Comparison of land surface temperature retrieval algorithm based on the Landsat8 OLI/TIRS data
[Purpose]This study aims to evaluate the performance differences of different inversion algorithms in satellite remote sensing land surface temperature(LST)data acquisition,especially for the Hohhot area at a specific time.[Method]Based on Landsat-8 OLI/TIRS data,three different inversion algorithms(mono-window algorithm by Qin Zhihao,Offer Ronzenstein split-window algorithm,and Jiménez-Muñoz split-window algorithm)were selected to invert the surface temperature in the Hohhot region.Subsequently,accuracy tests and sensitivity analysis were conducted on the inversion results to evaluate the performance of different algorithms under the same conditions.[Result]After comparative analysis,the mono-window algorithm by Qin Zhihao demonstrated the highest accuracy in surface temperature inversion in the Hohhot region,with an average relative error of 3.68%.In contrast,the average relative errors of the Offer Ronzenstein split-window algorithm and the Jiménez-Muñoz split-window algorithm were 4.22%and 6.60%,respectively.In terms of sensitivity analysis,the Jimenez-Munoz split-window algorithm was the least sensitive to changes in water vapor content,followed by the Offer Ronzenstein split-window algorithm,while the mono-window algorithm by Qin Zhihao showed higher sensitivity and was only applicable to a specific range of water vapor content.[Conclusion]The mono-window algorithm by Qin Zhihao is the preferred algorithm for surface temperature inversion in the Hohhot area due to its high accuracy.However,the differences in sensitivity and applicability of different algorithms indicate that in practical applications,it is necessary to select appropriate inversion algorithms according to specific data characteristics and regional conditions.In addition,further research can explore more algorithms to improve the accuracy and generalizability of surface temperature inversion.
land surface temperatureLandsat-8mono-window algorithm by Qin Zhihaosplit-window algorithmHohhot