.Interrater reliability: the kappa statisticBiochemia Medica; 22(3):276-82 Mekonnen Z, K Habtemariam, L Mulugeta, B Campbell. 2007. The role and management of Eucalyptus in Lode Hetosa District, Central Ethiopia. Forests, Trees and Livelihoods 17 (4):309-323 Melaku, B. 2003. Forest property rights, the role of the state and institutional exigency: The. Ethiopian experience. Doctoral thesis, Swedish University of Agricultural SciencesUppsala. Melese Worku1and Setechigne Deribew.2018. The Cause of Land Use Change and Effect of the Change on Crop Yield in case of Azezo Tekle Haymanot Kebele Mengistie Kindu, Thomas Schneider, Demel Teketay and Thomas Knoke. 2013, Land Use/Land Cover Change Analysis Using Object-Based Classification Approach in Muness Shashemene Landscape of the Ethiopian Highlands Remote Sens. 5, 2411-2435. Meyer, W. B. and Turner, B. L. II, 1992. Human Population Growth and Global Land Use/Cover Change. Annual Review of Ecology and Systematics (23): 39-57 Meyer W.B. and Turner B.L. II.1994. Changes in Land Use and Land Cover: A Global Perspective. 713 pp. Cambridge: Cambridge University Press [This is an important

- 47 -

contribution that examines methodological and data issues and reports on the human driving forces and consequences of major land-use and land-cover changes.]. Meyer, W. B. 1995. Past and Present Land-Use and Land –Cover in the U.S.A. Consequences.24-33. Meyer W.B., Turner B.L., 1996.Land use land cover change: challenges for geographers, Minale, A. S. 2012. Population and Environment Interaction: the case of Gilgel AbbayCatchment, Northwestern Ethiopia. Journal of Environmental Research a Management 4(1): 0153-0162 Molla, M. B. 2014. Land Use/ land cover dynamics in the Central Rift Valley Region of Ethiopia The Case of Arsi Negele District. Academia Journal of Environmental. Mohammed Assen and Tassew Nigussie.2009. Land Use/Cover Changes between 1966 and 1996 in Chirokella Micro-watershed, Southeastern Ethiopia Journal of Sciences (Volume 3 (1)1-8 Mohammed Mussa1, Habtamu Teka1 and Yared Mesfin .2017.Land use/cover change analysis and Bale rangelands, Southeast Ethiopia International Journal of Biodiversity and Conservatio vol. 9(12). Mulatie Mekonnen, Tsegaye Sewunet, Samson G/Mariam and Amare Sewnet. 2016. GIS and remote sensing based assessment of eucalyptus and a decurrense expansion over cropland from 1985-2016, western Amhara, Ethiopia. Mulugeta Lemenih, Demel Teketay, 2004. Restoration of native forest flora in the degraded highlands of Ethiopia: Constraints and opportunities. SINET: Ethiopian Journal of Science27 (1), 75-90. Muluneh, W. 2003. Population growth and environmental recovery: More people, more trees: Lesson learned from Western Gurage land. Ethiopian Journal of Social Sciences and Humanities Vol. 1, No.1 ISSN: 1810-4487, 1-33. Muluneh, W. 2003. Impact of Population Pressure on Land Use and Land Cover Changes Agricultural System and Income Diversification in West Gurague Land, Ethiopia Doctoral thesis, Norwegian university of science and technology (NTNU), Trondheim.

- 48 -

Nagendra, H., Munroe, D., South worth, J., 2004, Introduction to the special issue: From pattern to process: Landscape fragmentation and the analysis of land use/land cover change. Agriculture, Ecosystems and Environment 101:111–11 Nawir, A. A., Kasha, H., Sidewall, M., Dore, D., Campbell, B., Olsson, B. and Bekele M. 2007. “Stimulating smallholder tree planting lessons from Africa and Asia”, Unasylva 228, Vol. 58

Negussie Achalu. 2004. Farm Forestry decision making strategies of the Guraghe household Southern-Central highlands of Ethiopia. PhD Dissertation. Institute for International Forest and Holzwirtschaft Technische Universities Dresden.

Nurelegn Mekuriaw Garede and Amare Sewnet Minale.2014. Land Use/Cover Dynamics in Ribb Watershed, North Western Ethiopia Journal of Natural Sciences Researchwww.iiste.org ISSN 2224-3186 (Paper) ISSN 2225-0921 (Online) Vol.4,

Paul, W. B. and Lisa, A. S. 2011. Agricultural landscape change (1937–2002) in three town ships in Iowa, USA. Landscape and urban planning (100): 202–212.

Patterson, K. 2007. Integrating Population, Health, and Environment in Ethiopia Population Reference Bureau.

Prabhakar VK. 1998. Social and Community Forestry. Satish Garg, New Delhi, 316p

Prakasam C (2010). Land use and land cover change detection through remote sensing approach: A case study of Kodaikanal taluk, Tamil nadu. International journal of Geomatics and Geosciences, 1(2): 150-158

Rahdary, V., Soffianian, A., Najfabdai, S. M., Khajeddin, S. J. and Pahlavanravi, 2008. Land Use and Land Cover Change Detection of Mouteh Wildlife Refuge Using Remotely Sensed Data and Geographic Information System. World Applied Sciences Journal 3(1): 113-118

Rembold, F., Carnicelli, S., Nori, M. & Ferrari, G.A. 2000. Use of aerial photographs, Landsat TM imagery and multidisciplinary field survey for land-cover change analysis in the lakes.

- 49 -

region, Ethiopia. International Journal of Applied Earth Observation andGeoinformation. Vol. 2, Issue 3/4, 181-189.34. Rogana J.; Chen, D. 2004, Remote sensing technology for mapping and monitoring land-cover and land use change. Progress in Planning 61, 301–3 Sall, M. 2014. Land-based Adaptation and Resilience Powered by Nature. FJ. Analgesic and anti- inflammatory effects of essential oils of Eucalyptus. JEthnopharmacol 2003; 89(2-3): Samuale Tesfaye, Etefa Guyassa, Antony Joseph Raj, Emiru Birhane and Gebeyehu Taye Wondim.2014. Land Use and Land Cover Change, and Woody Vegetation Diversity in Human Driven Landscape of Gilgel Tekeze Catchment, Northern Ethiopia Selçuk Reis 2008.Analyzing Land Use/Land Cover Changes Using Remote Sensing and GIS in Rize, North-East Turkey Shiferaw, A. 2011. Evaluating the Land Use and Land Cover Dynamics in Borena Woreda of South Wollo Highlands, Ethiopia. Journal of Sustainable Development in Africa 13 (1): 87- 107 Tefera, M. M. 2011. Land-use/land-cover Dynamics in Nonno District, Central Ethiopia. Journal Of Sustainable Development in Africa 13(1): 123-14 Tsegaye, L. 2014. Analysis of Land Use and Land Cover Change and Its Drivers Using GIS and Remote Sensing: The Case of West Guna Mountain, Ethiopia. International Journal of Remote Sensing and GIS 3(3): 53-63 Turner, II B. L. and Meyer, W. B. 1994. Global land-use and land-cover change: An overview. In changes in land-use and land-cover: A global perspective. Cambridge: Cambridge University Press. 3-10 Turner, B. L., Meyer, W. B., & Skole, D. L. (1994). Global land-use/land-cover change: towards an integrated study. Ambio. Stockholm, 23(1), 91-95 Ulbricht, K.A.; Heckendorf, W.D. 1998, Satellite images for recognition of landscape and land use changes. ISPRS Journal of Photogrammetry & Remote Sensing 53, 235-243. Yomralıoğlu, T. Coğrafi Bilgi Sistemleri Temel Kavramlar ve Uygulamalar, 2000 .Seçil Of set, Istanbul, Turkey, United Nations Statistics Division .2017.Framework for the Development of Environment)

- 50 -

Statistics (FDES2013), https://unstats.un.org/unsd/environment/fdes/FDES-2015- support in Tools/FDES.pdf (accessed 17 December 2017 Woldeamlak, B. 2002. Land cover dynamics since the 1950s in Chemoga watershed, Blue Nile Basin, Ethiopia. Mountain Research and Development 22, No. 3: 263–26. Worku M, Deribew S .2018. the Cause of Land Use Change and Effect of the Change on Crop. Yield in Case of Azezo Tekle Haymanot Kebele. J Agri Sci Food Res 9: 21 Wu, Q.; Li, H. Q.;Wang, R.S.; Paulussen, J.; He, H.; Wang, M.; Wang, B.H.; Wang, Z. 2006, Monitoring and predicting land use change in Beijing using remote sensing and GIS. Landscape and Urban Planning 78, 322–333 Verburg, P., Schot, P. P., Dijst, M. J. and Veldkamp, A. 2004. Land use change modelling: current practice and research priorities. GeoJournal (61): 309–324 Vishin A. Patil, Sachin A. Nitave (2014) A Review On Eucalyptus globulus: A Divine Medicinal Herb World Journal of Pharmacy and Pharmaceutical Sciences Volume 3, Issue 6, 559-567. Review Article Issn 2278 – 4357http://www.botanical.com Verheye, W. 2011. Land Cover, Land Use and the Global Change. Journal of Land Use, Land Cover and Soil Science Zeleke and Hurni H., 2001. Implication of Land Use and Land Cover Dynamics for Mountain Resource Degradation in the North-Western Ethiopian Highlands. Journal of Mountain Research and Development. 21(2): 184–191. Zerihun Kebebew. 2002. Profitability and household income contribution of growing Eucalyptus globulus to smallholder farmers. MSc thesis, Swedish University of Agricultural Sciences, kinnskatteberg, Sweden Zhou GY, JD Morris, JH Yan, ZY Yu, SL Peng. 2001. Hydrological impacts of reforestation with Eucalyptus and indigenous species: a case study in southern China. Forest Ecology and Management. 5741, 1–1 Zsuzsanna, D.; Bartholy, J.; Pongracz, R.; Barcza, Z. 2005, Analysis of land-use/land-cover change in the Carpathian region based on remote sensing techniques. Physics and Chemistry of Earth 30,

- 51 -

Appendix 1.Estimated value of wheat and wheat straw yield as crop

wheat wheat yield(quintal/ha/yr) straw(quintal/ha/yr)Mean± Cases Mean± std.Devation std.Devation Awuzet 39.39± 3.64 69.96±8.68 Siharina 32.5.0± 3.7 73.8±5.8 Wowmagerat 31± 4.06 65± 7.77 hiruyabaargawi 32.5±.4.74 70.3±.7.93 Mean 31.725±4.03 69.765±7.54

Appendix 2. Estimated value of pasture yield for grazing land

pasture yield(quintal/ha/yr Cases )Mean± std.Devation Awuzet 76± 5.74 Siharina 78.5.0± 7.79 Wowmagerat 85± 6.59 hiruyabaargawi 57±.4 Mean 74.125±6.03

Appendix 3. Estimated value of Eucalyptus globulus yield for plantation land

Eucalyptus globulus yieldd(quintal/ha/yr)Mean± std.Devation Awuzet 126± 41.3 Siharina 115± 37.05 Wowmagerat 127± 39.11 hiruyabaargawi 108±37.1 Mean 117.75±38.64

- 52 -

Appendix 4 Cost Benefit analysis of crop land (wheat) Gross cost of crop land amount Total cost Gross cost list of cost unit price birr/year birr/year birr5/year labour cost for land preparation 20person 100birr 2000 10000 seed cost 150kg/ha 13birr 1950 9750 Fertilizer cost 200kgha 13.5kg/ha 2700 13500 Weeding 18person 110birr/person/day 1980 9900 Harvesting 20person 110birr/person/day 2200 11000 Trashing 16person 110birr/person/day 1760 8800 transportation cost 2person 110birr/person/day 220 1100 total cost 12810 64050

Gross income of crop land

Average amount of wheat yield 31.725qt/ha 34,263birr/ha/yr. 171,315birr/5yr

Average amount of straw yield 69.765qt/ha 6,278.85birr/ha/yr 31,394.25birr/5yr

Total gross income 40,541.85birr/ha/yr. 202,708.25birr/ha

Net benefit=total income-total cost, 202,708-64,050

138,659.25 birr

N.B; Current Average price of 1 quintal (100kg) wheat straw yield = 90birr

- 53 -

Appendix 5 Cost Benefit analysis of grazing land

Gross cost of pasture land unit total cost gross cost list of cost amount price birr/year birr/year birr5/year

Pasture harvesting &

collecting 20person 110birr/person/day 2200 11000 transportation cost 10person 110birr/person/day 1100 5500 total cost 3300 16500

Gross income of grazing land

Average amount of pasture yield 74.125quntal (birr/ha/yr. 11118.75

Total gross income 55,593.75birr/ha/5yr

Net benefit = total income – total cost, 55.593.75-16,500

39093.75 birr

N.B; Current Average price of 1quntal (100kg) pasture yield = 150.8birr

- 54 -

Appendix 6 Cost analysis of E. globulus based land

Gross cost of E. globulus based land

List of cost Total cost Gross cost Amount Unit price birr/year birr/year birr5/year

Seedling cost 13000seedling 0.35cent/seedling 4550 4550

Seedling transport cost 13person/day 110birr/person/day 1430 1430

Labour cost for planting 26person/day 110birr/person/day 2860 2860

Weeding for seedling 13person/day 110birr/person/day 1430 1430

Total cost 10270 10270

Gross income of Eucalyptus globulus based land

Average amount of Eucalyptus globulus yield meter3117.75mter3/ha5yr / 116030.8birr/ha/yr 580154birr/5yr

Total gross income 580154birr/5yr

Net benefit=total income-total cost, 580,154-10,270

569884 birr

N.B; - Current Average price of 1 meter3 Eucalyptus globulus= 4927biirr

-Eucalyptus globulus sells on the field

- 55 -

Appendix 7 Wheat crop in Awuzet kebele

Appendix 8 grazing area in wowamagerat kebele

Appendix 9 Eucalyptus globulus Awuzet kebele

- 56 -

Appendix 10 Confusion Matrix

Table 4.1 Confusion Matrix for the LULC Map of 1989

reference image

Class - name forest Grazi ng Wetl and cultiv ated Plant ation Bare Settle ment RT UA Forest 10 2 0 0 0 1 0 13 76.92

Grazing 1 18 0 1 0 0 1 21 85.71 Wetland 0 0 5 1 0 0 0 6 83.33 Cultivated 0 1 0 27 1 0 1 30 90 plantation 1 0 1 0 8 1 0 11 72.73 bare land 0 1 0 1 0 15 0 17 88.24 settlement 0 0 0 1 0 8 9 88.89 CT 12 22 6 30 10 17 10 107 classification image classification PA 83.33 81.82 83.33 90.00 80.00 88.24 80.00 over all accuracy% 85.06 kappa coefficient 81.49 NB.CT -column total, PA- producer accuracy, UA- user accuracy, RT- row total

Table 4.2 Confusion Matrix for the LULC Map of 1999

reference image

Class Wetlan d bare land plantati on Grazin g cultivat ed Forestl and Settlem ent RT UA Wetland 35 0 0 1 0 0 0 36 97.22 Bare land 41 0 0 0 1 0 42 97.62 Plantain 0 0 38 0 1 1 0 40 95.00 Grazing land 0 1 0 42 0 0 1 44 95.45

image Cultivated 1 0 0 1 47 0 1 50 94.00 classification classification Forest 0 0 0 0 0 29 1 30 96.67 Settlement 0 0 1 0 1 0 33 35 94.29 CT 36 42 39 44 49 31 36 277 PA 97.22 97.62 97.44 95.45 95.92 93.5 91.67 over all accuracy% 85.1 Kappa coefficient 82.2 NB.CT-column total, PA- producer accuracy, UA- user accuracy, RT- row total

- 57 -

Table 4.4Confusion Matrix for the LULC Map of 2009 reference image

Class Wetl and bare land plant ation Graz ing culti vate d Fore stlan d Settl eme nt RT UA

Wetland 5 1 0 0 0 0 0 6 83.33

Bare land 13 1 0 0 1 1 16 88.89 Plantain 7 0 2 1 0 9 77.78

image Grazing land 0 1 1 25 0 0 0 27 92.59 Cultivated 0 2 0 0 18 1 4 25 72 classification classification Forest 1 0 0 0 1 29 0 31 93.55 Settlement 1 1 1 0 1 1 31 36 86.11 CT 7 18 10 25 23 32 35 150 128 PA 71.4 72.2 70 100 78.26 90.3 88.57 over all accuracy% 85.3

Kappa 82.4 coefficient 9 NB.CT-column total, PA- producer accuracy, UA- user accuracy, RT- row total

Table 4.5 Confusion Matrix for the LULC Map of 2019

reference image

Class grazing land bare land cultivat land ed Plantati on Settlem ent water body Forestl and wetlan d RT UA grazing land 10 4 14 85.43

bare land 8 2 10 80.00 cultivated land 1 48 1 50 96.00 Plantation 1 2 15 1 19 78.95 Settlement 1 1 17 1 20 85.00 water body 5 1 6 83.33 Classification forest land 1 10 1 12 83.33 wetland 2 5 7 71.43 CT 11 10 59 16 19 6 11 6 138 PA 90.91 80.00 81.36 93.75 89.47 83.33 90.91 83.33 over all accuracy% 85.5 kappa coefficient 81.53

NB.CT-column total, PA- producer accuracy, UA- user accuracy, RT- row total

- 58 -

Author’s Biography The author was born in August 1967 in South Gander zone of the Amhara National Regional State, at Simada district Ethiopia. He attend his elementary and, secondary education at Aji primary and Tagel secondary school. After completion of his secondary school he joined to district agricultural center graduate with certificate in development agents in 1997, Alage TVET College graduate with Diploma in Natural resource in2004 and Bahir Dar University graduate with B.Sc. Degree in Natural resource Management in 2011. After graduation he was employed in Simada woreda development agents, supervisor and office expert work processer, South Gonder zone agriculture department forestry expert and Amhara science technology information communication commission environment protection technology transformation expert he joined his M.Sc. Program he was doing environment protection technology transformation expert. Finally, she joined the post graduate studies of Bahir Dar University in June 2019 in the Department of Natural Resource Management of study for his Master of Science degree in environment and climate change.

- 59 -

- 60 -

- 61 -