Urban land-use, land-cover classification through watershed segmentation in the V–I–S feature space

Abstract

This article introduces an innovative approach using marker-controlled watershed segmentation (WS) in the Vegetation–Impervious Surface–Soil (V–I–S) feature space for urban land-use and land-cover (LULC) classification. The complement (e.g., the inverse) of the V–I–S feature space image shows depressions, which can be treated as topographic watersheds and they correspond to LULC classes. WS partitions the complement of V–I–S feature space image into LULC regions based on user-specified initial markers. These regions are then labelled with specific LULC classes, which lead to the subsequent LULC classification. The results showed that WS can achieve substantial classification accuracy. Compared to the traditional maximum likelihood classifier (MLC), our method requires less user input while improving the classification accuracy. A sensitivity test of the WS-based method on the location of the initial markers also is provided.