%0 Thesis %A Holmes, Sadie E. %D 2019 %T Mapping of spatiotemporal changes across the East African Rift System to identify geothermal anomalies using MODIS land surface temperatures %U https://figshare.le.ac.uk/articles/thesis/Mapping_of_spatiotemporal_changes_across_the_East_African_Rift_System_to_identify_geothermal_anomalies_using_MODIS_land_surface_temperatures/10298225 %R 10.25392/leicester.data.10298225.v1 %2 https://figshare.le.ac.uk/ndownloader/files/18715406 %K Thesis %X
A range of satellite datasets, including MODIS land surface temperature (LST), are
used to identify geothermal anomalies associated with rift basins across the East African
Rift System. Monthly and yearly absolute LST means are generated from January 2003
to 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 geothermal
anomalies. Two approaches are applied to delineate the LST more clearly - principal
component analysis (PCA) and normalisation of the LST with respect to elevation. The
first technique uses PCA to delineate the known physical parameters influencing LST
and reveals elevation to be dominant. Consequently, steps have been taken to minimise
the effects on LST. This has been achieved via normalisation, whereby absolute LST is
recalculated, using linear regression analysis, to equivalent normalised LST at an
elevation of 0 m. Several previously masked areas, including the Ethiopian Dome, have
since been revealed as warmer and with an increased likelihood of relationship to
geothermal heat flux since they correspond to emissivity and tectonic patterns. Note the
impressive manner in which volcanoes including Mount Elgon, cold in absolute LST
because of elevation, are also identified as warmer post normalisation. Caution must
still be exercised with respect to the warm anomalies in normalised LST, as these can
still not be conclusively confirmed as geothermal anomalies. A restricted PCA of the
normalised LST shows that these are still sensitive to emissivity as expected but
particularly in a well-defined region around Lake Turkana. In conclusion, the likelihood
of identifying a geothermal anomaly is best associated with the normalised LST and
where high frequency spatial structure is observed. Identified regions should be checked
against the restricted PCA. Future work should incorporate the use of other indicators of
geothermal activity or heat flux to better identify the LST variance that corresponds to
geothermal anomalies.
%I University of Leicester