Mapping of small water bodies with integrated spatial information for time series images of optical remote sensing

Abstract

Small water bodies and their temporal changes are, especially in urban areas, closely related to the urban climate, people’s daily life, among others. Mapping of small water bodies with optical remote sensing images in complex urban landscapes is challenging: that is to establish a balance between reducing incorrect water detection and increasing the integrity of water extraction. In this work we propose a spatial information-integrated small water bodies mapping (SWM) method to achieve a complete and accurate extraction and temporal change monitoring of small water bodies. The spatial contextual information is exploited by the proposed water index roughness feature to compensate for the indistinguishability of small water bodies in spectral information. Results using Landsat and Sentinel-2 data show that the proposed algorithm achieves better water extraction performance, i.e. higher completeness and less incorrect extractions. It proves the ability to observe the changes of surface water.