Land Surface Temperature Investigation Around Ikogosi Warm Spring Nigeria Using Landsat8 Data

Abstract

Ikogosi warm spring (IWS) is among the most visited geothermal resource by tourists in Nigeria. On that basis, it has attracted so much attention from researchers using various geophysical methods, except the retrieval of the land surface temperature (LST) from remote sensing data. This work aimed at computing LST to delineate hot zone around Ikogosi geothermal resources. The split-window approach was used to compute the LST from Landsat 8 data. The interpretation of Landsat8 data revealed that the central region of the study area is of high LST, and the temperature then drops towards the southwest direction. The result also shows that the warm spring is situated around a region with high land surface temperature (about 29 °C) which is an indication of a geothermal reservoir. The supervised classification of the LST yields two zones of the high density of pixels with high temperature, hot spot zones. The hot spot zone west of IWS is believed to be the heat source of IWS as it has high LST, and it is closer to IWS while the hot spot zone NW of IWS shows an indication of a viable geothermal resource, high LST

Geothermal energy potentiality modeling using GIS-based machine learning algorithm concept in Southwestern Nigeria: insights from geophysical and remote sensing data sets

“…The (i) land use land cover, (ii) slope, (iii) land surface temperature, (iv) surface albedo, (v) lineament density, and (vi) normalized differential vegetation index was generated. Applying Equations (1-4) are the existing equations researchers have adopted (Putri et al, 2021;Bello et al, 2021) in processing various factors identi ed as possible indicators of geothermal potential. The normalized differential vegetation index (NDVI) was processed and analyzed to produce thematic themes.…”