Studying the spatial non-stationary relationships of some physical parameters on the Earth's surface temperature using GWR in Upper Awash basin, Ethiopia

Abstract

Exploring the spatial non-stationary relationships between land surface temperature (LST) and their driving environmental factors is important for selecting appropriate strategies to mitigate and regulate the thermal environment of watersheds. To examine the influence of various biophysical factors on LST in the Upper Awash Basin (UAB) of Ethiopia, the study used two models: Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models. As a global model, the OLS model was initially used to capture the overall relationship between LST and some biophysical factors. And then the GWR, a local spatial modeling approach, was used to examine the spatial non-stationary relationships between LST and its influencing biophysical factors. Landsat 8 OLI/TIRS image and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) were used to generate the LST and its influencing biophysical factors. Biophysical parameters such as enhanced vegetation index (EVI), modified normalized difference water index (MNDWI), normalized difference built-up index (NDBI), normalized difference bareness index (NDBaI), albedo and elevation were used as potential driving environmental factors of LST. The result showed that the GWR model, with a higher coefficient of determination (R2) (GWR: 0.98; OLS: 0.52) and a smaller Akaike Information Criterion (AIC) (GWR: 12354; OLS: 65412), provides a better prediction than the traditional OLS model, reflecting the spatial non-stationarity relationships. The results also showed that increased LST was significantly affected by NDBI, NDBaI, and albedo, with NDBI having the greatest effect. Conversely, EVI, MNDVI, and DEM showed a negative correlation with LST, with EVI having the greatest impact. These findings highlighted the importance of considering the spatial non-stationarity relationships between LST and pertinent driving factors, and they also offer recommendations for mitigating measures to control the thermal environment of a river basin.