This paper presents the potential of integrating socioeconomic data into GIS that helps to explain spatial differentiation of resources availability, utility potential, market orientation and socioeconomic condition in an area. Socioeconomic data were gathered through the family survey and linked them to GIS by using house position, and continuous thematic raster layers were produced by interpolation. Biophysical conditions were assessed using RS/GIS techniques. Regression analysis was used to assess association between socioeconomic and biophysical condition by taking farm income as dependent variable and cost distance to market and land quality parameters as independent variable. Multivariate linear regression showed that cost distance to market and land quality parameter extracted from RS/GIS explain the income potential of a farm in a given location. Future strategies of reducing cost distance to the market through road improvement and increasing the quality of land through soil and water management activities and their impact on income were tested and presented.
Key words: Geographic information systems, remote sensing, socioeconomic data integration, spatial differentiation, farm income modeling, Nepal.
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