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DC Field | Value | Language |
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dc.contributor.author | Graw, Valerie | - |
dc.contributor.author | Smale, Melinda | - |
dc.contributor.author | Menz, Gunter | - |
dc.date.issued | 2016 | - |
dc.date.accessioned | 2021-03-30T09:54:52Z | - |
dc.date.available | 2021-03-30T09:54:52Z | - |
dc.identifier.uri | http://41.89.96.81:8080/xmlui/handle/123456789/2365 | - |
dc.description.abstract | Abstract Worldwide, most poor people live in rural areas and depend directly on agricultural land for most of their food, making them vulnerable to environmental changes such as land degradation. This study provides insights into land-population dynamics by focusing on the interlinkages between biophysical and socio-economic perspectives rather than either perspective taken alone. We analyze the interlinkages among socio-economic variables including land tenure and poverty, biophysical preconditions and trends in land productivity among 41 villages in western Kenya. We apply an interdisciplinary framework, combining and modeling panel survey data collected from households in western Kenya with biophysical data and vegetation trends based on remote sensing imagery. Data span the same time period and are linked in a Geographical Information System (GIS). We find that poverty, as well as trigger events such as the global food price crisis of 2008 and post-election crisis of 2007/8, are strongly related to land productivity. Linkages could not be validated between land productivity and land ownership as such, reflecting the fact that the change in ownership of land over the time period studied was not significant in the area of study. Yet links could be observed between productivity change and land fragmentation. Within a coupled humanenvironment system single indicators might have major impact but in combination with others could also trigger processes such as more intense land degradation. Therefore, using Ordinary Least Squares Regression (OLS) a set of indicators, including socio-economic and biophysical variables, could be defined which explained around 80% of the variation in significantly decreasing productivity trends. Key Words: GIS, poverty, land tenure, land degradation | en_US |
dc.description.sponsorship | Fiat Panis Foundation | en_US |
dc.language.iso | en | en_US |
dc.publisher | Tegemeo Institute | en_US |
dc.subject | Land Degradation, Tenure, and Poverty -- Geospatial Analysis -- Socio-ecological Systems | en_US |
dc.title | Land Degradation, Tenure, and Poverty: A Geospatial Analysis of Socio-ecological Systems in Western Kenya | en_US |
dc.title.alternative | Working Paper 61 | en_US |
dc.type | Working Paper | en_US |
Appears in Collections: | Tegemeo Institute |
Files in This Item:
File | Description | Size | Format | |
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Land Degradation, Tenure, and Poverty A Geospatial Analysis of Socio-ecological Systems in Western Kenya.pdf | 1.2 MB | Adobe PDF | View/Open |
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