MODIS-based spatiotemporal variability assessment of urban Land Surface Temperature in Burkina Faso

Abstract

Abstract

Urbanization modifies the thermal properties of the surface, and has become a major driver of Land surface temperature (LST) in Sub-Saharan countries. Even though LST is an important variable in climatic modelling, it is not recorded by ground observation stations in Burkina Faso. This research aimed at investigating the spatiotemporal variability of LST in Ouagadougou and Bobo-Dioulasso from 2003 to 2021, using remote sensing technics. Moderate Resolution Imaging Spectroradiometer (MODIS) daily LST product and ERA 5 Land air temperature datasets were used in Google Earth Engine platform. A gap-filling method, based on LST and 2-meters above ground air temperature relationship was applied to get continuous daily LST datasets. The Mann-Kendall trend test was performed on the seasonal and yearly mean datasets to assess the trend. The results revealed an increasing trend in yearly LST in both cities. The computation of the climatological seasonal trend showed that the global trend of LST is driven by that of March-April-May season, which presented a significant increase (p=0.009) in Ouagadougou and a non-significant increase (p=0.08) in Bobo-Dioulasso. The mean LST increase for this season during the study period was 0.05°C and 0.03°C per year, respectively in Ouagadougou and Bobo-Dioulasso. These findings provide a scientific reference to urban planners for sustainable cities planning, in the era of climate change, by mainstreaming UHI mitigation.