The content of this article is from the 7th issue of Surveying and Mapping Bulletin in 2023, review number: GS Jing (2023) No. 1340
Optimization of surface temperature inversion algorithm for Landsat 9 data
WEN Ya-fei1,2, LIU Yu2, WANG Guang-hui2, ZHANG Qiu-zhao1
1. School of Environment and Geomatics, China University of Mining and Technology, Xuzhou 221116, China; 2. Land Satellite Remote Sensing Application Center, Ministry of Natural Resources, Beijing 100048, China
Keywords: surface temperature, Landsat 9, single window algorithm, split window algorithm, thermal infrared remote sensing
Citation format:Wen Yafei, Liu Yu, Wang Guanghui, et al. Optimization of land surface temperature inversion algorithm for Landsat 9 data[J]. Bulletin of Surveying and Mapping, 2023(7): 74-79.doi: 10.13474/j.cnki.11-2246.2023.0204
Abstract: Surface temperature is widely used in many fields as a key parameter for energy exchange between the surface and the atmosphere. In this paper, the single-window algorithm model and the split-window algorithm model are optimized for the Landsat 9 data, and the surface temperature inversion is realized, and the accuracy verification and analysis is carried out by combining the measured data of the SURFRAD site and the surface temperature products. The results show that the determination coefficients of the two algorithm models are greater than 0.96, among which the accuracy of the splitting algorithm model is high, the error (RMSE) value is about 1.45 K, and the accuracy of the single-window algorithm model is low, and the error (RMSE) value is about 1.61 K. Compared with the single-window algorithm, the splitting algorithm model has lower sensitivity to parameters, and the results of the splitting algorithm model are better than the results of the single-window algorithm model in the range of high water vapor content. The results of the land surface temperature inversion method proposed in this paper and the error (RMSE) value of the official surface temperature product are within 2.5 K, which can meet the application requirements of thermal infrared remote sensing data to produce surface temperature products.
About author:Wen Yafei (1993-), male, master's degree, the main research direction is thermal infrared surface temperature inversion theory and application. E-mail:[email protected] correspondence: Liu Yu. E-mail:[email protected]
Preliminary Review: Yang Ruifang Review: Song Qifan
Final judge: Jin Jun
information