Spatiotemporal variability of land surface temperature in north-western Ethiopia

Abstract

The aggravating deforestation, industrialization, and urbanization are becoming the principal causes for environmental challenges worldwide. As a result, satellite-based remote sensing helps to explore the environmental challenges spatially and temporally. This investigation analyzed the spatiotemporal variability in land surface temperature (LST) and its link with elevation in the Amhara region, Ethiopia. The Moderate Resolution Imaging Spectroradiometer (MODIS) LST data (2001-2020) were used. The pixel-based linear regression model was used to explore the spatiotemporal variability of LST changes. Furthermore, Sen's slope and Mann-Kendall trend test were used to determine the magnitude of temporal shifts of the areal average LST and evaluate trends in areal average LST, respectively. Coefficient of variation (CV) was also used to analyze spatial and temporal variability in seasonal and annual LST. The seasonal LST CV varied from 1.096-10.72%, 0.7-11.06%, 1.29-14.76%, and 2.19-10.35% for average autumn (September to November), summer (June to August), spring (March to May), and winter (December to February) seasons, respectively. The highest inter-annual variability was observed in the eastern, northern, and south-western districts than that in the other parts. The seasonal spatial LST trend varied from -0.7-0.16, -0.4-0.224, 0.6-0.19, and -0.6-0.32 for average autumn, summer, spring, and winter seasons, respectively. Besides, the annual spatial LST slope varied from -0.58 to 0.17. Negative slopes were found in the central, mid-western, and mid-northern districts in annual LST, unlike the other parts. The annual variations of mean areal LST decreased insignificantly at the rate of 0.046°C year^-1 (P<0.05). However, the inter-annual variability trend of annual LST increased significantly. Generally, the LST is tremendously variable in space and time and negatively correlated with elevation.

Keywords: Elevation. LST; MODIS; Mann-Kendall trend test; Sen’s slope.