Spatio-Temporal Land Cover Analysis and the Impact of Land Cover Variability Indices on Land Surface Temperature in Greater Accra, Ghana Using Multi-Temporal Landsat Data

作     者：Aarthi Aishwarya Devendran Fabrice Banon Aarthi Aishwarya Devendran;Fabrice Banon

作者机构：Department of Built Environment and Energy Technology Linnaeus University Vä xjö  Sweden Ecole Africaine des Métiers de l’Architecture et de l’Urbanisme Lomé Togo 

出 版 物：《Journal of Geographic Information System》 (地理信息系统（英文）)

年 卷 期：2022年第14卷第3期

页      面：240-258页

学科分类：083002[工学-环境工程] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 08[工学] 09[农学] 0804[工学-仪器科学与技术] 0903[农学-农业资源与环境] 0816[工学-测绘科学与技术] 081602[工学-摄影测量与遥感] 081102[工学-检测技术与自动化装置] 0811[工学-控制科学与工程] 

主　　题：Land Surface Temperature Urbanization Land Cover Variability Indices Landsat 7 ETM Greater Accra 

摘      要：Urbanization, as a result of anthropogenic activities, reduces the vegetated and green spaces and thereby increases the impervious surfaces in cities. This in turn increases the surface temperature of cities when compared to the rural regions resulting in the formation of urban heat island. Especially, in under-developed countries, it is very crucial to obtain timely and accurate information on the urban trend and its development due to the higher increasing rate of population growth and lack of infrastructural facilities and regulations to mitigate the adverse consequences of urbanization. The current study analyzes the urban development of Greater Accra, Ghana using Landsat 7 dataset acquired in 2002, 2013, and 2020. Further, the influence of urban growth on the land surface temperature (LST) and land cover variability (LCV) indices including NDVI (Normalized Difference Vegetation Index), NDBI (Normalized Difference Built-Up Index), and NDWI (Normalized Difference Water Index) is identified during the study periods. Results suggest that the area of built-up quadrupled between 2002 and 2020 in the study region. Shannon’s entropy-based analysis suggests that the urban development in the region is heterogeneous or dispersive in nature. Further, the regression analysis highlights a strong positive relation between LST and NDBI (0.755) and a negative relation is found associated between LST and NDVI (0.4417) and LST and NDWI (0.76). Results of the study could be useful to design sustainable urban socio-economic and environmental planning policies in the study region.