Sub-pixel-scale Land Cover Map Updating by Integrating Change Detection and Sub-Pixel Mapping

Abstract

Coarse-resolution remotely sensed images are high in temporal repetition rates, but their low spatial resolution limits their application in updating land cover maps. Our proposed land cover updating method involves the use of coarse-reso-lution images to update fine-resolution land cover maps. The method comprises change detection and sub-pixel mapping methods. The current coarse-resolution image is unmixed, and the previous fine-resolution map is spatially degraded to produce current and previous class fraction images. A change detection method is applied to these fraction images to create a fine-resolution binary change/non-change map. Finally, a sub-pixel mapping method is applied to update the fine-resolution pixel labels that are changed in the change/ non-change map. The proposed method is compared with a pixel-based classification method and two sub-pixel mapping methods. The proposed method maintains most of the spatial patterns of land cover classes that are unchanged in the previous and current images, whereas other methods cannot