Retrieval of Land Surface Temperature by Utility of the Remote Sensing Techniques from Landsat-9 TIRS-2 Data, A Case Study of the Tigris River in Wasit - Iraq.

Abstract

This research proposes the Split-Window0 (SW) and Mono-Window0 (MW) algorithms for obtaining Land Surface Temperature (LST) from Landsat-09 TIRS-02 data. Given this, there are several chances to research land dynamics using remote sensing techniques thanks to LANDSAT data. Compared to other conventional ways, this one is not only less time-consuming but also far more efficient. It also costs less. The present Tigris River study was carried out in the Wasit region of Iraq, where we measured the LST difference over a  section of the Tigris River in 2024 for both the winter and spring seasons. The land surface emissivity (LSE) determination was carried out with the help of the NDVI threshold value. The spatial distribution of LST for winter using an MW was ( ), RMSE of ( ), and the Bias of ( ), while for spring, it was ( ), RMSE0 of ( ), and the Bias of ( ). The spatial distribution0 of LST using a SW in winter was ( ), RMSE of ( ), and the Bias ( ), and in spring, it was ( ), RMSE of ( ), and the Bias of ( ). The regression study between SW and MW algorithms for LST retrieval shows an R² value of 0.844 in winter and an R² value of 0.9819 in spring. The results were validated by juxtaposing0 them with LST measurements taken at the twelve research sites during the satellite picture acquisition for both seasons. In conclusion, the proposed split window algorithm gave very similar results with little difference from the in situ recorded results and is predictable to be an authoritative method for retrieval LST0 from Landsat-9 TIRS-02data.