Open AccessWetland Monitoring and Land Surface Temperature Response in Panjin City Based on Tiangong-2 Data
Author(s) -
Xing Jin,
Bai Qinling,
Dan Meng
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/780/3/032055
Subject(s) - wetland , swamp , environmental science , remote sensing , hydrology (agriculture) , paddy field , correlation coefficient , thermal infrared , imaging spectrometer , spectrometer , geology , infrared , geography , ecology , statistics , physics , geotechnical engineering , mathematics , archaeology , optics , biology , quantum mechanics
In the research area Panjin city, visible and near-infrared remote sensing images by Tiangong-2 wide-band imaging spectrometer was used to extracte wetland. According to the established remote sensing interpretation signs, the wetland types of Panjin city in 2018 are extracted by using the method of partition classification. The thermal infrared imaging spectrometer of Tiangong-2 was used to invert the land surface temperature based on the split-window algorithm. This paper comprehensively analyzed the distribution of wetland cover types of Panjin city in 2018 and their impact on land surface temperature. The results show that in 2018, Panjin wetland covers an area of 3,184.89 km 2 and the major type of wetland is artificial wetland. The area is reduced successively according to paddy field, reed swamp, mudflat wetland, suaeda salsa swamp, aquaculture farm, reservoir/pond and river wetland. The overall accuracy of partition classification method is 89.97%, kappa coefficient is 0.8761. The applicability of Tiangong-2 wide-band imaging spectrometer in wetland monitoring is verified. The split-window algorithm can be used to effectively invert the land surface temperature of Tiangong-2 data, and the land surface temperature results obtained by inversion are in good consistency with those obtained by MODIS inversion, the correlation coefficient reached 0.79. Through counting, the land surface temperature of different wetland types is different, among which the land surface temperature of mudflat wetland is the highest and that of reservoir is the lowest.