High-precise water extraction based on spectral-spatial coupled remote sensing information

Remote sensing information extraction is the key step of remote sensing application, and the automatic and high-precise extraction of water information from remotely sensed images is of great significance and urgently required in many research fields. This paper presents a step-by-step iterative transformation mechanism to extract water information, which uses spatial scale transformation mechanism of “whole-local” based on water index fitted from spectral library using spectral angle method first, and then fuses the hierarchical knowledge of water extraction and achieves the gradually approach of the water body´s optimal margin iteratively by combining the segmentation and classification at whole and local scales respectively. Experiment of plateau lake information extraction demonstrates its better accuracy and efficiency.