Abstract:
In this study, the
spatiotemporal dynamics of the urban
environment and thermal environment of
Benin City are analysed. The maximum
likelihood algorithm for land use and land
cover (LULC) analysis was used to
categorise Landsat images. The relative
transfer equation (RTE) and land surface
emissivity (LSE) approaches were used to
retrieve the land surface temperature (LST),
whereas the Cellular Automata-Markov
(CA-Markov) algorithm was used to forecast
the LULC for 2030. The findings reveal
evolving LULC patterns over time. Built-up
areas made up 19.66% of the total area in
1990, bare ground made up 9.25%, and
vegetation made up 71.08%. Built-up areas
reached 23.40% in 2000, bare land reached
12%, and the vegetation cover dropped to
64.16%. In 2010, there was an increase in
the proportion of built-up areas to 44.38%,
the proportion of bare land increased to
22.20%, and the proportion of vegetation
decreased to 33.42%. Built-up areas reached
61.79% in 2020, compared to 22.29% for
bare land and 61.79% for vegetation.
Regarding the relationship between the
fractional vegetation cover (FVC) and LST,
for the years 1992, 2002, 2012, and 2022, R2
is equal to 0.87097, 0.84598, 0.83957, and
0.71838, respectively. Conversely, for the
LST and the normalised difference built-up
index (NDBI), the R2 values were 0.5975,
0.73876, 0.86615, and 0.90368 for 1992,
2002, 2012, and 2022 respectively. In
conclusion, this study evaluates Benin City's
metropolitan setting and thermal
environment. According to the LULC study, there are more built-up areas and less
vegetation. The impact of the changing land
cover on urban thermal features is shown
through correlation analysis, which links
more built-up regions to higher LSTs. These
results can support urban design efforts to
lessen the effects of climate change.
Examining the distribution of the LST and
its associations with particular land cover
types was the major goal of this study.
Future research will undoubtedly use this
study as a useful reference when modelling
urban terrain and temperature variations.
