Mapping of spatiotemporal changes across the East African Rift System to identify geothermal anomalies using MODIS land surface temperatures

Abstract

A range of satellite datasets, including MODIS land surface temperature (LST), areused to identify geothermal anomalies associated with rift basins across the East AfricanRift System. Monthly and yearly absolute LST means are generated from January 2003to December 2013 and show regions of warmer LSTs in relevant basins. However,without auxiliary data it is not possible to show that these are related to geothermalanomalies. Two approaches are applied to delineate the LST more clearly - principalcomponent analysis (PCA) and normalisation of the LST with respect to elevation. Thefirst technique uses PCA to delineate the known physical parameters influencing LSTand reveals elevation to be dominant. Consequently, steps have been taken to minimisethe effects on LST. This has been achieved via normalisation, whereby absolute LST isrecalculated, using linear regression analysis, to equivalent normalised LST at anelevation of 0 m. Several previously masked areas, including the Ethiopian Dome, havesince been revealed as warmer and with an increased likelihood of relationship togeothermal heat flux since they correspond to emissivity and tectonic patterns. Note theimpressive manner in which volcanoes including Mount Elgon, cold in absolute LSTbecause of elevation, are also identified as warmer post normalisation. Caution muststill be exercised with respect to the warm anomalies in normalised LST, as these canstill not be conclusively confirmed as geothermal anomalies. A restricted PCA of thenormalised LST shows that these are still sensitive to emissivity as expected butparticularly in a well-defined region around Lake Turkana. In conclusion, the likelihoodof identifying a geothermal anomaly is best associated with the normalised LST andwhere high frequency spatial structure is observed. Identified regions should be checkedagainst the restricted PCA. Future work should incorporate the use of other indicators ofgeothermal activity or heat flux to better identify the LST variance that corresponds togeothermal anomalies.