Land-use allocation/Description: Difference between revisions

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Land-use change is determined by various factors, such as climate and climate variability, soil and terrain characteristics, and socio-economic variables, such as population density and accessibility ([[O'Neill, 2013]]). Land-use change dynamics differ substantially between regions ([[Lambin et al., 2000]]). These characteristics are taken into account in IMAGE 3.0 in a regional suitability assessment based on an empirical multiple linear regression analysis.
Land-use change is determined by various factors, such as climate and climate variability, soil and terrain characteristics, and socio-economic variables, such as population density and accessibility ([[O'Neill, 2013]]). Land-use change dynamics differ substantially between regions ([[Lambin et al., 2000]]). These characteristics are taken into account in IMAGE 3.0 in a regional suitability assessment based on an empirical multiple linear regression analysis.
The suitability assessment includes data on two biophysical determinants: the potential yield which covers effects of climate and soil ([[Crop and grass]]), and [[Slope - grid|the terrain slope index]] based on {{TempAcronymTemplate|AEEI}} SRTM elevation data (Shuttle Radar Topography Mission) from NASA. Two socio-economic determinants are included: population density ([[Klein Goldewijk et al., 2010]]), and the accessibility index from JRC ([[Nelson, 2008]]), which is defined as minutes travel time to major cities (>50,000 inhabitants).  
The suitability assessment includes data on two biophysical determinants: the potential yield which covers effects of climate and soil ([[Crop and grass]]), and [[Slope - grid|the terrain slope index]] based on {{TempAcronymTemplate|SRTM}} elevation data (Shuttle Radar Topography Mission) from NASA. Two socio-economic determinants are included: population density ([[Klein Goldewijk et al., 2010]]), and the accessibility index from JRC ([[Nelson, 2008]]), which is defined as minutes travel time to major cities (>50,000 inhabitants).  


These four independent variables are used in multiple linear regression analysis to investigate the relationship between these land-use determinants and current land use (fractions of crop and grassland in 2005 from [[Klein Goldewijk et al., 2011]]). The analysis is performed separately for each IMAGE region, and takes into account the logarithmic relationship found for all independent variables except for potential crop yield.
These four independent variables are used in multiple linear regression analysis to investigate the relationship between these land-use determinants and current land use (fractions of crop and grassland in 2005 from [[Klein Goldewijk et al., 2011]]). The analysis is performed separately for each IMAGE region, and takes into account the logarithmic relationship found for all independent variables except for potential crop yield.

Revision as of 14:55, 5 May 2014