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| | 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}} SRTMelevation 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. | ||
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Currently, IMAGE is not using the endogenous intensification calculated by CLUMondo ([[Van Asselen and Verburg, 2013]]) because it is not necessarily consistent and is mostly lower than the intensification calculated by the agro-economic model ([[Agricultural economy and forestry]]). At a later stage, intensification in IMAGE and CLUMondo could be made consistent via iterations or closer linkages. For similar reasons, grassland dynamics are not taken from CLUMondo but from the [[Livestock|IMAGE livestock]] and [[Agricultural economy and forestry|agro-economic models]]. | Currently, IMAGE is not using the endogenous intensification calculated by CLUMondo ([[Van Asselen and Verburg, 2013]]) because it is not necessarily consistent and is mostly lower than the intensification calculated by the agro-economic model ([[Agricultural economy and forestry]]). At a later stage, intensification in IMAGE and CLUMondo could be made consistent via iterations or closer linkages. For similar reasons, grassland dynamics are not taken from CLUMondo but from the [[Livestock|IMAGE livestock]] and [[Agricultural economy and forestry|agro-economic models]]. | ||
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Revision as of 14:35, 5 May 2014
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