Author(s)

Elhadi K. Mustafa¹, Guoxiang Liu¹, Abubakr Hassan¹, Mohamed A. Damos¹, Musa Tarawally²

¹Department of Surveying and Geo-Informatics, Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China.
²School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, China.

Global warming has attracted much concern about the worldwide organization, civil society groups, researchers, and so forth because the worldwide surface temperature has been expanding. This investigation intends to assess and compare the ability of a combination of land cover indices to predict the future distribution of land surface temperatures in Freetown using the Polynomial model analysis. Landsat satellite images of 1988, 1998, 2000, 2010, and 2018 of the Freetown Metropolitan zone were utilized for analysis. The investigation had adopted two land covers indices, Modification of normalized difference water index and Urban Index (UI) (e.g., MNDWI and UI) and applied a multi regression equation for forecasting the future LST. The stimulation results propose that the development will be accompanied by surface temperature increases, especially in Freetown’s western urban area. The temperature prevailing in the west of the metropolitan area may increase in the city somewhere in the range from 1988 to 2018. Additionally, the results of the LST prediction show that the model is perfect. Our discoveries can be represented as a helpful device for policymakers and community awareness by giving a scientific basis for sustainable urban planning and management.

Global Warming, Land Surface Temperature, Polynomial Curve Fitting, Land Cover Indices

Mustafa, E. , Liu, G. , Hassan, A. , Damos, M. and Tarawally, M. (2020) Predicting of Land Surface Temperature Distribution in Freetown City, Sierra Leone by Using Polynomial Curve Fitting Model. Journal of Geographic Information System, 12, 531-544. doi: 10.4236/jgis.2020.125031.