Impacts of the spatial configuration of built-up areas and urban vegetation on land surface temperature using spectral and local spatial autocorrelation indices
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Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
Remote Sensing Letters
Abstract
Understanding how the spatial configuration of land cover patterns of built-up areas and urban vegetation affect urban surface temperatures is crucial for improving the sustainability of cities as well as optimizing urban design and landscape planning. Because of their capability to detect distinct surface thermal features, satellite data have proved useful in exploring the impacts of spatial configuration of land cover on land surface temperature (LST). In this study, we examine how the spatial configuration of built-up and urban vegetation affects the LST in the Harare metropolitan city, Zimbabwe. In order to achieve this objective, we combined the LST, local spatial statistics of Getis-Ord Gi* and local Moran’s I statistic, Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Built-Up Index (NDBI) derived from multi-date Landsat satellite data (1994, 2001 and 2017)
Description
Keywords
Spatial configuration, Land surface temperature (LST), Urban vegetation, Zimbabwe, Getis-Ord G Statistics
Citation
Kowe, P., Dube, T., Mushore, T.D., Ncube, A., Nyenda, T., Mutowo, G., Chinembiri, T.S., Traore, M. and Kizilirmak, G., 2022. Impacts of the spatial configuration of built-up areas and urban vegetation on land surface temperature using spectral and local spatial autocorrelation indices. Remote Sensing Letters, 13(12), pp.1222-1235.