Determination of urban land-cover types and their implication on thermal characteristics in three South African coastal metropolitans using remotely sensed data. Issue 1 (2nd January 2017)

• Record Type: Journal Article
• Authors: Odindi, John; Mutanga, Onisimo; Abdel-Rahman, Elfatih M.; Adam, Elhadi; Bangamwabo, Victor
• Is Part Of: South African geographical journal. Volume 99:Issue 1(2017)
• Page Start: 52
• Page End: 67
• Publication Date: 2017-01-02
• Subjects: Coastal metropolitans -- remote sensing -- land use–land cover -- vulnerability -- climate change; Geography -- Periodicals; South Africa -- Geography -- Periodicals; 916
• DOI: 10.1080/03736245.2015.1117015
• Languages: English
• ISSNs: 0373-6245

Abstract

Abstract: Coastal landscapes have historically attracted a larger number of settlements than inland. This trend is expected to continue. Commonly, increase in coastal settlements has been accompanied by growth of existing urban areas. Such growth is characterized by transformation from natural landscapes to impervious surfaces associated with thermal elevation. This results in urban micro and macro climate alteration and increased vulnerability to climate change and associated impacts. This study sought to determine the role of existing land-use-land-cover (LULC) mosaics on thermal variability between three South African coastal metros using remotely sensed Moderate Resolution Imaging Spectroradiometer (MODIS) data-set. Duncans post hoc one-way analysis of variance, multispectral Landsat 8 scenes and Terra MODIS were used to determine differences between the major LULC mosaics and their respective surface thermal values. Based on each of the metropolitan's LULC proportions and their respective thermal values from MODIS imagery, the Contribution Index was used to determine the source/sink contributions within each metropolitan area. The eThekwini metropolitan area, due to its dominant impervious surfaces proportion, was more vulnerable to elevated urban heat and therefore higher relative vulnerability to climate change and associated impacts than the Buffalo City and Nelson Mandela Bay metropolitans. Results in this study show the value of remotely sensed data-sets in determining inter and intra urban landscape matrix, thermal elevation and relative vulnerability to climate change. Such findings are particularly valuable for sustainable coastal urban landscape planning and mitigation of climate change-related impacts at local, regional and even global scales.