Combining Spectral Water Indices and Mathematical Morphology to Evaluate Surface Water Extraction in Taiwan

Abstract

Rivers in Taiwan are characterised by steep slopes and high sediment concentrations. Moreover, with global climate change, the dynamics of channel meandering have become complicated and frequent. The primary task of river governance and disaster prevention is to analyse river changes. Spectral water indices are mostly used for surface water estimation, which separates the water from the background based on a threshold value, but it can be challenging in the case of environmental noise. Edge detection uses a canny edge detector and mathematical morphology for extracting geometrical features from the image and effective edge detection. This study combined spectral water indices and mathematical morphology to capture water bodies based on downloaded remote sensing images. From the findings, this study summarised the applicability of various spectral water body indices to the surface water extraction of different river channel patterns in Taiwan. The normalised difference water index and the modified normalised difference water index are suitable for braided rivers, whereas the automated water extraction index is ideal for meandering rivers.