The threshold determination methods of water body information extraction using GF-1 satellite image

International Conference on Manufacturing Technology, Materials and Chemical Engineering

材料科学;化学工业

Ji, R.P.^1^2 ; Yu, W.Y.^1^2 ; Feng, R.^1^2 ; Wu, J.W.^1^2 ; Zhang, Y.S.^1^2

Institute of Atmospheric Environment, China Meteorological Administration, Shenyang

110166, China^1

Key Laboratory of Agrometeorological Disasters, Liaoning Province, Shenyang

110166, China^2

关键词: Earth observation systems;    High spatial resolution;    High temporal resolution;    Normalized difference vegetation index;    Normalized differences;    Overall accuracies;    Threshold determination;    Water body information extractions;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/592/1/012088/pdf
DOI  :  10.1088/1757-899X/592/1/012088

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

The GF-1 satellite is the first satellite of China High-resolution Earth Observation System (referred to short as CHEOS) with the advantages of high spatial resolution, high temporal resolution and 4 multi-spectral channels, which can quickly extract inland water body information. At present, the methods of water body information extraction by remote sensing mainly include single-band threshold method, spectral relation method, normalized difference vegetation index (NDVI) method, normalized difference water body index (NDWI) method and shade water body index (SWI) method. The results of water body information extraction will vary with different methods; especially, the thresholds determination of each method is an important factor in the accuracy of water body information extraction. In this paper, the water body information of Qinghai Lake, Hongze Lake, and Hulun Lake were extracted by NDWI index, and the optimal thresholds of water body information extraction were determined by using Jeffries-Matusita (J-M) distance method and density slice method was in the range of -0.061∼0.093. Finally, the accuracy of the extraction results was analyzed, and the overall accuracy is more than 88%.