Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Spatiotemporal Assessment of Remotely Sensed LST Variability in Afghanistan during 2000-2021

Version 1 : Received: 29 May 2022 / Approved: 30 May 2022 / Online: 30 May 2022 (08:45:01 CEST)

A peer-reviewed article of this Preprint also exists.

Nabizada, A.F.; Rousta, I.; Dalvi, M.; Olafsson, H.; Siedliska, A.; Baranowski, P.; Krzyszczak, J. Spatial and Temporal Assessment of Remotely Sensed Land Surface Temperature Variability in Afghanistan during 2000–2021. Climate 2022, 10, 111. Nabizada, A.F.; Rousta, I.; Dalvi, M.; Olafsson, H.; Siedliska, A.; Baranowski, P.; Krzyszczak, J. Spatial and Temporal Assessment of Remotely Sensed Land Surface Temperature Variability in Afghanistan during 2000–2021. Climate 2022, 10, 111.

Abstract

To investigate the dynamics of land surface temperature (LST) in Afghanistan in the period 2000-2021 and to assess the impact of such factors as soil moisture, precipitation, and vegetation coverage on it, remotely sensed soil moisture data from Land Data Assimilation System (FLDAS), precipitation data from Climate Hazards Group Infra-Red Precipitation with Station (CHIRPS), and NDVI and LST from Moderate Resolution Imaging Spectroradiometer (MODIS) were downloaded and correlations between them were analyzed using the regression method. The result shows that the LST in Afghanistan has a slightly decreasing, but insignificant trend during the study period (R=0.2, p-value=0.25), while vegetation coverage, precipitation, and soil moisture had an increasing trend. It was revealed that soil moisture has the highest impact on LST (R=0.7, p-value=0.0007), and the soil moisture, precipitation, and vegetation coverage explain almost 80% of spring (R2=0.73) and summer (R2=0.76) LST variability in Afghanistan. The LST variability analysis done separately for Afghanistan’s rivers subbasins shows that the LST of the Amu Darya subbasin had an upward trend in the study period, while for the Kabul subbasin the trend was downward.

Keywords

Land Surface Temperature; LST; Afghanistan; remote sensing; FLDAS; CHIRPS; MODIS; multiple regression; anomaly analysis

Subject

Environmental and Earth Sciences, Environmental Science

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