Land surface temperature inversion based on Landsat 7 and GF-1 WFV images

doi:10.13474/j.cnki.11-2246.2021.352

Abstract

Abstract: Land surface temperature (LST) is the focus of geographical research and plays an important role in the earth-atmosphere system. However, the domestic high-resolution image lacks thermal infrared band, and the image resolution of thermal infrared band is relatively low. Based on this, a low resolution image downscaling method is proposed to retrieve high-resolution land surface temperature. Firstly, the surface temperature of typical objects is extracted from the thermal infrared band of Landsat 7 image. After preprocessing the GF-1 WFV image, least squares under the full constrained method is used to decompose the high-resolution image into mixed pixels. According to the average temperature model, the surface temperature of the high-resolution image is obtained. The root mean square error (RMSE) is 1.40℃, the mean absolute error (MAE) is 0.44℃, and the precision is verified with Landsat 7 image.

Key words: surface temperature, pixel decomposition, downscaling, GF-1 WFV

CLC Number:

P237

FU Baoling, JU Feng, ZHAO Weizhong, XU Xing. Land surface temperature inversion based on Landsat 7 and GF-1 WFV images[J]. Bulletin of Surveying and Mapping, 2021, 0(11): 124-127,135.

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