Study on Information Extraction of Water Bodyin Plain RiverNetwork Area Based on Multi-temporalGF-1 Image - LIAO Yubing; ZHOU Feng (Renmin Zhujiang)
High-accuracy extraction of water body information is the base of and the key to the study of the regional water resources utilization. In order to solve the mixture of pixels such as the towns, shadow and bare earth in the extraction of remote sensing information of water body in Plain River Network Area, based onmulti-temporal GF-1 image, this paper proposes a decision tree model combining the Normalized Differential Vegetation Index (NDVI), Normalized Differential Water Index (NDWI), and near-infrared albedo for water body information extraction, and conducts a study taking the typical plain atthe lower reaches of Yangtze and Huai River.The results show that compared with other methods including single-band threshold and Shadow Water Index (SWI), the multi-temporalspectral information in newly proposed method can effectively eliminate the mixture of pixels such as the towns, shadow and the bare earth, improve the extraction accuracy of smaller water bodies with an overall accuracy of 93% and a Kappa coefficient of 0.85,and reasonably show a spatial distribution of water surface rate with a declining trend from West to East, which could provide a reference for the information extraction of water body in other plains as well.