Local uncertainty maps for land-use/land-cover classification without remote sensing and modeling work using a class-conditional conformal approach

Abstract

Land use/land cover (LULC) is one of the most impactful global change phenomenon. As a result, considerable effort has been devoted to creating large-scale LULC products from remote sensing data, enabling the scientific community to use these products for a wide range of downstream applications. Unfortunately, uncertainty associated with these products is seldom quantified because most approaches are too computationally intensive. Furthermore, uncertainty maps developed for large regions might fail to perform adequately at the spatial scale in which they will be used and might need to be customized to suit the specific applications of end-users.