Global land use data for integrated assessment modeling

Abstract

Changes in land use and land cover have been one of the major drivers of global change over the last three centuries. Detailed spatially-explicit data sets characterizing these historical land cover changes are now emerging. By synthesizing remotely-sensed land cover classification data sets with historical land use census data, our research group has developed comprehensive databases of historical land use and land cover change. Moreover, we are building estimates of the land suitability for agriculture to predict the constraints on future land use. In this project, we have interacted with the Global Trade and Analysis Project (GTAP) at Purdue University, to adapt our land use data for use with the GTAP database, a baseline database widely used by the integrated assessment modeling community. Moreover, we have developed an interactive website for providing these newly emerging land use data products for the integrated assessment (IA) community and to the climate modeling community.