Human Population Growth and Its Implications on the Use and Trends of Land Resources in Migori County, Kenya

HUMAN POPULATION GROWTH AND ITS IMPLICATIONS ON THE USE AND TRENDS OF LAND RESOURCES IN MIGORI COUNTY, KENYA

PAULINE TOLO OGOLA

A Thesis Submitted in Partial Fulfilment of the Requirements for the Award of the Degree of Master of Environmental Studies (Agroforestry and Rural Development) in the School of Environmental Studies of Kenyatta University

NOVEMBR, 2018

DEDICATION

To my loving parents, Mr. and Mrs. Ogola,

With long life He will satisfy you

ACKNOWLEDGEMENT

First of all, I am grateful to the Man above who gave me strength and health throughout this study. For sure, His goodness and Mercies are new every day.

Secondly, I am greatly indebted to my supervisors Dr. Letema and Dr. Obade for their wise counsel and patience.

Thirdly, I would like to convey my utmost gratitude to my parents and siblings for their moral support and prayers. Special thanks to my brother Stephen Ogeda for supporting me financially.

Finally, I wish to express many thanks to my colleagues at the Regional Centre for Mapping of Resources for Development and friends who have offered their support in kind and deed.

TABLE OF CONTENTS DECLARATION………………………………………………………………………… Error! Bookmark not defined.

DEDICATION…………………………………………………………………………...i

ACKNOWLEDGEMENT……………………………………………………………...ii

LIST OF TABLES……………………………………………………………………...vi

LIST OF FIGURES……………………………………………………………………vii

ABBREVIATIONS AND ACRONYMS……………………………………………….viii

ABSTRACT………………………………………………………………………………i x

CHAPTER ONE: INTRODUCTION…………………………………………………..1

1.1 Background to the Problem ...... 1

1.2 Statement of the Problem ...... 3

1.3 Research Questions ...... 5

1.4 Objectives of the Study ...... 5

1.5 Research Hypothesis ...... 6

1.6 Significance of Study ...... 6

1.7 Scope and Limitations of the Study ...... 7

1.8 Operational Definitions ...... 7

CHAPTER TWO: LITERATURE REVIEW……………………………………...9

2.1 Introduction ...... 9

2.2 Population Increase and Land Resources...... 9

2.3 Land Resources ...... 12

2.3.1 Forestland ...... 12

2.3.2 Cropland ...... 13

2.3.3 Water ...... 14

2.3.4 Land Use Changes ...... 14

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2.2.5 Sustainable Land Resources Management ...... 16

2.2.6 Benefits of Sustainable Land Resources Management ...... 18

2.2.7 Policies and Frameworks that Promote Sustainable Land Resources Management in Kenya ...... 18

2.8 Conceptual Framework ...... 22

2.9 Research Gap ...... 23

CHAPTER THREE: METHODOLOGY…………………………………………….25

3.1 Introduction ...... 25

3.2 Background to the Study Area ...... 25

3.2.1 Location and Extent ...... 25

3.2.2 Population Distribution ...... 26

3.2.3 Climatic Conditions ...... 27

3.2.4 Socio- Economic Activities ...... 28

3.3 Research Design ...... 28

3.4 Sample Size and Sampling Procedure ...... 28

3.5 Data Collection Tools and Procedures ...... 29

3.6 Land Use and Land Cover Methodology ...... 31

3.6.1 Collection and Quality Checking of Ancillary Data ...... 31

3.6.2 Database Development ...... 32

3.6.3 Landsat MSS, Landsat TM, and ETM+ Image Understanding and Acquisition ..... 32

3.6.4 Image Classification...... 35

3.6.5 Ground Reference Data Collection and Accuracy Assessments ...... 38

3.6.6 Accuracy Assessment ...... 40

3.6.7 Change Analysis and Derivation of Statistics ...... 45

3.6.8 Preparation of Final Land Cover and Change Maps ...... 45

3.6.9 Questionnaire Analysis ...... 46

CHAPTER FOUR: RESULTS AND DISCUSSIONS………………………………..47

4.1 Introduction ...... 47

4.2 Human Population Patterns in Migori Sub-county between 1979 and 2013 ...... 47

4.3 Trends and Pattern of Land Resources ...... 54

4.3.1 Land Use and Land Cover Mapping ...... 55

4.3.2 Land Use and Land Cover Change Mapping and Statistics ...... 63

4.3.3 Land Use and Land Cover Change for Epoch 1979-2013 ...... 73

4.3.4 Land Use Activities...... 75

4.4 Relationship between Human Population Growth, Forestland, Cropland and Water Resources in Migori Sub-county from 1979-2013 ...... 79

CHAPTER FIVE: SUMMARY, CONCLUSIONS AND RECOMMENDATIONS.84

5.1 Introduction ...... 84

5.2 Summary of the Findings ...... 84

5. 3 Conclusions ...... 86

5.4 Recommendations ...... 88

5.5 Suggestion for Further Studies ...... 89

REFERENCES………………………………………………………………………….90

APPENDICES…………………………………………………………………………..97

Appendix I: Summary of Questionnaire Details……………………………………...97

Appendix II: Questionnaire for Farmers……………………………………………104

Appendix III: Questionnaire for Ministry of Agriculture Official………………...108

Appendix IV: Questionnaire for Ministry of Water official………………………..111

Appendix V: Field Photos…………………………………………………………….114

Appendix VI: Research Authorization Letter………………………………………116

LIST OF TABLES

Table 3.1: Field verification points……………………………………………..42

Table 3.2: Compliance matrix between interpreter and validation results……...44

Table 4.1: Population data for Homa Bay, Migori and Rongo (79, 89, 99, 09)……………………………………………………………………………….48

Table 4.2: Areas for Waterbody, Cropland and Forestland……………………...63

Table 4.3: Change area for Cropland, Waterbody and Forestland (79-89)...... 66

Table 4.4: Change area for Cropland, Waterbody and Forestland (89-99)...... 69

Table 4.5: Change area for Cropland, Waterbody and Forestland (99-09)...... 72

Table 4.6: Change area for Cropland, Waterbody and Forestland (79-13)...... 75

Table 4.7: Land Use Activities…………...……………………………………...76

Table 4.8: Land Resources Conservation Measures...... 77

Table 4.9: Comparison between population, Cropland, Forestland and Cropland for the years 79, 89, 99 and 09……………….…………………….……80

Table 4.10: T-test results for population and Cropland……………………...... 81

Table 4.11: T-test results for population and Forestland……………………...... 82

Table 4.12: T-test results for population and Waterbody………………..…...... 83

LIST OF FIGURES Figure1.1: Conceptual Framework………………………………………………23

Figure 3.1: Population pyramid of Migori Sub-county………………….…...... 26

Figure 3.2: Location of Migori Sub-county...... 27

Figure 3.3: Image map for 1979, 1989, 1999, 2009 and 2013……………….....34

Figure 3.4: Generated Polygons ………………………………………………..37

Figure 3.5: Field Verification Points…………………………………………...41

Figure 4.1: 2000 Population Map……….………………………….…………...49

Figure 4.2: 2010 Population Map….…….……………………………………...51

Figure 4.3: 2020 Population Map….…….……………………………………...53

Figure 4.4: 1979 LULC Map……………….…………………………………...56

Figure 4.5: 1989 LULC Map …………………………………………………...59

Figure 4.6: 1999 LULC Map ……………………………………………………60

Figure 4.7: 2009 LULC Map ……………………………………………………61

Figure 4.8: 2013 LULC Map…………………………………………………….62

Figure 4.9: 1979-1989 LULC Change Map……………………………………..65

Figure 4.10: 1989-1999 LULC Change Map……………………………………68

Figure 4.11: 1999-2009 LULC Change Map……………………………………71

Figure 4.12: 1979-2013 LULC Change Map……………………………………74

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ABBREVIATIONS AND ACRONYMS

AOI Area of Interest CIA Central Intelligence Agency CIESIN Centre for International Earth Science Information Network ETM Enhanced Thematic Mapper FAO Food and Agriculture Organization of the United Nations GDP Gross Domestic Product GIS Geographic Information Systems GPS Global Positioning System ICRAF International Centre for Research in Agroforestry (World Agroforestry Centre) ILRI International Livestock Research Institute IPCC Intergovernmental Panel on Climate Change KNBS Kenya National Bureau of Statistics LULC Land Use Land Cover MAD CAT Mapping Device Change Analysis Tool MSS Multispectral Scanner System RCMRD Regional Centre for Mapping of Resources for Development SEDAC Socio-economic Data and Applications Centre SWC Soil and Water Conservation UNEP United Nations Environment Programme UNFPA United Nations Population Fund USGS GLOVIS United States Geographical Survey Global Visualization Viewer WOCAT Word Overview of Conservation Approaches and Technologies WRI Word Research Institute

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ABSTRACT The world population was at 7.3 billion people in 2015, and is projected to reach 9.7 billion in 2050 and 11.2 billion people in 2100. Population in the developing countries which Kenya is part of is expected to rise from 5.9 billion in 2013 to 8.2 billion in 2050 to 9.6 billion in 2100. Increasing human population and the threats posed by climate change continue to put pressure on the already limited environmental resources that support life on earth. This is evident in the case of land resources such as forests, cropland and water. Unsustainable human activities in fragile areas such as gold mining in Macalder, Migori are aggravated by natural disturbance such as drought or flooding and lead to land degradation and desertification. The main objective of the study was to establish the effects of human population growth on cropland, forestland and water resources in Migori Sub-county. The specific objectives of the study were to examine the human population growth patterns in Migori Sub-county between 1979 and 2013; to examine the trends and patterns of forestland, croplands and water resources in Migori Sub- county between 1979 and 2013 and to analyse the relationship between human population growth, forestland, cropland and water resources in Migori Sub- county between 1979 and 2013. The study adopted a survey approach. Quantitative and qualitative data was collected from various sources, analysed, interpreted and presented in a report. Simple random sampling method was employed to establish the sampling frame based on a list obtained from the local administration. A total of 150 questionnaires were administered to the selected households. Population data obtained from the KNBS and world gridded data were used to show population changes and showed that the population has been increasing from 1979 to 2009 (the period under study). Satellite images for the years 1979, 1989, 1999, 2009 and 2013 were processed in ERDAS Imagine and ArcGIS 10.3 and used to create land cover/land use and change maps. Primary data was collected in the field for validating land cover classification and accuracy assessment. Secondary data was obtained from scientific books, reports and journals to provide a context for the research. The mapped data from satellite image of 1979 indicated a Cropland cover of 182,416.2ha, a forest cover of 1,560ha and water body cover of 55,528.6ha. In 1989 forestland increased slightly to 2,593.6ha and to 3,828.8ha in 1999 but declined in, 2009 and 2013 to 3,519ha and 2,475.1ha respectively. Water resources depicted a continuous decline from 55,528.6ha in 1979 to 54,767ha in 2013. Croplands exhibited an irregular pattern occupying 76.2% in 1979 and 75.5% of the total area in 1989 and 75.8% in 2013. Farming which occupies the croplands is the main cause for loss of forestland. Two- tailed T-tests conducted indicated that there was a significant relationship between population growth and losses/gains in cropland, forestland and water resources with the value of P at 0.02, 0.008 and 0.009 respectively. The study thus established that population growth impacts on land resources in various ways. This study recommends that sustainable use of land resources should be embraced as the methods already in place do not suffice. This study provides base information for the national government, county governments, the academia, NGOs and the community on the status of land resources for necessary interventions and to ensure that they are used sustainably for posterity.

CHAPTER ONE: INTRODUCTION

1.1 Background to the Problem

Human population has been increasing and is expected to increase in future. As of

2015, world population was 7.3 billion and is expected to reach 9.6 billion in

2050 AND 10.9 billion in 2100 (UN, 2015). Population in the developing countries, is expected to rise from 5.9 billion in 2013 to 8.2 billion in 2050 and

9.6 billion in 2100 (Kiguru et al., 2013). Projected increases in world population appear moderate from the perspective of the past, however, in absolute indices it is quite high (Kiguru et al., 2013). Increases in the world population are expected to be uneven across the globe, with some areas growing much faster and a few others potentially shrinking (UN, 2013).

The rapid population growth being experienced in Africa has given rise to the growth of urban centres, led to encroachment into forests, increased the size of farmlands, and reduced the size of the available productive land, while the need for more production to feed the growing population has increased the rate of Land

Use and Land Lover Changes (LULCC) (Masek et al., 2000). The tropical region is growing faster, at 2.6 % annually, in contrast to 1.7% for Northern Africa and 1.1

% for Southern Africa (UN Population, 2012). According to Prakasam (2010),

LULCC in Africa are as a response to the socioeconomic, the political, cultural, demographic and environmental conditions which largely are a characteristic of human populations.

Kenya’s population has been increasing since independence. The previous population censuses showed that the population was 15.3 million, 21.4million,

28.7million and 38.6million for the years 1979, 1989, 1999 and 2009 respectively

(KNBS, 2010). Kenya has an annual growth rate of about 2.8% (Newmark, 2013) and her population is projected to reach 51million by 2025 (Miller & Spoolman,

2012). According to Kiage et al., (2007), Kenya like many other countries has had a great deal of LULCC over time as a result of the ever increasing human population resulting to pressure on environmental resources in order to address the day to day needs. During the early colonial period (1900- 1930), the country experienced massive land exploration coupled with European settlements and large scale agriculture (Campbell et al., 2003). There was a reduction in the constraint on

African land during the period nearing independence (1930- 1963). It was also during this period that interactions with the natural and undisturbed environment increased.

This was in a bid to address the needs of the increased population (Campbell et al.,

2003). After independence, the country propagated the development of rural areas through increased cash crop production especially in the central highlands and the western areas. The government also promoted land use diversification in the Arid and

Semi- Arid Lands (ASALs) to improve food production (Kiage et al., 2007). A lot of pressure has been imposed on land as 75% of the population practices agriculture in a country where only 20% land is arable (Campbell et al., 2003). This has led to the encroachment into wetter areas, deforestation and charcoal burning among other unsustainable land use practices.

Homa Bay District, of which Migori District was part of until after 1989, has experienced a significant growth in its population. According to the 1979 census,

the population of Homa Bay was 817,601(KNBS, 2010). In 1989, the population of Homa Bay was 1,066,583 (KNBS, 2010). Migori District was created after

1989 and recorded a population of 514,897 in the 1999 census (Obudho &

Ominde, 2011). In 2009, the population of the district was 335,873 (Owen, 2012).

This decrease is attributed to the subdivision of the district to Rongo and Migori as per the 2009 census. In the 2009 census Rongo District’s population was

325,211 (KNBS, 2010). The sum of Rongo and Migori Districts population is

661,084 which still reflect an increase in the population if the district had not been sub-divided in 2007. The ever increasing population in the area puts immense pressure on the environmental resources. The symptoms of the problem of pressure on land resources is manifested in terms of deterioration in the condition of land or impacts on other natural resources. The deterioration in land condition may be reflected by an impaired ability to carry out any functions of the land such as decreased agricultural yields and air pollution due to logging (UNEP, 2011).

This scenario acts as a ticking time bomb and if not controlled, it will render mother earth an inhabitable place.

1.2 Statement of the Problem

Achievement of sustainable development that includes land resource management has been a key agenda for many nations since the United Nations Conference on

Environment and Development (UNCED) held in Rio de Janeiro in 1992.

Kenya’s national and county governments strive to achieve the desired goals through formulation and adoption of key environmental policies, and channelling funds towards projects. In spite of these efforts, increasing human population

continues to put pressure on the already limited environmental resources that support life on earth. This is evident in the case of land resources such as forests, cropland and water (Mekuria, 2014). The conversion of farmland into small-scale permanent agriculture has been the main contributor to forest loss (Jay, 2013).

Forest loss is likely to continue at current rates unless governments initiate afforestation and re-afforestation programs (Unies, 2011). Unsustainable human activities that take place in already fragile areas such as gold mining in Macalder,

Migori, which are aggravated by natural disturbances such as drought or flooding; lead to land degradation (Obudho & Ominde, 2011). Consequences of land degradation include reduction in crop and pasture productivity, fuel wood and non-timber products; which are closely linked to poverty and food insecurity

(Omondi, 2012).

High population growth results in significant land use change in and around many small rural communities. Migori Sub-county faces environmental challenges due to the increasing human population. Some of the human activities that are believed to be drivers of changes in land use and land cover include encroachment into forests with the aim of expanding croplands, sand harvesting and mining. The landscape changes have ecosystem and socio-economic impacts therefore land use planning and policy could minimize negative impacts of population growth in the community (Hill & Aspinall, 2000). Much of this information is theorized or assumed. There lacks concrete information based on concrete information based on scientific findings on population growth and sustainable use of land. There are many areas in the country going through these changes but lack facts. There is

therefore the need to investigate the effects of the increased human population land resources. This information would be of use to policy makers and planners in developmental planning of the area.

1.3 Research Questions

The study endeavoured to answer the following questions: i) How are the human population patterns in Migori Sub-county from 1979

to 2013? ii) How are the trends and patterns of forestland, cropland and water

resources in Migori Sub-county from 1979 to 2013? iii) What is the relationship between human population growth, forestland,

cropland and water resources in Migori Sub-county from 1979 to 2013?

1.4 Objectives of the Study

The broad objective of this study was to establish the relationship between human population growth and its implications on the use and trends of land resources in

Migori- Sub- County, Kenya. Specifically, the study aimed to: i) To examine human population patterns in Migori Sub-county from 1979

to 2013. ii) To examine the trends and patterns of forestland, cropland and water

resources in Migori Sub-county from 1979 to 2013.

iii) To analyse the relationship between human population growth, forestland,

Cropland and water resources in Migori Sub-county from 1979 to 2013.

1.5 Research Hypothesis

Hi: Human population significantly impacts on forest cover, water resources and cropland in Migori Sub-county

H0: Human population doesn’t have significant impacts on forest cover, water resources and cropland in Migori Sub-county

1.6 Significance of Study

The information generated in this study is quite important to land use planners, urban and regional planners, the research community, academia as well as the policy and the decision makers (including the county government) in terms of understanding the relationship between land population growth and land use activities thus providing a basis for necessary interventions. The study mapped the major LULC classes in Migori Sub- County and was able to show the land use changes from one class to another, for example, the conversion of forest into cropland and recession of Lake Victoria. The study will also help in pushing for the necessary conservation and intervention measures. The established relationship between population growth and the use of land resources provides a basis for further remedial measures and related studies. In addition, evaluation of the strategies that are in place will help in knowing what need to be done in terms of implementation of the existing policies on forest and water. Incorporation of technology (GIS) into this study also forms a crucial step towards adoption and 6

inclusion of technology in addressing land resource problems affecting other areas by scholars. The findings if replicated in other parts of the world may help in addressing problems associated with population growth and land use planning.

1.7 Scope and Limitations of the Study

The study was conducted in Migori Sub- County, Kenya and focussed on establishing the impacts of human population growth and its implications on the use and trends of land resources. The main limitation of the study was resources in terms of time and finances. In addition, the sample size of the respondents had to be small due to the constraints in financial resources. The researcher could not reach a bigger population of farmers. However, despite the various constraints, the study population sampled was representative enough to avoid bias and to enable the researcher acquire some useful information, draw some conclusions and also make some recommendations.

1.8 Operational Definitions

Land cover- Physical, chemical or biological categorization of the terrestrial surface e.g. grassland, forest and concrete among others.

Land Cover Change- The alteration of the physical, chemical or biological categorization of the terrestrial surface e.g. grassland, forest and concrete among others. Various forms of land cover lose, gain or remain unchanged.

Land Resources- Refer to 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 and geo-hydrological 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.).

Land Use- Human activities which are directly related to land, making use of its resources or having an impact on these resources.

Land Use Change- Refers to the change in human activities which are directly related to land, making use of its resources or having an impact on these resources.

The changes either occur naturally or as a result of anthropogenic causes.

Human Population Growth- Refers to the increase in the number of people that reside within a geographic region

CHAPTER TWO: LITERATURE REVIEW

2.1 Introduction

This chapter reviews the existing literature on different thematic areas of focus in this study to fully address the objectives and identify the gaps. It includes literature on the impacts of human population growth on land resources which include croplands, water bodies and forestlands. It also presents a conceptual framework which shows the independent and the dependent variables which were studied. Also, mentioned in this chapter are the various land resources related policies applicable in Kenya.

2.2 Population Increase and Land Resources

According to United Nations Population Fund (UNFPA), it took hundreds of thousands of years for the world population to grow to 1 billion, and in just another 200 years or so it grew sevenfold. In 2011, the global population reached the 7 billion mark. According to Stephenson et al., (2010), 86 per cent of the world’s population lives in the developing world. Most of the growth has taken place in the developing countries. At 6.5 billion people in 2005, the planet now supports 47.9 persons per sq. km (FAO, 2009). Experts predict that by the year

2025, world population may reach 8.0 billion and by the year 2050 the population may reach about 9.2 billion (De Fres et al., 2010). Demographic reports show that the population of Africa alone increased by about 471million between the year

1980 and 2006 and is expected to rise to 1.2 billion in 2020 (Ittersum & Geijn,

2011). The yearly population growth rate is declining (from 2.5% between 1990 and 2000 to a projected 2.1% between 2010 and 2020), however; the increase in the total population is an indication of further pressure on resources (Benin et al.,

2010). The dramatic growth in population has been driven largely by increasing numbers of people surviving to reproductive age due to improved health care

(Benin et al., 2010).

World’s rising population is causing changes in land use patterns.

Overexploitation of the earth’s natural resources is so severe that it threatens the balance of many ecosystems globally (UNEP, 2002). All across the developing world, farm size is shrinking as farmers continue to subdivide holdings among their children. This has led to search for alternative land for cultivation through forest encroachment (Starke, 2005). Social inequality within the population leads to skewed structures of land ownership and leads to pressures towards land degradation. The power of population is greater compared to the power of the natural environment to produce resources (Bremner et al., 2010). As population increases, the demand of natural resources also increases. This leads to the higher rate of consumption compared to rate at which nature restores itself (Thakur,

2012). Other factors like religion and cultural beliefs might have played a role in increased population in Africa and other regions of the world (Evans, 2012).

Increasing human population leads to the need of more food and consequently increased agricultural areas. This results in clearing of forests and bush lands so as to pave way for cultivation areas (Mekuria, 2014). All these cause depletion of our natural resources pose a challenge to the conservation and management of the

finite resources in the world and also (Hassan et al., 2013). Some of these studies date back to the 1980s.

Anker and Knowles (1983) conducted a study that focused on Population growth, employment and economic-demographic interactions in Kenya using a model called Bachue. This study touched on human population but not in relation to land resources. In 2009, Bongaarts published a research work that touched on human population growth and demographic transition with more focus on fertility, life expectancy and age structures. Liu et al published a document whose title was

“Complexity of coupled human and natural systems”. Embu and Vihiga areas were their areas of study in Kenya. Kahl did a study that focused on population growth, environmental degradation and state-sponsored violence, a case of Kenya from the years 1991-1993.

Other studies in Kenya that either human population growth or natural resources have been done in Machakos (Tiffen and Mortimore, 1992), Lake Victoria

(Verschuren et al., 2002), Upper Mara Basin (Mango et al., 2010) and Kajiado

(Sindiga, 2014). These studies bore these titles on “Population and productivity in

Kenya: a case of Machakos District”, “History and timing of human impact on

Lake Victoria, East Africa”, “Land Use and Climate Change impacts on hydrology of the upper Mara River Basin Kenya: results of a modelling study to support better resource management and Land and population problems in

Kajiado and Narok, Kenya.”

2.3 Land Resources

World’s area is 510.072 million Km2. Land area is 148.94 million Km2 while water occupies 361.132Km2 of the world’s area (CIA, 2012). Some of the world’s land resources include forests and woodlands, arable land, mountains, deserts, coastal lands, and freshwater systems that hold vast opportunities for development and improving human well-being if managed sustainably (UNEP, 2009). Kenya covers an area of 591,958Km2, which comprises 98.1 per cent land and 1.7 per cent water (GoK, 2011).

Land resources are sources of food, fibre, fuel, habitat for animals and source of other biotic materials for human use.

2.3.1 Forestland

Human society and the global economy are inextricably linked to forests. More than 1 billion people depend on forests for their livelihoods (Tesi, 1997). There have been campaigns all over the world calling for the conservation of forests.

This has led to improved management practices in some regions. However, despite decreased deforestation rates in some regions, forest ecosystems are still under great threat. According to WRI research, 30 per cent of global forest cover has been cleared, while another 20 per cent has been degraded (Lambin & Geist,

2008). Most of the rest has been fragmented, leaving only about 15 per cent intact

(WRI, 2012).

Increasing human population has led to clearing of forests for industries, cultivation and settlement areas (UNEP, 2012). Forests cover only about three per

cent of Kenya’s land area, yet 70% of Kenya’s domestic energy comes from wood

(Thakur, 2012). Kenya’s forests also provide other ecosystem services for instance, recharging groundwater tables and trapping and storing rain water among others (Obutho & Ominde, 2011). With the depletion of forests, biodiversity is declining and biological endemic species, that have a potential to sustain livelihood in the rural areas, are now vulnerable if not extinct (FAO,

2007). It is therefore essential to take care of our forests by investing in tomorrow’s forest (UNEP, 2012).

2.3.2 Cropland

The increasing population poses a challenge on how to provide sufficient food to everyone in the world. This has led to increased cropland over the years. In the past 50 years, the percentage of cultivated land has increased by 12 per cent globally (Thakur, 2012). Agriculture uses 11 per cent of the world’s land surface for crop production and also makes use of 70 per cent of all water withdrawn from aquifers, streams and lakes (Boserup, 2013). In Kenya, agricultural sector accounts for 65 per cent of Kenya’s total exports and provides more than 18 per cent of formal employment (GoK, 2010). The rate of the increase in agricultural production should be higher than the rate of population growth in future in order to improve nutrition (Obutho & Ominde, 2011). This will have to occur largely on existing agricultural land. Improvements will thus have to come from sustainable intensification that makes effective use of land and water resources as well as not causing them harm (Unies, 2001).

2.3.3 Water

Studies reveal that the total volume of water on earth is estimated at about 340 million cubic miles of which only 2.5 percent is fresh water (Ittersum & Geijn,

2011). Agriculture accounts for some 90 percent of the world's water consumption

(UNEP, 2012). Industry and the domestic sector use about 5 percent each (Ahlburg et al., 2013). The United Nations says that even though the world has plenty of fresh water, the problem of access to the resource is caused by mismanagement and corruption (Boberg, 2005).In many parts of the developing nations, about 40 percent of the water is unaccounted for because of leaks in canals and pipes and illegal connections (Kahl, 2014). Water sources around the world are threatened by pollution from agricultural and urban areas, solid waste, on-site waste water treatment, oil and gas extraction and refining and mining (Babcock & Walton,

2010). Kenya faces water challenges like other regions of the world. Just like the other land resources, water bodies in Kenya have been interfered with due to the increasing population that puts pressure on the water resources. Pollution, introduction of invasive species, for example, hyacinth on Lake Victoria and over- extraction of groundwater pose major threats to the resources (Awange &

Ong’ang’a, 2006). Management of water should be based on understanding of natural drainage systems, including groundwater, streams, rivers and lakes.

2.3.4 Land Use Changes

According to Lambin and Meyfroidt (2009), land changes are the major contributors of environmental change. Land use changes are driven by the need

to expand agricultural areas, urbanization and in some rare cases pastoral areas.

Increasing human population has a direct link to these land changes. With increased human population more food is needed to feed the large numbers of people and land for settlement. Technological advancement coupled with the need for urbanization in the 21st century also piles pressure on land. Land resources such as forests, grasslands and water bodies are greatly affected by land changes.

Removal of vegetation cover as grasses or forests exposes land to factors such as wind and water that cause erosion. Compaction of bare soil due to trampling by humans and animals affects soil quality due to minimized aeration. Land use changes have numerous effects on an entire ecosystem.

Kenya faces challenges resulting from land use changes. Some of these changes started gradually in the early 1900s. Government ministries and other non- governmental organizations have tried to come up with measures on how to create a balance between the changes and nature. However, this kind of initiative is often met by resistance from many sectors. The locals always feel that they are being pushed away from their ancestral land where evictions are employed. In some cases the said ancestors encroached into forests or were given the land by one of their political leaders. Lack of awareness, political interference and ignorance are some of the issues that hinder proper land management. Lack of proper land policies or poor implementation of the existent ones is a disease that is ailing the land sector in Kenya and needs to be addressed. All these land issues stream down to the local level as well. Migori Sub-county has its own fair share of land issues.

The area is mainly an agricultural zone. Small-scale farming takes place on the

bigger part of the Sub-county. Lack of regulation, minimal help from agricultural extension ad over use of inorganic fertilizers affect the land use. Declining soil fertility coupled with the effects of climate change affects food security in the region. Some of the locals have turned to sand harvesting along the Sub-County’s main rivers and gold mining; both which lead to river pollution and derelict land.

Land use changes have numerous impacts on the environment, food security and the socio-economic well-being of a community. Proper cooperation and coordination among stakeholders is necessary to address some of the emerging issues due to land use change.

2.2.5 Sustainable Land Resources Management

Human beings have made some notable progress in their quest to achieve sustainable land management. Some of these include the documentation of

Agenda 21 after the United Nation’s conference on environmental development held in Rio de Janeiro, Brazil in 1992. Chapter 10 of Agenda 21 entitled

‘Integrated Approach to Planning and Management of Land Resources’ sets some guidelines on sustainable land management. Sustainable land management entails the use of land resources, including soils, water, animals and plants, for the production of goods to meet changing human needs, while simultaneously ensuring the long-term productive potential of these resources and the maintenance of their environmental functions (FAO, 2011). The main objectives of sustainable land management include maintaining and enhancing production, reducing level of risk and enhancing soil capacity to buffer against land degradation, economic viability of land and equitability of land (CIESIN, 2017).

Sustainable land management requires collaboration of all stakeholders and the bottom-up approach is crucial. FAO (2011) asserts that the four main principles of sustainable land management are land-user driven and participatory approaches, integrated use of natural resources at ecosystem and farming system levels, multilevel and multi-stakeholder involvement and targeted policy and institutional support including development of incentive mechanisms for sustainable land management adoption and income generation at local level.

Creation of awareness is important especially among the women folk who do a lot of farming in Kenya. Some ways of achieving sustainable development in Kenya and its entire region include efficient water use, proper soil management and proper farming practices. These can be achieved through reduction of water loss, harvesting water, maximizing storage and managing excess water. Climate variability over the years has led to erratic rainfall. This has affected crop production as the rains come earlier than expected or later after planting, at times they fail completely. It is important to dig wells that serve as water storage facilities or put up tanks that can collect the rain water. This will ensure that there is increase productivity in rainfed and irrigated agriculture.

Soil fertility is dwindling in Kenya and considering that a big population relies on agriculture for income then measures have to be taken to enhance and improve soil fertility. Soil fertility enhancement involves improved fallow systems, residue management, application of improved compost, minimum soil disturbance or zero tillage (conservation agriculture), growing higher yielding varieties and mitigating impacts of climate variability and climate change. Sustainable land management

might seem like a far-fetched dream but it is possible with technical support, determination and back up of proper policies.

2.2.6 Benefits of Sustainable Land Resources Management

Sustainable land management is an integrated process that requires collaboration among all stakeholders for maximum benefits to be accrued. United Nations

Convention to combat desertification, points some of the benefits of sustainable land management to be increase food security especially for smallholder farmers.

Increase soil productivity means that more yields are recorded. Secondly, household energy is readily available, primarily in rural households that rely on fuel wood. Agroforestry through the growing of fast growing tree species like grevillea provides not only fuel wood but also fodder for on-farm animals.

Increased tree cover changes the microclimate of an area is created. Fresh air and clean water are available as a result of this. Cultural and natural landscapes have been restored through sustainable land management. This preserves the indigenous knowledge and also enhances tourism in an area.

2.2.7 Policies and Frameworks that Promote Sustainable Land Resources

Management in Kenya

Kenya has adopted various policies, laws and frameworks that provide clear guidelines on how to manage land sustainably. However, poor implementation due to political interference, mismanagement of funds and lack of goodwill hinders the achievement of the desired goal. A lot of co-operation among all stakeholders is necessary coupled with proper planning and monitoring is

essential for sustainable land management in all parts of the country. Some of these important frameworks, laws and policies include:

2.2.7.1 Agenda 21

From the environmental perspective, Agenda 21 a product of the United Nation’s conference on environment and development, is important for achievement of sustainable land management. Chapter 10 of this document sets guidelines for integrated approach to the planning and management of land resources.

According to Agenda 21, this will be achieved through the reorganization and, where necessary, strengthening of the decision-making structure, including existing policies, planning and management procedures and methods that can assist in putting in place an integrated approach to land resources. The main objective of this process should be promoting sustainable use of land resources such that the future generations still benefit.

2.2.7.2 Sustainable Development Goals (SDGs)

Sustainable development goals are the post-millennium development goals. It is a result of agreement of nations to set a path for sustainable development after

2015. Many nations committed themselves to achieving the seventeen goals by the year 2030. Attaining these goals will be a positive thing all over the world.

The main beneficiaries will be developing countries which Kenya is part of. Most of the goals are directly linked to sustainable land management. Goal number 15:

‘Life on land’ is more focused on land resources. It calls for protection, restoration and promoting sustainable use of terrestrial ecosystems, sustainably

managing forests, combating desertification, halting and reversing both land degradation and biodiversity loss. Other goals that feed directly into land management include Goals 6, 12 and 13. These call for clean water and sanitation, responsible consumption and production; and climate action respectively.

Availability of water and sustainable management of this resource will ensure that human beings have enough water for activities like farming and household use.

Sustainable consumption and production patterns are essential for proper use of land resources. Climate variability and change is a serious threat to the environment. It is believed that global temperatures have been increasing in the last decade. Kenya has made strides in her fight towards climate variability and change with the existence of National Climate Change Response Strategy and

National Climate Action Plan. Implementation of these important policies should take place.

2.2.7.3 National Land Policy 2009

The National Land Policy is a document that was adopted to guide the country towards sustainable development and equitable land use. The document calls for immediate actions addressing environmental problems that affect land resources such as degradation, soil erosion and pollution. The policy stipulates certain principles that touch on conservation and management of land based natural resources, protection and management of fragile and critical ecosystems including wetlands and arid lands; and overhaul of current policies and institutions with an attempt to address tenure insecurity and inequity.

2.2.7.4 Kenya Constitution 2010

The constitution of Kenya acknowledges the need for sustainable land management. Chapter five that focuses on Land and environment is divided into two parts; part 1 and 2 addressing Land and Natural resources respectively. The constitution states that land in Kenya shall be held, used and managed in a manner that is equitable, efficient, productive and sustainable. The document further states that for the latter to be achieved, management has to be in accordance with principles touching on sustainable and productive management of land resources, sound conservation and protection of ecologically sensitive areas (Kenya

Constitution, 2010). The importance of National Land Policy is also stated in the constitution since the above principles are to be implemented through this policy.

2.2.7.5 Kenya Vision 2030

Vision 2030 is a document that was created by Kenya government through the then Ministry of planning and national development. One important foundation of vision 2030 touches on Land reforms. The social pillar addresses the need for conservation of environment and water resources. Some of the ways that water conservation are to be done include harvesting of rain water and utilization of groundwater. As for the environment, the strategy aims to have Kenya’s environment that is clean, secure and sustainable by 2030. Conservation measures include the increment of national forest cover and undertaking projects that deal with water catchment management, solid waste management, land use and land cover mapping.

2.8 Conceptual Framework

Figure 2.1 shows the relationship between different variables in the research.

Integrating the study objectives, the study envisages that; human population growth (Independent Variable) plays a major role in the increase or decrease of land resources in an area. The increase in human population puts immense pressure on land resources leading to deforestation, land degradation, and encroachment into water bodies and riparian areas. This has an impact on the spatial coverage of forestlands, croplands and water bodies. They either increase or decrease in size. Land degradation is a major cause of unsustainable use of land and especially for the croplands as it reduces their productivity. Intervention measures (Land management practices) which include agroforestry, afforestation and reforestation, mulching, use of organic manure etc. help safeguard land from degradation thus leading to the continued and increased productivity for the increasing human population.

Figure 2.1: Conceptual Framework on Population Growth and Land Resources

Source: Synthesized from Literature (2016)

2.9 Research Gap

A lot of work has been done by different scholars and researchers touching on

LULCC in many regions of the world including the African continent. However, most of these studies focus on the general land use or natural resource changes but not in relation to the effects of the human population growth to specific land

resources. It is hard to ignore that all the natural resources are intertwined in one way or another. For instance, the presence of forestland contributes a lot to the hydrological cycle and water resources. Cropland impacts either negatively or positively to forestland and forestland. Human beings are at the centre of this cyclic pattern. Previous studies have contributed immensely to the knowledge data bank but it is clear that there is a lacuna that this kind of study has not been done in Migori Sub-county. This study’s interest was on only three types of land resources which are cropland, forestland and water resources (also known as waterbody) in the land cover, in relation to human population growth.

CHAPTER THREE: METHODOLOGY

3.1 Introduction

This chapter forms the core of the study. It gives in details the information on the study area with regards to the location, vegetation, climatic conditions and the population patterns. This chapter also gives in details the sources and forms of data acquired for the research, as well as the methods used for data analysis and presentation.

3.2 Background to the Study Area

3.2.1 Location and Extent

Migori Sub-county is located in south-western Kenya bordering Kuria Sub- county, Homa-Bay and Kisii counties. Its geographical coordinates are latitudes

0º36’South, S1º24’ and longitudes E33º54’, E34º48’ (Google Earth, 2013; Fig

3.1). Its headquarters is Migori town. Migori Sub-county has an area of

2505Km2, 475Km2 which is composed of Lake Victoria (ICRAF, 2013). Figure

3.1 is the map of Migori Sub-county within the County and national context.

Figure 3.1 Location of Migori Sub-county in the Local and National Context Source: Author’s construct (2015)

3.2.2 Population Distribution

Migori Sub-county has a population of 253,409; Male 121,181 and Female

132,228 (KNBS, 2010). The population density of Migori Sub-county is 255 persons per Km2 (ICRAF, 2013). The Sub-county has 115,000 households with

96,456 farm holdings (ICRAF, 2013). The average household size is 5 persons

(ICRAF, 2013). Figure 3.1 shows the distribution of the human population in

Migori Sub-county.

Figure 3.2 Population Distribution of Migori Sub-county

Source: KNBS, 2010

The soils in Migori Sub-county are mainly derived from two main series of ancient rocks, the Kavirondian and Nyanzanian volcanics north of the Migori

River; and intrusives mainly, granites, with some doleritic dykes, south of Migori

River (ILRI, 2013). All these soils give rise to reasonably fertile soils capable of producing good crops where they are sufficiently deep.

3.2.3 Climatic Conditions

The area has two rainy seasons. Annual rainfall increases from 700-800mm near the lake to 1400-1500mm in the East (GoK, 2005). About 40% of the total annual falls during the long rains (March-May: 16-18 days/month) and 28% during the

short rains (October-December: 11-13 rain days/month). The reliability of the rains increases as total annual rainfall increases (GoK, 2005).

Temperatures in the Sub-county vary with the location. Around the lake, temperature ranges from a minimum of 14-18oC to a maximum of 30-34oC. The range, in the East is from 10-14oC to 26-30oC, maximum temperatures occur in

February and October and minimum temperatures in July (GoK, 2005).

3.2.4 Socio- Economic Activities

Agriculture, fishing, manufacturing, sand harvesting and mining are the main economic activities in the Sub-county (GoK, 2005). Gold mining takes place in

Macalader area of Migori on the way to Sori (Karungu Bay).

3.3 Research Design

The research design undertaken was a survey. This is because data was only collected from some of the population members and a systematic instrument, a structured questionnaire was used to gather data from each sampled members

(Lavrakas, 2008). A survey is less costly and timelier as opposed to census. The survey involved use of appropriate sampling design to come up with the sample size, collection of data from various sources, analysis and interpretation of data and finally the presentation of the findings in a report.

3.4 Sample Size and Sampling Procedure

Households were sampled randomly based on the household list obtained from the local administration offices which was used in developing the sampling frame.

The number of households sampled within the administrative area (location level) was calculated as the number (n) required in estimating population proportions (π) at 95% confidence intervals around observed sample proportions (P) with an interval no larger than P ± 0.103 as shown in equation below (Wonnacott and

Wonnacott, 1977, Eq. 8-40)

Where 1.96 is the z-value for a 2-sided 95% confidence interval, c=0.08 is the desired maximal half-width of the confidence interval, and π=0.5 is the population proportion that results in the widest confidence interval for a given sample size

(worst-case for a conservative estimate of sample size). Using this into the equation, the sample size was

3.5 Data Collection Tools and Procedures

Population data obtained from the Kenya National Bureau of Statistics was used to show population growth in the area in the last three decades. In addition,

United Nations gridded population data produced by socio-economic data and applications centre of Columbia University was used to show the variations in population in radius of approximately 1km in the Sub-county for the years 2000,

2010 and projections for 2020. Data from national census and population registers adjusted to match official UN population estimates were used to create these gridded data sets. The main advantage of using the gridded data sets is that they

indicate population for each grid or point, and also ensure consistency for analyses (SEDAC, 2016).Landsat images for the years 1979, 1989, 1999, 2009 and 2013 were obtained from the USGS website used to create land cover-land use and change maps for the respective years using Remote sensing/GIS technology. Remote sensing affords researchers the capability to literally see the invisible (Lillesand et al., 2008). On the other hand, GIS systems are capable of handling both locational data and attribute data about features that can be referenced by geographical location (Lillesand et al., 2008). GIS not only permits the automated mapping or display of the locations of features, but also these systems provide a capability for recording and analysing descriptive characteristics about the features(Lillesand et al., 2008).

Primary data was collected in the field for ground truthing land cover classification of remotely sensed data and land use practices. Geographical positioning System (GPS) instruments and digital camera were used to collect coordinates of geographic features. The data were integrated into Arc GIS 10.3 to generate point GIS layers. It was overlaid into existing land cover data to ensure that the land use classification depicts is on the ground. Necessary changes were carried out thereafter.

Since Remote sensing/GIS technology does not show the social aspect, key informants and representatives from the ministries of water and agriculture were interviewed to find out information on social issues such as household structure, education level of the target population, ages and what the government is doing to support farmers.

Secondary data was obtained from scientific books, journals and report. Books and journals enable a researcher to assess them at his/her own convenient time.

They also provide thoughtful data, in that, participants have given attention in compiling them (Creswell, 2009). Observation took place and photographs taken.

Observation gives the researcher a chance to record information as it occurs.

Unusual aspects can be noticed during observation and provides an avenue for exploring topics that may be uncomfortable for the participants to discuss

(Creswell, 2009). Important information was obtained from the relevant authorities.

3.6 Land Use and Land Cover Methodology

3.6.1 Collection and Quality Checking of Ancillary Data

Collection of ancillary data is important as a baseline for any study. This activity involved collecting as much information as possible from previous reports, publications and studies within the scope of the study. Vector data (roads layers) and raster data (satellite images) were obtained. The sole purpose of this activity was to have sufficient spatial and related attribute information on land use and land cover mapping from the different sources.

Ancillary datasets collected from the various sources were checked for accuracy, consistency and completeness based on various quality standards. This was an important procedure to determine fitness-for-use of particular datasets collected from the various institutions related to the study, and was mostly facilitated

through studying the metadata of a particular dataset and subjecting the data to independent quality assessments.

3.6.2 Database Development

This activity involved designing a spatial database with appropriate data structures for storage of ancillary datasets collected in ArcGIS 10.3. The database acts as storage for other datasets and products that were collected and/ or generated through image processing and interpretation. GIS layers and raw imagery data were also archived in this database therefore an appropriate database structure was required for this activity with definition of proper data types and formats being considered.

Data management is always a critical component when implementing most spatial related research work such as the land use land cover mapping of Migori sub- county. In this regard, we populate the spatial database being developed by the researcher with land cover and vegetation data sets generated during this study.

The specific tasks within this activity were: i) Geodatabase creation; ii) Database standards preparation.

3.6.3 Landsat MSS, Landsat TM, and ETM+ Image Understanding and

Acquisition

The images were acquired from Landsat GLOVIS covering Migori Sub-county for the epochs 1979, 1989, 1999, 2009 and 2013. The images were of spatial

resolution 60m (1979) and 30m (1989, 1999, 2009 and 2013). Landsat 3

(Multispectral scanner), Landsat 5 (Thematic Mapper) and Landsat 7 (Enhanced

Thematic Mapper) images were acquired from the USGS site and processed using remote sensing applications (ERDAS Imagine and Arc GIS 10.3). Data pre- processing involved image orthorectification where necessary. It was necessary to consider dates of acquisition, cloud cover and the type of sensor involved. Figure

3.3 shows the imagery for 1979, 1989, 1999, 2009 and 2013 were that were downloaded and processed.

Figure 3.3: Images for the years 1979, 1989, 1999, 2009 and 2013

Source: Author (2015)

3.6.4 Image Classification

To achieve adequate land use and land cover classification, a proper classification scheme consistent with the existing classification schemes and definitions in

Migori sub-county was selected in order to properly represent the land use land cover characteristics. Selecting the appropriate levels of detail for image classification was important as an over-abundance of land cover categories can lead to considerable confusion among cover types, whilst an under-representation may sometimes not meet the user demands. This therefore called for a detailed study of the existing classification schemes to guide in choice of an appropriate structure to represent the land cover characteristics of Migori Sub-county with guidance of the objectives of the study.

Reference was also made to the IPCC and FAO guidelines used in developing globally used standards that also meet country specific classification scheme standards. FAO land use and land cover category for classification was used to come up with the following 10 classes:

 Forestland

 Shrubland

 Grassland

 Riverine

 Bare Areas

 Settlements

 Plantation

 Cropland Small Scale

 Waterbody

 Wetland

Before classification, image processing steps of image selection for identification of cloud free images; layerstacking of image bands to obtain scene composites; band combination analysis and image enhancements and corrections was performed. The initial stage of image processing involved extraction of the individual bands followed by layerstacking; where the various bands of the multispectral Landsat image were composited into a single multi-band image.

This ensures that the various bands of a multispectral image are utilized in determining the land use land cover characteristics of a given area. Consideration was made to the thermal band and the panchromatic band to ensure consistency in the spatial resolutions of the images since they differ in spatial resolution from the rest of the bands. Image mosaics were created from the composites as products of layer stacking to represent wall-to-wall coverage of Migori Sub-county. Subsets representing Migori Sub-county extracted using the AOI file depicting the Sub- county boundary were produced for the 5 epochs of the dataset. Erdas Imagine and Arc GIS were used for image processing. Supervised classification (object oriented) was done in Arc GIS 10.3 to produce output files in vector format. On screen digitization was employed to conduct the classification. Visual interpretation was essential in determining the classes. This process involved extraction of information from the satellite images as polygons which were then coded by assigning them to the correct class. Figure 3.4 shows the generated polygon.

Figure 3.4: Generated polygon

Source: Author (2016)

Thorough knowledge of the different land cover classes is important. The most current year which is 2013 was the first to be classified. Quality checks were performed on the first draft 2013 classification using high resolution imagery that can be accessed through the Google Earth platform before the ground truthing exercise. The first draft 2013 was verified using field points. Necessary corrections were done and the final draft produced followed by the generation of the accuracy report. The 2013 land cover served as the base file for classifying the years 2009, 1999, 1989 and 1979. The 2013 file was saved as the 2009, 1999,

1989 and 1979 to avoid confusion or replacement of the file. The 2009, 1999,

1989 and 1979 images were then overlaid. The changes are easily noticed. Editing of the 2013 file based on the 2009, 1999, 1989 and 1979 images produced the

Land Use Land Cover files for the years 2009, 1999, 1989 and 1979. Change analysis was conducted to generate change maps that show the exact areas where

changes occurred and the transition among classes. The land use and land cover statistics were generated in Arc GIS 10.3 and tables created in Excel. Among other tasks within this activity involved: i) Selection of the administrative boundary to be used for classification ii) Land cover mapping for the 5 time series with the minimum mapping

units of 0.5 hectares being consistent with the existing classification

scheme of FAO. iii) Selection of object oriented (supervised classification) performed at the

individual Landsat scene level; iv) Derivation of land cover statistics v) Development of land cover land use maps using the scale of 1:350,000 for

the Sub-county maps.

3.6.5 Ground Reference Data Collection and Accuracy Assessments

This activity involved collection of ground reference points in order to train the computer to recognize the various land cover categories in the imagery and to assess the categorical accuracy of the resulting classification. The collected reference data for accuracy assessment for 2013 imagery was also used to establish random ground control points for follow up monitoring. Reference information and training data for classifying imagery for earlier dates, that is,

1979-2013 was developed from review and study of existing land use and land cover and vegetation data, reports and publications and through use of Google

Earth platform for the high resolution times-series imagery. Change detection was

also used to distinguish irregular changes and for identification of erroneous classes. Ground reference data is collected from the field on randomly generated points at selected zones for image classification accuracy assessment. A number of criteria was considered when evaluating the suitability of any ground reference data set for land cover classification such as: sufficiency of reference samples to achieve required confidence levels; a random method has to be considered and should be systematic and representative of the area of study; and the reference data must be of around the same time as the satellite image.

A plan for selecting locations for collecting ground control points for data verification using stratified random sampling involved identifying a sample of each land cover class proportionate to the population size of the class when viewed against the entire population. Then the number of points per land use category was identified and used to generate the number of such points within a sampling frame. The stratified random sampling technique was then applied to randomly distribute points across the sampling frame and across each land cover category in relation to their area coverage in the sampling zone.

Accuracy assessment to analyze and modify the result of the classification was conducted for the 2013 land cover classification with a recorded accuracy of 86%.

The accuracy assessment of the land use and land cover maps was produced using a confusion matrix to compare the reference points generated from the land cover classification to the sample points collected from ground reference locations. A report of accuracy analysis with the methods used and source of reference points being indicated was produced. Tasks within this activity involved;

i) Identification and definition of a sampling zones; ii) Developing a sampling design, sampling frame and collecting ground

reference data; iii) Implement simple quality assurance and quality control procedures on the

ground reference data; iv) Creating error/ confusion matrix for accuracy assessment using random

generated points at scene level and at national level; v) Assessing accuracy using both ground reference points and points

interpreted from high resolution satellite imagery (Google earth).

Ground referencing activity was limited in time and resources and was done for one week. Ground reference data (a total of 80 points) was collected from the field on randomly generated points at selected zones. The probability sampling design was the preferred approach. It combines random or stratified sampling to get points to validate the land cover predefined in the first draft classification and perform accuracy assessment of the same. In view of this, the data collection method was systematic, and representative of the entire area that had been classified. The randomness of selection was to avoid selection bias of the land cover. Time constraint contributed to 80 points being selected.

3.6.6 Accuracy Assessment

The thematic accuracy of the 2013 land cover was assessed by comparing the land cover type shown on the 2013 land cover map to the land cover type identified on the ground for a representative sample of evaluation points. When land cover

types are mapped and labeled with the correct land cover types (ground reference), then the map or land cover has high thematic accuracy. The acceptable threshold for overall accuracy according to USGS classification is 75%. USGS states that for each map class, both producer’s and user’s accuracy are evaluated.

User’s accuracy indicates the probability that a sample point mapped as a given vegetation type will be shown to be of that type on the ground. Producer’s accuracy indicates the probability that a sample point classified as a given land cover class on the ground will have been assigned to that association on the map.

In addition to the user’s and producer’s accuracy, measures of the overall map accuracy are calculated, and contingency tables showing the frequency of confusion (i.e. misclassification) between associations are presented.

Figure 3.5: Field Verification Points Source: Author, 2017

Ground Referencing points were split in two ways. Some of the points are used in refining the classification and the remaining points were used for accuracy assessment. Of the 80 points collected (Figure 3.5), 30 points were used in improving the classification by correcting the wrongly classified regions while 50 points were used in checking the accuracy of the classification. Table 3.1 shows each class and the number of points collected in the field.

Table 3.1: Field Verification Points

Land Cover Class No. of Points Bare Areas 4 Cropland 35 Forestland 10 Grassland 6 Plantation 4 Riverine 2 Settlements 5 Shrubland 5 Waterbody 6 Wetland 3 Total 80 Source: Field work (2016)

Accuracy assessment was critical for a map generated from any remote sensing data. Error matrix is in the most common way to present the accuracy of the classification results (Fan et al, 2007). Overall accuracy, user’s and producer’s accuracies, and the Kappa statistic were derived from the error matrices. The

Kappa statistic incorporates the off diagonal elements of the error matrices and represents agreement obtained after removing the proportion of agreement that could be expected to occur by chance (Yuan et al, 2005).

Kappa ( Kˆ ). = observed accuracy – chance agreement

1- Chance agreement

Table 3.2 is the error matrix, along with the overall accuracy and the Kappa coefficient. The overall accuracy of classification imagery dated 2013 was 86% and the Kappa coefficient was 81.76%.

Table 3.2: Compliance Matrix between Interpreter and Validation Based Results FIELD DATA 2013-

LULC Bare Crop- Forest- Grass- Water- Shrub- Wet- Plantation Riverine Settlements TOTAL PA% Areas Land land Land body land land Bare Areas 2 0 0 0 0 0 0 0 0 0 2 100% Cropland 0 20 0 0 2 0 0 0 0 0 22 90.90% Plantation 0 1 3 0 0 0 0 0 0 0 4 75% Forestland 0 2 0 6 0 0 0 0 0 0 8 75% Grassland 0 0 0 0 2 0 0 0 0 0 2 100% Riverine 1 0 0 0 0 1 0 0 0 0 2 50% Settlements 0 0 0 0 0 0 3 0 0 0 3 100% Waterbody 0 0 0 0 0 0 0 3 0 0 3 100% Shrubland 0 2 0 0 0 0 0 0 1 0 3 50% Wetland 0 0 0 0 0 0 0 0 0 1 1 100% TOTAL 2 21 3 8 4 1 3 3 3 2 CA% 100% 95.23% 100% 75% 50% 100% 100% 100% 33.33% 50% 100% Source: Author (2016) Overall Accuracy= (2+20+3+6+2+1+1+3+3+1+1)/50 * 100 =86%

Kappa= 50 (43)-( (2*2)+ (22*21)+(4*3)+(8*8)+(2*4)+(2*1)+(3*3)+(3*3)+(3*3)+(1*2)

(50)2-( (2*2)+ (22*21)+(4*3)+(8*8)+(2*4)+(2*1)+(3*3)+(3*3)+(3*3)+(1*2)

Kappa= 0.8176 which indicates a high agreement

3.6.7 Change Analysis and Derivation of Statistics

The final land use and land cover files for the years 1979, 1989, 1999, 2009 and

2013 were used to derive the change files. Change analysis was done using

ArcGIS. Four change pairs 1979-1989, 1989-1999, 1999-2009 and 1979-2013 were analyzed and statistics derived. Statistics help to note gains and losses. Gains and losses can be used to assess land degradation, deforestation and reforestation.

For instance, a change from grassland/ bare area to cropland indicates seasonal changes. Another change from forestland to Shrubland indicates deforestation while a change from grassland to bare area might be seasonal change or degradation. Changes in acreage also show areas that require immediate intervention. Illegal logging and encroachment into forests may lead to complete destruction within a short time. Change analysis was important to bring out the transition in land uses and cover over the years. Change maps were then produced using the change files.

3.6.8 Preparation of Final Land Cover and Change Maps

This activity ensured that well designed land use and land cover maps for each of the 5 epochs, as well as the change maps were represented at suitable scales depending on the spatial extents of Migori Sub-county. Consideration was made to the various map elements to ensure proper representation of map features.

Preparation of the final land cover maps for the 5 epochs resulting from the land use and land cover classification were presented in user appropriate formats and to the required cartographic standards. These maps were formatted to a uniform

coordinate reference system appropriate for Kenya. Among the key tasks involved at this stage will include: i) Generation of the required land cover maps in the required vector format ii) Preparation of single file maps representing each of the 5 epochs to be

studied for Migori Sub-county; iii) Preparation of maps in a uniform coordinate system (geographic

coordinate system (WGS84). iv) Preparation of land use and land cover change maps

3.6.9 Questionnaire Analysis

A total of one hundred and fifty questionnaires were administered to households and officials in the ministries of Agriculture and water at the Sub-county level.

The collected data from questionnaires were entered into Statistical Package for

Social Sciences (SPSS) to come up with reliable analysis of the data. Data was analysed using univariate, bivariate and multivariate analysis. This involved cross-tabulation and factor analysis. Quantitative and qualitative analyses were made. The generated information was presented in the form of tables.

CHAPTER FOUR: RESULTS AND DISCUSSIONS

4.1 Introduction

This chapter focused on data analysis, interpretation and presentation. The chapter also covers the trends and patterns of human population, relationship between human population growth and forest land, relationship between human population and cropland, demographic characteristics and t-test analysis.

4.2 Human Population Patterns in Migori Sub-county between 1979 and

2013

According to a United Nations Population Division (UNPD) report of 2015,

Kenya’s population as of mid-2015 was at 46,050,000, and it is expected to reach

95, 505,000 by mid-2100. This is in line with the population data that Kenya

National Bureau of Statistics has been publishing after each census. Cohen (1995) mentioned that earth’s human carrying capacity is uncertain calling for need to utilize the resources in a sustainable manner. Human population growth has been increasing yearly and this is the case with Migori Sub-county as well. Migori district was formed after 1989. Initially it was part of Homabay County and was later sub-divided into Rongo and Migori districts in 2007. The available population data for Migori are for 1999 and 2009. However, the sub-division might give the impression that there was a decline in the population. This study sought to look at the dynamics of human population from 1979 to 2013.Therefore population data for Homabay district (1979 and 1989) was used to show the growth of a region that Migori district was part of then and in 2009, sum of

Rongo and Migori has been used to show the growth. Table 4.1 shows the districts and their population for the census conducted in 1979, 1989, 1999 and

2009.

Table 4.1: Population data for Homa Bay, Migori and Rongo Districts for 1979, 1989, 1999 and 2009

District Year Population

Homa Bay 1979 817, 601 Homa Bay 1989 1,066,583 Migori 1999 514,897 Migori 2009 335,873 Rongo 2009 325,211 Migori and Rongo 2009 661,084 (summation) Source: KNBS (2010)

Additionally, UN gridded population data was used to indicate population in the

Sub-county for the years 2000, 2010 and projections for 2020. 2000 and 2010 were chosen because of being close to the census years; 1999 and 2009. 2020 gives a picture of what is expected in the future. UN gridded data has a resolution of 30 arc-seconds which is approximately 1 kilometer at the equator. This data was classified and presented in the form of maps as indicated in figures 4.1, 4.2 and 4.3.

Figure 4.1: Migori Sub-county’s Human population for the year 2000

The national population census for Kenya was conducted in the year 1999. The gridded population data for the year 2000 was selected because of only one year period since the official release of the 1999 census. Figure 4.1 above indicates the

UN adjusted gridded population data for Migori Sub-county for the year 2000. As expected, human population in Migori Sub-county is higher in the urban areas such as Karungu, Mihuru, Rongo and Migori. Highest population concentration is within close proximity of the urban areas. In the year 2000, areas around Ndhiwa,

Nyakweri, Macalder and Bande had a population of between 6 to 160 persons per square kilometer. Mukuro and Ayego regions had a population of 161 to 261 persons per square kilometre. Rakwaro, Awendo, Karungu and Muhuroni registered population of about 399 to 772 persons per square kilometer. Major towns in the Sub-county like Migori and Rongo took the lead with 773 to 1,514 persons per square kilometer.

Figure 4.2: Migori Sub-county’s Human Population for 2010

The UN adjusted gridded population for the year 2010 was selected for this study because it reflects population for the Sub-county only a year after the 2009 census. Figure 4.2 above indicates the UN adjusted gridded population data for

Migori County for the year 2010.Just like in the year 2000, human population in

Migori Sub-county is higher in the urban areas such as Karungu, Mihuru, Rongo and Migori. However, there was an increase in the number of persons per square kilometer. In the year 2010, areas around Ndhiwa, Nyakweri, Macalder and

Bande had a population of between 7 to 191 persons per square kilometer.

Mukuro and Ayego regions had a population of 192 to 311 persons per square kilometer. Rakwaro, Awendo, Karungu and Muhuroni registered population of about 475 to 920 persons per square kilometer. Major towns in the Sub-county like Migori and Rongo took the lead with 921 to 1,806 persons per square kilometer. This could be because these are commercial and they attract people for businesses and employment given that agriculture is not as productive as it used to be. The available land for agriculture has been on the decline whereas the available arable land is continually losing its fertility coupled with unpredictable weather patterns.

According to Benin et al., (2010), the dramatic growth in population in an area is largely driven largely by increasing numbers of people surviving to reproductive age due to improved health care. Other explanations for the rapid human population growth are improved health care and economic status together with availability of resources in an area. These play a major role in the rate at which population grows as a result of reduced maternal and infant mortality (Entwisle &

Stern, 2012). Other factors could explain this phenomenon is favourable land ownership policies that cause migration of people into a place as well as the productivity of the land therein (UNEP, 2002).

Figure 4.3: Migori Sub-county’s Human population for the year 2020

Figure 4.3 shows the projected gridded population for Migori Sub-county for the year 2020. The projection is based on the official results of the 1999 and 2009 censuses. It assumes that the population will continue increasing at the growth rates of years 1999 and 2009. Figure 4.3 above indicates the projected UN

adjusted gridded population data for Migori Sub-county for the year 2020. Human population in Migori Sub-county is expected to increase in all the regions. As per the trend the urban areas such as Karungu, Mihuru, Rongo and Migori will continue having the highest population per square kilometer in the Sub-county. In the year 2020, areas around Ndhiwa, Nyakweri, Macalder and Bande are expected to have a population of between 8 to 221 persons per square kilometer. Mukuro and Ayego regions will have a population of 222 to 360 persons per square kilometre. Rakwaro,Awendo, Karungu and Muhuroni are expected to register population of about 550 to 1,065 persons per square kilometer. Major towns in the

Sub-county which are Migori and Rongo will have a population of 1,066 to 2,088 persons per square kilometer.

Population dynamics is one of the key factors affecting land resources around the globe. The rise in the size of human population happening in Migori Sub-county is not different from many parts of the country and the world respectively.

According to Hawken (2005), several factors have acted in play to contribute to this phenomenon. They include high birth rates, low death rates, improvement in medical services and increase in technology. Other factors include ignorance in family planning and birth control practices, absence of violence, wars and epidemics (UNPC, 2003).

4.3 Trends and Pattern of Land Resources

Cropland, Forestland and Water resources were the three land resources that this study focused on. Their trends were assessed through the use of satellite images.

The three resources were classified as Waterbody, Cropland and Forestland in accordance with the Food and Agriculture Organization’s classification system.

The entire Sub-county’s land cover was derived so as to enable analysis of losses and gains to take place. The transition of these three resources occurs in relation with other land cover types as well.

4.3.1 Land Use and Land Cover Mapping

Land Use and land cover is important when it comes to addressing many environmental problems. Uncontrolled development, poor management of resources, shrinking pasture, loss of forest cover and declining environmental quality pose risk to the environment. Therefore, as part of this study Land Use and

Land Cover mapping was done to show the various changes in the land uses over the years.

Land Use (activities taking place on land) and Land Cover (physical characteristics of the land surface) mapping was done for five epochs. Decisions about Land Use and Land Cover can dictate what kind of vulnerabilities land resources will face presently and in future. These epochs were chosen to coincide with Land the census years in Kenya. The five epochs were 1979, 1989, 1999,

2009 and 2013. 2013 was not a census year but it was chosen to show the land uses three years ago. Landsat satellite images were used to conduct the mapping.

Figures 4.4, 4.5, 4.6, 4.7 and 4.8 indicate the land cover maps that were generated.

1979 Land Use and Land Cover Map

Figure 4.4: 1979 LULC Map

1979 was selected as one of the historical images to show the condition of land resources thirty four years prior to 2013. 1979 LULC map (Figure 4.4) shows that cropland was the dominant class. Plantation which is mostly sugarcane covered several hectares of land. There were scattered patches of forestland and riverine vegetation along the major rivers in the Sub-county. The only visible bare area is the one along the lake. Wetland was substantial in size. Shrubland and grassland were smaller in area in relation to other land use and land cover classes. Visible settlements include Awendo, Migori and Macalder.

In 1989, the dominant land use and land cover class was cropland (Figure 4.5 below). However, there was an increase in grassland and shrubland. The bare areas reduced due to transition to grassland. The wetland’s area reduced compared to that of the year 1979. Forestland and riverine covered substantial area in the

Sub-county.

Land use and land cover map for 1999 (Figure 4.6) indicates cropland as the major class. Shrubland reduced compared to the year 1989. Settlements around

Migori town increased greatly between the years 1989 and 1999. Forestland increased slightly in the ten year period, between 1989 and 1999. There were minimal changes in size of the wetland. There was transition of grassland to bare areas.

2009 is the year that we had the latest census in Kenya. In the year 2009 (Figure

4.7) cropland was the major class. Settlements around Rongo and Migori towns increased between the years 1999 and 2009. Wetland increased due to presence of

increased vegetation on the lake and shores. Grassland increased in the year 2009 in comparison to the year 1999.

2013 land use and land cover map was generated to show the state of the land resources just four years after the 2009 census. Just like the other years under study, cropland was the major land use and land cover class in 2013 (Figure 4.8).

The size of the wetland is reduced between 2009 and 2013. There was an increase in settlements around major towns in the Sub-county like Migori, Rongo and

Macalder. There was a decline in grassland between 2009 and 2013, However, shrubland increased in 2013. This could have happened as a result of the undergrowth that remained after trees in the forests were cleared.

1989 Land Use and Land Cover Map

Figure 4.5: 1989 LULC Map

1999 Land Use and Land Cover Map

Figure 4.6: 1999 LULC Map

2009 Land Use and Land Cover Map

Figure 4.7: 2009 LULC Map

2013 Land Use and Land Cover Map

Figure 4.8: 2013 LULC Map

Table 4.2: Area Covered by Waterbody, Forestland and Cropland

Waterbody, Forestland and Cropland Area (Ha)

Year

Land Use 1979 1989 1999 2009 2013 Cropland 182,416.2 182,650.8 181,504.2 178,111.7 179,407.7

Forestland 1,560.5 2,593.6 3,828.8 3,519.4 2,475.1

Waterbody 55,528.6 55,328.1 55,244.4 54,974.2 54,767.9 Total 239,505.3 241,807.7 240,577.4 236,605.3 236,650.7

Table 4.2 shows the areas covered by Cropland, Waterbody and Forestland for the years 1979, 1989, 1999, 2009 and 2013. The areas have been inconsistent over the period. Cropland area was more than 180,000 for the period 1979-1999 and then reduced in 2009 but later regained in 2013. Forestland had the least area in 1979 but increased to more than 2,593.6ha in 1989. In 1999, further increased but a decline was recorded in 2009. This further decreased to 2,474ha in 2013 as compared to 3,519ha in 2009. Waterbodies have experienced a gradual decline since 1979. Waterbody area was 55,528ha in 1979 and dropped to 54,767ha in

2013.

4.3.2 Land Use and Land Cover Change Mapping and Statistics

LULCCs driven by increase in human population may have positive or negative impacts on the land resources. LULC analysis was done as part of the study.

LULCC maps were generated to show the various changes from 1979-2013. Four change pairs were generated, mainly: 1979-1989, 1989-1999, 1999-2009 and

2009-2013. The first three had an interval of 10 years while the latter was generated to show the long-term changes. Statistics were derived to show the

changes between the three resources; Waterbody, Forestland and Cropland and other Land Cover classes. Figure 4.9 is a land cover change map showing the different changes in land cover classes for the period 1979- 1989.

Figure 4.9: 1979-1989 LULC Change map

4.3.2.1 Land Use and Land Cover Change and Statistics for Period 1979-

1989

1979-1989 was one of the change pairs used to show changes in Cropland,

Waterbody and Forestland between this set of years.

Table 4.3: Acreage change in Cropland, Waterbody and Forestland from

1979-1989

LULC Change 1979-1989 Area(Ha) Cropland to Forestland 1,834.75 Cropland to Grassland 196.98 Cropland to Plantation 144.23 Cropland to Riverine 1,133.92 Cropland to Settlements 104.34 Cropland to Shrubland 684.82 Cropland to Waterbody 169.64 Cropland to Wetland 12.12 Forestland to Cropland 831.04 Forestland to Grassland 38.60 Forestland to Riverine 2.23 No Change in Cropland 178,256.28 No Change in Forestland 688.66 Plantation to Cropland 105.17 Riverine to Cropland 2,474.09 Riverine to Forestland 56.57 Settlements to Cropland 33.68 Settlements to Forestland 0.17 Shrubland to Cropland 52.29 Shrubland to Forestland 10.98 Waterbody to Cropland 145.89 Waterbody to Forestland 11.97 Wetland to Cropland 1,011.89

Table 4.3 and figure 4.9 show the changes in LULC with emphasis on Cropland,

Waterbody and Forestland. Cropland, Waterbody and Forestland went through various transitions during the ten-year period. Some of the most significant

changes in terms of area are highlighted in the table above. Some of the changes have no negative effect on the three land resources that form part of this study.

One of the positive changes was from cropland to forestland by 1,834.75 hectares between 1979 and 1989. This can be attributed to increase plantation of trees on farms. One negative change was the conversion of 1,011.87 hectares of wetland to cropland. Wetlands play a critical role in the ecosystem; therefore their loss may cause an imbalance.

The demand for food by the ever growing population has led to an increase in croplands at the expense of forestlands, water bodies, grasslands and shrublands.

The ever shrinking size of arable land causes people to fringes where land is believed to be more fertile and thus farers can expect good harvests. The fringes include the forested areas and the waterbodies. This explains the phenomenon experienced in the study where the croplands increased in size whereas the waterbodies decreased in size. According to Billah and Rahman (2004), the other reason as to why there could be an increase in the area covered by croplands is the presence of favorable weather conditions that motivated people to go into farming. This coincides with the fact that the image used to process the results for the period between 1979 and 1989 was taken during the rainy season.

4.3.2.2 Land Use and Land Cover Change and statistics for Period 1989-1999 This change pair was used to show the transition of land resources from 1989-1999.

Figure 4.10: 1989-1999 LULC Change map

Table 4.4: Change in Cropland, Waterbody and Forestland from 1989-1999

LULC Change 1989-1999 Area (Ha) Cropland to Bare areas 33.17 Cropland to Forestland 1,861.97 Cropland to Plantation 412.53 Cropland to Riverine 862.48 Cropland to Settlements 443.67 Cropland to Waterbody 147.24 Cropland to Wetland 180.18 Forestland to Cropland 574.26 Forestland to Plantation 3.68 Forestland to Riverine 188.56 Forestland to Settlements 28.82 Forestland to Waterbody 7.78 Grassland to Cropland 306.09 No Change in Cropland 178,709.59 No Change in Forestland 1,790.49 Other Changes 61,230.78 Riverine to Cropland 1,077.54 Riverine to Forestland 31.25 Settlements to Cropland 10.03 Shrubland to Cropland 511.66 Shrubland to Forestland 142.99 Waterbody to Cropland 127.68 Waterbody to Forestland 2.05 Wetland to Cropland 226.70

Table 4.4 and Figure 4.10 show the changes in Land Use and the three land resource trends for Waterbody, Cropland and Forestland between 1989 and 1999.

During this period several inter-land cover changes occurred. There were both positive and negative changes. However, the alarming ones were transitions from riverine to cropland by 1,077.54 hectares and forest to cropland by 574.26 hectares. One great positive change was the conversion of 1,861.97 hectares of cropland to forestland. Many people plant trees on their land for commercial purposes especially eucalyptus.

The reduction in the size of the area covered by water bodies between 1989 and

1999 can be attributed to the amount of rainfall experienced during the season.

When rainfall levels are low, the riverine recedes. The other explanation for the decrease in the size of water bodies is the cultivation of the riverines. The soils near the waterbodies are considered to be more fertile as a result of siltation. This attracts people to cultivate even near those places in order to increase their chances of more harvest.

Land Use and Land Cover Change between 1999-2009

Figure 4.11: 1999-2009 LULC Change map

Table 4.5: Change in Cropland, Waterbody and Forestland from 1999-2009

LULC Change 1999-2009 Area (Ha) Bare areas to Cropland 33.17 Cropland to Bare areas 601.94 Cropland to Forestland 1,394.82 Cropland to Grassland 333.17 Cropland to Plantation 79.97 Cropland to Riverine 918.13 Cropland to Settlements 396.59 Cropland to Shrubland 79.81 Cropland to Waterbody 447.98 Cropland to Wetland 2,774.77 Forestland to Cropland 1,726.00 Forestland to Riverine 97.60 Forestland to Settlements 0.01 Forestland to Waterbody 26.71 No Change in Cropland 174,476.99 No Change in Forestland 1,978.44 Other Changes 61,391.57 Plantation to Cropland 280.35 Plantation to Forestland 3.68 Riverine to Cropland 1,074.49 Riverine to Forestland 71.01 Settlements to Cropland 61.54 Settlements to Forestland 32.83 Shrubland to Cropland 6.18 Shrubland to Forestland 37.86 Waterbody to Cropland 440.42 Waterbody to Forestland 0.78 Wetland to Cropland 12.56

Table 4.5 indicates the numerous changes in cropland, waterbody and forestland between 1999 and 2009. Some of the great changes in terms of area included conversion of cropland to forestland by 1,394.82ha, forestland to cropland by

1726ha and riverine to cropland by 1,074.49ha. Some were negative like transition from forestland to cropland and riverine to cropland. This is tree cover that was lost. One positive change was the conversion of cropland to forestland.

This could be as result of the efforts by the government and other agencies sensitizing and encouraging the residents on the importance of planting trees on 72

their farms. In the recent years, the government has been making drastic efforts to remove people who have encroached riparian areas and thereafter planting trees to conserve them.

4.3.3 Land Use and Land Cover Change for Epoch 1979-2013

1979- 2013 change pair shows changes that occurred in the entire study period of thirty-four years. These changes do impact greatly on cropland, waterbody, forestland and the environment at large. Positive changes include the conversion of cropland to forestland by 1,742.40ha and cropland to wetland by 1,192.96ha. A lot of urbanization as a result of development has also taken place in the Sub- county in the thirty-four-year period. Cropland that was converted to settlements was 1,132.52ha. Many towns that did not exist in 1979 have come up. Migori town which is the capital of the Sub-county has expanded. Negative changes include the conversion of 2,527.09ha of riverine to cropland and 853.18ha of forestland to cropland.

With increase population there is increased need for arable land for food production to feed people but this increase without check may have detrimental effects to the environment. In many rural areas farm size is shrinking as farmers continue to subdivide holdings among their children. This has led to search for alternative land for cultivation through forest encroachment (Starke, 2005). Social inequality within the population leads to skewed structures of land ownership and leads to pressures towards conserved or protected areas. This leads to land degradation (UNEP, 2002)

Figure 4.12: 1979-2013 LULC Change map

Table 4.6: Change in Cropland, Waterbody and Forestland from 1999-2009

LULC Change 1979-2013 Area (Ha) Cropland to Bare areas 79.70 Cropland to Forestland 1,742.40 Cropland to Grassland 196.98 Cropland to Plantation 144.23 Cropland to Riverine 573.33 Cropland to Settlements 1,132.52 Cropland to Shrubland 1,335.72 Cropland to Waterbody 59.51 Cropland to Wetland 1,192.96 Forestland to Cropland 853.18 Forestland to Grassland 38.60 Forestland to Riverine 2.23 Forestland to Shrubland 10.05 No Change in Cropland 175,958.90 No Change in Forestland 656.46 Other Changes 62,171.55 Plantation to Cropland 105.17 Riverine to Cropland 2,527.09 Riverine to Forestland 51.20 Settlements to Cropland 17.65 Settlements to Forestland 10.89 Shrubland to Cropland 0.50 Waterbody to Cropland 204.72 Waterbody to Forestland 23.67

4.3.4 Land Use Activities

To build up on the land use and land cover analysis, questionnaires were administered to Migori Sub-county residents to find out various issues such as land ownership, land size and land activities. Table 4.7 indicates the information on land activities.

Table 4.7 Land Use Activities

Land factor Characteristic Frequency Percentage Land Lessor (Landlord) 93 69.4 Ownership Leasee 41 30.6 Total 134 100 Land size Less than one acre 38 40.9 1-5 acres 41 44.1 6-10 acres 11 11.8 More than 10 acres 3 3.2 Total 93 100 Land Cultivation 29 31.2 Activities Mining 16 17.2 Livestock Rearing 9 20.7 Fallow land 7 17.5 Fish farming 32 13.4 Total 93 100

From the findings in Table 4.7, majority of the respondents (69.4%) indicated that they own the land they currently occupy while 30.6% indicated that they do not own the land they currently occupy. The type of land tenure or ownership has a bearing on how the land is used. Respondents carrying out farming activities on their own pieces of land are more likely to adopt farming methods that are sustainable since they enjoy security of tenure. On the other hand, people conducting farming activities on rented or public land don’t enjoy security of tenure and thus they don-t feel entitled with being too careful of the activities they conduct on such land as they know they are there only temporarily.

The study further sought to find out the size of the land of those who said they own the land which they currently occupy. From the findings, 44.1% of the respondents indicated that the size of the land they occupy is 1-5 acres, 40.9% less than 1 acre, 11.8% 6-10 acres while 3.2% indicated that the size of the land they occupy is more than 10 acres. It was important to know the activities carried out 76

in these lands. Activities indicate the amount of pressure on land. From the findings, 13.4% of the respondents indicated that they use their land for fish farming, 31.2% for cultivation, 17.2% for mining, 20.7% for livestock rearing while 17.5% indicated that their land is fallow. With the exception of fish farming and fallow land, cultivation, mining and livestock rearing can have numerous impacts on the land. Some respondents have come up with ways in which they conserve their parcels of land which is a positive indication. With the increase in demand for food and cash crops, more intensity and pressure are exerted on land to maximize production hence the more the likelihood of such parcels becoming degraded. The increasing population has also led to more excisions to accommodate the higher number of people inheriting their ancestral land. Smaller parcels of land thus push many towards the fringes including forests and riverine where they are likely to get “idle” land for cultivation.

Table 4.8 Land Resources Conservation Measures

Land Resources conservation Frequency Percentage measure Agroforestry 7 5.2 Mulching 31 23.1 Crop rotation 15 11.2 Application of fertilizer 43 32.1 Application of manure 17 12.7 Erosion control 9 6.7 Irrigation 12 9.0 Total 134 100

Application of fertilizer is the most preferred method for land conservation at

32.1% of the respondents. However, it is important that over use of these inorganic fertilizers can lead to eutrophication. Therefore soil analysis should be conducted to know the nutrient that is lacking in the soils and right amount to be

added. Mulching came in second at 23.1% which is a good measure not only for the soils but also for water conservation. Application of manure was at 12.7%.

Crop rotation was practiced by 11.2% of the respondents. Crop rotation helps in restoring nutrients and also aids in keeping away crop parasites such as cutworms and termites or reducing their infestation. Erosion control, irrigation and agroforestry were the lowest at 6.7%, 9.0% and 5.2% respectively. Agroforestry need to be practiced more in Migori Sub-county due to its numerous benefits.

Agroforestry helps in soil erosion by both wind and water by holding soil together, Nitrogen-fixing trees and decomposing trees add nutrients thus improving soil fertility, fruits and pods from trees that are fit for consumption by humans and animals serve as food, Leaves and twigs can be used as fodder, timber and fuel wood is provided by the pruned branches and some trees like the neem tree have medicinal uses. A positive thing is that of the 134 respondents, all used one or more ways of conserving land resources. More awareness would help in increasing land conservation in the region.

Plate 4.1: Fish farming in Migori Sub-county

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4.4 Relationship between Human Population Growth, Forestland, Cropland and Water Resources in Migori Sub-county from 1979-2013

Relationship between human population growth, forestland, cropland and water resources in Migori Sub-county is debatable. Studies indicate that in the last fourty years there has been a decrease in forest cover, increase in cropland, expansion in forest cover and decline in cropland (Turner et al., 1994). Data from both the national censuses and United Nation’s adjusted gridded population data indicate that population increased from 2000 to 2010 in the Sub-county. Likewise, the populations for 2020 indicate an expected growth in the Sub-county.

Population growth affects water resources, forestland and cropland in the Sub- county. In terms of quantity, the three resources that were studied do not show a steady decline or increase. Cropland is the major resource in the Sub-county. This can be attributed to farming being the main source of income in the area.

Forestland increased gradually from 1979 up to 1999 and then started decreasing in 2009 and 2013. The main water body being the Lake has been decreasing from

1979. Presence of hyacinth has played a role in the reduction in size of the lake.

On the other hand, human population has increased from 1979 to 2013.This means that more land has to be converted from Forestland and Grassland to pave way for Cropland. Table 4.9 indicates the statistics for the three land resources and population for 1979, 1989, 1999 and 2009.

Table 4.9: Population, Cropland, Forestland and Waterbody areas for 1979,

1989, 1999 and 2009

Year Population Cropland Forestland Waterbody 1979 817,601 182,416.2 1,560.5 5,5528.6 1989 1,066,583 182,650.8 2,593.6 5,5328.1 1999 514,897 181,504.2 3,828.8 5,5244.4 2009 661,084 178,111.7 3,519.4 5,4974.2

(The population for 1979 and 1989 represents Homa Bay, while 2009 is summation of Rongo and Migori). Table 4.9 shows the relationship recorded areas of Cropland, Forestland and Waterbody in Migori Sub-county for the years

1979, 1989, 1999 and 2009; and the population for the concurrent years. In 1979 and 1989 the then Migori Sub-county was part of Homa bay County and it is evident that the population increase was recorded from 1979 to 1989. Similarly, during the decade 1999 to 2009, Migori Sub-county recorded an increase in the population. The trend of Cropland and Forestland is not that of a continuous increase throughout the years unlike Waterbody (water resources) that registered an increased trend. Human beings are known to influence the resources in one way or another. For example, with increased population there’s need for arable land to feed the population. This leads to clearing of forests and other vegetation.

However, in this case Forestland registered a continuous growth which is a positive thing. Waterbody which represents water resources recorded a gradual decline. The presence of hyacinth on the lake has played a part in this.

In order to further show the relationship between human population and land resources under study, t-tests were conducted. T-test was selected due to ease of gathering the required data (mean), ease of calculation using Microsoft Excel, which aids persons with minimal statistical expertise and simplicity of interpretation of results. The three resources (cropland, forestland and water resources) and population were analyzed. The results are as follows:

Table 4.10: T-test Results for Population and Cropland

Population and Cropland t-Test: Paired Two Sample for Means

Variable 1 Variable 2 Mean 765041.25 181170.73 Variance 55689736650 4403556.502 Observations 4 4 Pearson Correlation 0.502 Hypothesized Mean Difference 0 df 3 t Stat 4.970 P(T<=t) two-tail 0.02 t Critical two-tail 3.182

Table 4.10 indicates the t-test results for population and cropland. The probability for the two tail was at approximately 0.02. This shows that there was a significant difference between the means of population and cropland. The interpretation of this result is that an increase in population greatly affects the size of land under cultivation (cropland). Since an increase in population doesn’t increase the size of land, what follows is that there is intensification on the available land or more croplands are hived from other forms of land cover including waterbodies, forests, grasslands, shrublands or bare lands.

Table 4.11: T-test Results for Population and Forestland

Population and Forestland t-Test: Paired Two Sample for Means

Variable 1 Variable 2 Mean 765041.25 2875.575 Variance 55689736650 1044026.896 Observations 4 4 Pearson Correlation -0.635 Hypothesized Mean Difference 0 Df 3 t Stat 6.441 P(T<=t) two-tail 0.008 t Critical two-tail 3.182

Table 4.11 indicates the t-test results for population and forestland. The value for the two tail was at approximately 0.008. This shows that there was a significant difference between the means of population and forestland. This implies that the size of population has an impact on Forestland (either positive or negative).

Table 4.12: T-test results for Population and Waterbody

Population and Waterbody t-Test: Paired Two Sample for Means Variable 1 Variable 2 Mean 765041.25 55268.825 Variance 55689736650 52799.016 Observations 4 4 Pearson Correlation 0.420 Hypothesized Mean Difference 0 Df 3 t Stat 6.018 P(T<=t) two-tail 0.010 t Critical two-tail 3.182

Table 4.12 indicates the t-test results for population and waterbody. The probability for the two tail was at approximately 0.010. This shows that there was a significant difference between the means of population and waterbody.

Based on the above t-test results the null hypothesis was rejected. It is evident that human population growth has some impact on the three land resources: cropland, forestland and waterbody in Migori County.

The results of the analyses depict the concerns, the status of land resources and their vulnerability as a result of continued population growth in the area; thus, the study acknowledges the role played by human population growth in land degradation. The impacts are far reaching both on the existing population and the land resources in question. Land cover and land use changes in the area increase the susceptibility of an area to land degradation. The results of land cover analysis inform the different forms of conversions and modifications which can largely be attributed to activities resulting from human population dynamics. This includes a reduction in forest cover in the area which exposes the area to changes in weather patterns and unfavorable responses to rainfall by the ground. This affects productivity of land in the area. Clearing of forests also affects the waterbodies as reduced rainfall leads to shrinking of rivers while the exposure to direct sunlight leads to massive evaporation. The impact of human population growth on the three land resources (waterbodies, forestlands and croplands) is intertwined and it is difficult to look at the impacts in isolation.

CHAPTER FIVE: SUMMARY, CONCLUSIONS AND

RECOMMENDATIONS

5.1 Introduction

This chapter presents the summary of key data findings, conclusion drawn from the findings highlighted and recommendation made there-to. The conclusions and recommendations drawn were focused on addressing the objectives of the study.

5.2 Summary of the Findings

The main purpose of this study was to establish the effect of human population growth on the use and trends of land resources in Migori Sub-county. The study relied on satellite data for the analysis of land resources and the official national census reports for the years of interest. Gridded population data was also used to bring out the population counts at a smaller scale of approximately one square kilometer. Questionnaires were distributed to the farmers in the Sub-county. Field visits were conducted as a means of verifying the land cover and to observe the situation on the ground.

From the study it is clear that that human population has been growing in Migori

Sub-county located in western part of the country. Land Use and Land Cover analysis also indicated that the three types of resources under study have been affected due to increase in human population. Cropland which is the major land cover and land resource recorded minimal changes from 1979 to 2009. The major change was recorded between 1999 and 2009 with a drop-in area by 3,392.5 Ha.

Changes in forestland have been relatively positive. There has been an increase in forest area in the Sub-county with a drop between 1999 and 2009. Numerous measures have been put in place from the year 2000 to see an increase in forest cover by various stakeholders. Advances in technology coupled with availability of satellite images have made it easier to monitor changes in forests.

Deforestation and reforestation are mainly driven by human beings though some trees have the potential to regenerate after sometime. Increase in human population calls for increase in arable land to feed the masses. A clear trend for changes in Forestland and Cropland was not established. However, it was clear that are of water resources has been decreasing gradually. The study further established through statistical analysis such as t-test that population impacted on the land resources in Migori Sub-county.

Land use changes indicated transition from the three main resources to other resources in the area. Both positive and negative changes in area coverage were recorded as losses and gains. Gains are increases in forests, shrubs and riverine.

Losses indicate degradation or deforestation, for instance, conversion of forests, shrubland to grassland and grassland to cropland or settlements. However, it is important to note that there are changes that are due to two periods of transition.

Grasslands easily generate to shrubland and shrubland can be converted to grassland. Croplands are either bare or have grasses after harvest.

Analysis of the questionnaires administered to the locals revealed that majority of the respondents who were interviewed owned their land as indicated by 69.4 %.

This can be attributed to culture of the residents who inherit land from their

parents. Land ownership can have both positive and negative impacts on the resources. Some farmers may feel that they are at liberty to do whatever they wish on their land such as cutting trees which is a negative thing if not controlled.

Likewise land ownership grants the farmers rights to make positive decisions regarding the land practices. All of the farmers interviewed indicated that they use at least one form of land conservation measures. These included use of manure, agroforestry, crop rotation or use of mineral fertilizers. It was evident that there is over use of mineral fertilizers at 32.1 % (See Table 4.8). There is need for embracing other farming methods like agroforestry more.

5. 3 Conclusions

The outcome of this and other related studies need to get to the end users including policy makers, land use planners and the community. The results of the study reveal that human population growth will continue to take place for years to come based on the official census reports and projections conducted by the United

Nations and other research institutions like Columbia University. On the other hand, land resources are finite and continue to be depleted at a fast rate with each passing day. Migori Sub-county in Migori County has experienced tremendous human population growth which has interfered with the land resources. There is need to adoption checks that will address the rapid population growth. This will help reduce the pressure on land resources.

Some of the changes in land resources are inevitable with the increasing population. For example, arable land has to increase for the supply of more food

to the huge population. Demand for water and forest products also grows with the increase in masses. Urban areas also grow and increase in number as people migrate to towns in search of employment or businesses. The question that should linger in our minds is whether the available resources will be able to meet the needs of mankind, not only now but in the years to come. The findings in this study further affirm the importance of technology (GIS) in management of land resources. The variability in terms of losses and gains on land resources would have been difficult to quantify in the absence of such technology.

Some of the farmers in Migori Sub-county practice proper land management practices however, there is still need for more education on the best farming methods. Population control might be a challenging matter but with proper measures and guidelines in place the growth can be in a manner that does not exceed the land’s carrying capacity. However, if the present scenario of population growth persists, there arises the need for strategic interventions in order to safeguard the land resources for posterity. The existing land related plans and policies need to be adopted and implemented fully. There is also the need for education to the community members on good land management practices including soil and water conservation measures and enhanced soil fertility. This will help maximize the output from farming activities. Most importantly is that any anthropogenic activity should be undertaken with the aim of achieving sustainable development. This will ensure that the future generations do not pay for the mistakes of the current generation.

5.4 Recommendations

From the findings and conclusions of the study, some of the recommendations that are suggested include:

1. The various agencies in the Sub-county that deal with population such as

National Population Council should educate the masses on importance of having growth rate that is manageable by the state. Importance of family planning and raising number of children that one can take care of in terms of provision of quality health and education need to be emphasized. Migori Sub-county being a rural area will definitely have persons who object family planning but continuous prodding and convincing can yield positive results.

2. The trends in the land resources based on the land use and land cover analysis conducted indicate that there are both positive and negative changes in the resources studied. Proper land management is necessary so as to safeguard these finite resources. There is need for farmer education on proper farming methods such as conservation agriculture. Secondly, environmental awareness should start at the earliest age possible. Rain water harvesting for irrigation, agroforestry and proper waste management need to be the norm so as to conserve the land resources. Additionally, this study recommends for imposition of rules and regulation of charcoal burning in the communities. To prevent high rates of deforestation, the relevant agencies should impose heavy fines on law breakers.

Individuals can be further educated and encouraged to use energy alternatives such as biogas for cooking in their homes.

3. Hyacinth has played a major role in the reduction of acreage of Lake

Victoria. This weed has affected both fishing which is the main source of livelihood of people of Migori Sub-county and the environs as well as the quality of the water. Harvesting of hyacinth which has started in some parts of the lake is one of the ways of reclaiming the lake. Regulations should be put in place to avoid dumping of wastes into the water.

5.5 Suggestion for Further Studies

The following recommendations are offered as possible ways to improve this study:

1. There is continuous improvement and advancement in technology. Future land use and land cover analysis can be conducted using better images of high resolution such as Sentinel satellite images that were released recently by the

European Union and are freely available. This would aid in producing detailed analysis of the land cover.

2. Human population growth is just one of the many factors that affect land resources such as water resources. Therefore, there is need for comprehensive analysis of water quality in the Sub-county. Lab tests of water samples and the role of hyacinth and other pollutants on water resources will help in coming up with the best measures on how to preserve water.

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APPENDICES

Appendix I: Summary of Questionnaire Details

This research study had a sample size of 150 respondents. Out of this sample size,

134 questionnaires were filled and returned to the researcher which represents a sample size of 89.3% response rate. This response rate was excellent and conforms to Mugenda and Mugenda (1999) stipulation that a response rate of

50% is adequate for analysis and reporting; a rate of 60% is good and a response rate of 70% and over is excellent. This commendable response rate can be attributed to the data collection procedure, where the researcher personally administered questionnaires and waited for respondents to fill in, kept reminding the respondents to fill in the questionnaires through frequent phone calls and picked the questionnaires once fully filled.

A Demographic Characteristics

Social- demographic Characteristics of the Respondents

The demographic characteristics of the respondents were investigated in the first section of the questionnaire. They are presented in this section under gender, age, education level, gender of the household head and current occupation. The findings are summarized in Table 4.1. 51.5% those interviewed were male while

48/5% were female. Out of those interviewed, the highest number (44%) was schooled up to secondary school level. This increases the level of response and

understanding to questions asked. 33.6% of the total number of respondents derives their income from farming, being their main occupation.

Table A: Demographic Characteristic of the Respondents

Demographic Characteristic Frequency Percentage Factor Gender Male 69 51.5 Female 65 48.5 Total 134 100 Age 21-30 13 9.7 31-40 49 36.6 41-50 38 28.4 51-60 26 19.4 Above 60 8 6.0 Total 134 100 Education level None 3 2.2 Primary 31 23.1 Secondary 59 44.0 Tertiary 41 30.6 Total 134 100 Gender of Male 89 66.4 Household Head Female 45 33.6 Total 134 100 Occupation of Business 32 23.9 Respondents Employed 21 15.7 Farming 45 33.6 Sand harvesting 19 14.2 Mining 17 12.17 Total 134 100

B. Sources of Water

The study also sought to establish where the respondents obtain water for carrying out the activities on their land. The findings are as indicated in Table B. Majority of the respondents (51.6%) obtain their water from Rivers, 36.6% from wells/boreholes while 11.8% use rain water. This has a bearing on the reduction or the increase of the size of the rivers.

Table B: Sources of Water

Source of Water Frequency Percentage River 48 51.6 Rain water 11 11.8 Wells/boreholes 34 36.6 Total 93 100

C: Sources of Energy

The study further sought to establish the form of energy that the respondents use for cooking and other household activities. The findings are as indicated in Table

Table C: Sources of Energy for the Households

Form of Energy Frequency Percentage Liquid Petroleum Gas (LPG) 16 11.9 Paraffin/kerosene 35 26.1 Charcoal 83 61.9 Total 93 100

According to the findings, 61.9% the respondents indicated that the form of energy they use for cooking and other household activities is charcoal, 26.1% paraffin/kerosene while 11.9% indicated that they use liquid petroleum gas

(LPG).

D: Use of Crop Residue

The study also sought to find out how the forty-five respondents who are farmers dispose the crop residues from the farm/ cultivated land. The findings are as indicated in Table 4.4. According to the findings, 55.2% of the respondents

indicated that they use the residue from the farm/cultivated land as animal feed,

23.1% as manure while 21.6% indicated they burn the crop residues from the farm/cultivated.

Table D: Use of crop residues from the farm/ cultivated land

Type of crop residue disposal Frequency Percentage Burning 9 20 Use as animal feed 25 55.5 Use as manure 11 24.5 Total 45 100

E: Soil and Water Conservation Measures

The study also sought to find out the soil and water conservation measures that the respondents undertake on their farm. The findings are as indicated in Table E.

Table E: Soil and Water Conservation on Farmlands Soil and Water conservation measure Frequency Percentage Agroforestry 7 5.2 Mulching 31 23.1 Crop rotation 15 11.2 Application of fertilizer 43 32.1 Application of organic manure 17 12.7 Erosion control 9 6.7 Irrigation 12 9.0 Total 134 100

From the findings, 32.1% of the respondents indicated that they conserve soil and water in their farm by applying fertilizers, 23.1% by mulching, 12.7% by applying organic manure, 11.2% by crop rotation, 9.0% by irrigation, 6.7% by erosion

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control while 5.2% indicated that they conserve soil and water in their farm by agroforestry.

Further, the ministry official from the Ministry of Agriculture indicated that the ministry offers extension services to the farmers. In addition, they have extension officers who visit the farmers and educate them on better farming practices; they give the farmers fertilizers with the help of the government so as to increase their yields; High yielding varieties and drought-resistant species of maize are sold to farmers at subsidized rates; and during the harvesting season the ministry buys maize from farmers at good rates.

The ministry official from the Ministry of Agriculture went ahead to indicate that challenges are faced by the farmers in the Sub-county include erratic rains which lead to poor yields; poor soils in terms of nutrients due to over planting each season without rest or addition of fertilizers; high cost of fertilizers and high- yielding varieties; unreliable market prices as prices keep on fluctuating; weeds such as striga affect yields.

On the soil preservation services that are applied by farmers, the ministry official from the Ministry of Agriculture indicated that agroforestry is used to increase nutrients in the soil and improve income, mulching, use of organic manure, crop rotation and use of terraces in hilly areas.

In addition, the ministry official from the Ministry of Agriculture expressed that the measures that have been put in place by the Ministry to enhance proper land management by the farmers include use of extension officers to educate the

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farmers on proper land management practices; offering incentives to farmers who grow trees on their farms so as to prevent soil erosion and add nutrients to soils.

This increases income because farmers are able to get firewood, fodder and fruits from the trees; and digging terraces in hilly areas to prevent soil erosion.

The ministry official at the ministry of water expressed that major sources of water in Migori Sub-county is River Migori, Lake Victoria, Boreholes, Rain water and piped water (only in the town area). Further, the official indicated that the major causes of water contamination in the area include animal dung when rivers are taken to the river to drink water; sewage gets its way into the rivers; soap and detergents when people wash clothes and dishes, and also bathe in the rivers and lake; and siltation. The ministry conducts water tests once annually. In addition, the official indicated that water quality of rivers has been greatly compromised by the human activities in the area. Poor farming practices cause erosion. Most of this soil gets its way into the rivers and lakes when it rains

The official at the ministry of water indicated that lack of cooperation from the residents is one of the challenges that the ministry faces. People are not willing to let go of their habits like bathing in the river and lack of funds to make piped water available to the residents of Migori Sub-county. The official further indicated that the measures that the ministry of water have in place to ensure the standard water quality is maintained include conducting seminars so as to educate the residents on importance of proper hygiene and need of water conservation measures; doing water quality analysis with the help of other agencies such as

Water Resources Management Authority (WRMA) and Kenya Medical Research

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Institute (KEMRI); partnering with donors so as to ensure that piped water is available to more people in the Sub-county; and supplying water tanks with the assistance of NGOs so as to enhance water harvesting.

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Appendix II: Questionnaire for FarmersHUMAN POPULATION GROWTH AND ITS IMPLICATIONS ON THE USE AND TRENDS OF LAND RESOURCES IN MIGORI COUNTY, KENYA

Pauline Ogola

School of Environmental Studies

Department of Environmental Sciences

Kenyatta University

Research Student

[email protected]

This questionnaire has been designed as part of an academic study to investigate the effects of human population growth on land resources, particularly forestland, cropland and water in Migori Sub-county Kenya. The questionnaire attempts to gather information on human activities within the Sub-county and how these activities are related to the degradation of land resources mentioned above. Declaration: I assure you that your opinion is very important to this study and therefore utmost confidentiality pertaining to any information that you may provide in this survey will be observed. Information provided will be used for academic purposes only.

SECTION 1: HOUSEHOLD DEMOGRAPHIC AND SOCIO-ECONOMIC INFORMATION

Kindly tick as appropriate in the brackets a) Gender of the respondent Male (………..) Female (………..) b) Age of respondent Less than 20 (………..)

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21-30 (………..) 31-40 (………..) 41-50 (………..) 51-60 (………..) Above 60 (………..) c) Educational level of the respondent

None (………..) Primary (………..) Secondary (………..) Tertiary (………..) Others. Please specify (………..) d) Gender of the household head Male (………..) Female (………..) e) What is the current occupation of the respondent? Business (………..) Employed (………..) Farming (………..) Sand harvesting (………..) Mining (………..) Others. Please specify (………..) f) What is the composition of your family members?

Wife/ Wives/Husband (………..)

Males (boys) (………..)

Females (girls) (………..)

SECTION 2: LAND USE ACTIVITIES/ USES OF LAND RESOURCES a) Do you own the land you currently occupy?

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Yes (………..) No (………..)

If yes, what is the size of the land that you own/occupy?

Less than one acre (………..)

1-5 acres (………..)

6-10 acres (………..)

More than 10 acres (………..) b) Which of the following activities do you use your land for? Cultivation (………..) Mining (………..) Livestock rearing (………..) Fallow land (………..) Fish farming (………..) Plantation forest (………..) Others. Please specify (………..) c) Where do you get water for carrying out the activities on your land? River (………..) Rain water (………..) Lake (………..) Dam (………..) Wells/Boreholes (………..) d) Which form of energy do you use for cooking and other household activities? Biogas (………..) Liquid petroleum gas (LPG) (………..) Paraffin/Kerosene (………..) Electricity (………..) Solar (………..) Charcoal (………..)

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Others. Please specify (………..) e) What do you do with the crop residues from the farm/ cultivated land? Burn them (………..) Use as animal feed (………..) Use as manure (………..) Others. Please specify (………..) f) Which of the following soil and water conservation measures do you undertake on your farm? Agroforestry (………..) Mulching (………..) Crop rotation (………..) Applying fertilizers (………..) Applying organic manure (………..) Erosion control (………..) Irrigation (………..) Others, Please specify (………..) g) Any further comments/suggestions/ ideas?

......

THANK YOU FOR YOUR TIME AND CO-OPERATION!

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Appendix III: Questionnaire for Ministry of Agriculture Official

HUMAN POPULATION GROWTH AND ITS IMPLICATIONS ON THE USE AND TRENDS OF LAND RESOURCES IN MIGORI COUNTY, KENYA

Dear sir/madam,

You have been selected to participate in this study and your participation is important. Kindly answer the questions to the best of your ability. You are hereby assured that the information provided will be treated with confidentiality and be applied for academic purposes only. Be assured as well that any images or photographs captured during this field work are to serve none other than academic purposes.

Thank you.

Pauline Ogola

School of Environmental Studies

Department of Environmental Sciences

Kenyatta University

Research Student [email protected]

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Kindly tick as appropriate within the brackets

1. Gender of the respondent

Male (…….)

Female (…….)

2. Has the number of registered farmers been increasing in the Sub-county? Yes (……..) No (……..) 3. Does the ministry keep records of total land under cultivation in the Sub-county? Yes (…….) No (…….) 4. Does the ministry offer extension services to the farmers? Yes (…….) No (…….) If yes, please clarify on the kind of services that you offer to farmers? ……………………………………………………………………………………… ……………………………………………………………………………………… ……………………………………………………………………………………… ……………………………………………………………………………………… ……………………………………………………………………………………… ……………………………………………………………………………………… ……………………………………………… 5. Do the farmers co-operate with the ministry officials? Yes (…….) No (…….) 6. Which challenges are faced by the farmers in the Sub-county? ……………………………………………………………………………………… ……………………………………………………………………………………… ………………………………………………………………………………………

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……………………………………………………………………………………… …………………………….... 7. Which conservation and land management practices have been adopted by farmers in the area? ...... 8. What measures have been put in place by the Ministry to enhance proper land management by the farmers? ……………………………………………………………………………………… ……………………………………………………………………………………… ……………………………………………………………………………………… ………………………

THANK YOU FOR YOUR TIME AND CO-OPERATION!

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Appendix IV: Questionnaire for Ministry of Water official

HUMAN POPULATION GROWTH AND ITS IMPLICATIONS ON THE USE AND TRENDS OF LAND RESOURCES IN MIGORI COUNTY, KENYA

Dear sir/madam,

Thank you.

Pauline Ogola

School of Environmental Studies

Department of Environmental Sciences

Kenyatta University

Research Student

[email protected]

Kindly tick as appropriate in the brackets

1. Gender of the respondent

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Male (………..)

Female (………..)

2. Which are the major sources of water in Migori Sub-county? ……………………………………………………………………………………… ……………………………………………………………………………………… ……………………………………………………………………………………… ……………………… 3. Do you consider the residents have access to sufficient, clean and secure water for use? Yes (……..) No (……..) 4. What are the major causes of water contamination in the area? ……………………………………………………………………………………… ……………………………………………………………………………………… ……………………………………………………………………………………… ……………………………………………………………………………………… ……………………………… 5. Does the ministry conduct water quality tests? Yes (…….) No (…….) If yes, a) What is the duration in which they conduct the tests? ……………………………………………………………………………………… ……………………………………………………………………………………… ……………………………………………………………………………………… ……… b) What is your take on the water quality? ……………………………………………………………………………………… ………………………………………………………………………………………

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……………………………………………………………………………………… ……….. 6. Does the ministry involve the locals in proper water conservation and management activities? Yes (…….) No (…….) 7. What are the challenges that you face as a Ministry? ……………………………………………………………………………………… ……………………………………………………………………………………… ……………………………………………………………………………………… ……………………… 8. What measures do you have in place to ensure the standard water quality is maintained? ……………………………………………………………………………………… ……………………………………………………………………………………… ……………………………………………………………………………………… ……………………………………………………………………………………… ………………………………

THANK YOU FOR YOUR TIME AND CO-OPERATION!

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Appendix V: Field Photos

18/12/2014

A. Sand harvesting in Migori River

18/12/2014

B. Forest in Migori

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19/12/2014

C. Gold Mining in Migori

19/12/2014

D. Open Shrubland

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Appendix VI: Research Authorization Letter

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