Abstract

This study aimed at using remote sensing methodology to assess the daytime surface urban heat island (SUHI) in Lagos metropolis. Several studies have examined the SUHI, using point data from meteorological stations. However, it has been shown in the literature recently that it is practically impossible to accurately value the intensity of SUHI from ground meteorological measurement due to heterogeneity and complexity of surface temperature over land. Therefore a time series of Landsat data, from 1984 to 2012, were used in the present study to assess spatial and temporal variability in the contribution of source and sink landscape to daytime SUHI in Lagos. This study uses remote sensing methods because Lagos has a strong heterogeneity of land surface characteristics; with several drainage, vegetation, built-up and soil between the coast and mainland, thus the land surface temperature (LST) changes rapidly in space and time. The results from this study show differences in the contribution of source and sink landscape to SUHI. The main findings from the results show that source landscape contributes positively to the intensity of SUHI in Lagos metropolis. The results show a general increase in mean LST during the periods of study from 1984 to 2012. The north-west (NW) zone of Lagos has highest LST compared to other zones. In 1984, the mean LST of NW zone was 300.53 K, but increased to 301.85 K in 2000 and 302.85 K in 2012. Although contributions from the landscapes differ by zones and time, much more intensified LST was noted in the NW zone of the city. The study find out that change in landcover has been the most important driver of intensified SUHI in Lagos metropolis. NW zone recorded the highest increased in built-up area throughout the years: 320.32 km2 in 1984, 535.28 km2 in 2000 and 630.70 km2 in 2012. This study demonstrates therefore that it is possible to assess spatial distribution and long-term temporal evolution of the LST in urban area, using remote sensing data. Also the results shows that remote sensing methods offer possibility for measuring LST over complete spatially averaged rather than point values. The results from this study further our understanding that not only the SUHI is frequent to cities in developed countries, but the effects are also obvious in several urban settlements in tropical countries.

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