Impacts of the spatial configuration of built-up areas and urban vegetation on land surface temperature using spectral and local spatial autocorrelation indices
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...
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| Format: | research article |
| Language: | English |
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Taylor and Francis Online
2022
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| Online Access: | https://cris.library.msu.ac.zw//handle/11408/5321 |
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| author | Pedzisai Kowe Data Science and Spatial Analytics Lab PhD (GIScience and Remote Sensing) Terence Darlington Mushore Amos Ncube Tatenda Nyenda Godfrey Mutowo Tsikai Solomon Chinembiri Mamadou Traore Gökhan Kizilirmak |
| author2 | Data Science and Spatial Analytics Lab PhD (GIScience and Remote Sensing) |
| author_facet | Data Science and Spatial Analytics Lab PhD (GIScience and Remote Sensing) Pedzisai Kowe Data Science and Spatial Analytics Lab PhD (GIScience and Remote Sensing) Terence Darlington Mushore Amos Ncube Tatenda Nyenda Godfrey Mutowo Tsikai Solomon Chinembiri Mamadou Traore Gökhan Kizilirmak |
| author_sort | Pedzisai Kowe |
| collection | DSpace |
| description | 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). The results of local Moran’s I statistic showed moderate and negative correlations between LST and Landsat derived NDVI. Overall, these results of local Moran’s I statistic demonstrate that clustered vegetation tend to lower LST, providing thermal comfort conditions. In contrast, clustered spatial arrangements of NDBI based on the Getis-Ord Gi* elevate LST, implying that continued clustered built-up expansion has the potential to increase urban surface temperatures. |
| format | research article |
| id | ir-11408-5321 |
| institution | My University |
| language | English |
| publishDate | 2022 |
| publisher | Taylor and Francis Online |
| record_format | dspace |
| spelling | ir-11408-53212022-12-20T10:46:13Z Impacts of the spatial configuration of built-up areas and urban vegetation on land surface temperature using spectral and local spatial autocorrelation indices Pedzisai Kowe Data Science and Spatial Analytics Lab PhD (GIScience and Remote Sensing) Terence Darlington Mushore Amos Ncube Tatenda Nyenda Godfrey Mutowo Tsikai Solomon Chinembiri Mamadou Traore Gökhan Kizilirmak Data Science and Spatial Analytics Lab PhD (GIScience and Remote Sensing) #PLACEHOLDER_PARENT_METADATA_VALUE# University of Zimbabwe | UZ · Department of Space Science and Applied Physics PhD Environmental Science (Remote Sensing), MSc GIS and Earth Observations (Water Resources and Environmental Management), Postgrad in Meteorology, BSc Honours Physics Parthenope University of Naples | Università Parthenope · Department of Science and Technology Master of Science Sustainability Life Cycle Analysis Stellenbosch University | SUN · Department of Conservation Ecology and Entomology #PLACEHOLDER_PARENT_METADATA_VALUE# #PLACEHOLDER_PARENT_METADATA_VALUE# OYAK & Cimpor Global Holding Doctor of Engineering Istanbul Technical University · Center for Satellite Communications and Remote Sensing MS spatial configuration urban vegetation land surface temperature (LST) Normalized Difference Vegetation Index (NDVI) Normalized Difference Built-Up Index (NDBI) 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). The results of local Moran’s I statistic showed moderate and negative correlations between LST and Landsat derived NDVI. Overall, these results of local Moran’s I statistic demonstrate that clustered vegetation tend to lower LST, providing thermal comfort conditions. In contrast, clustered spatial arrangements of NDBI based on the Getis-Ord Gi* elevate LST, implying that continued clustered built-up expansion has the potential to increase urban surface temperatures. 13 12 1222 1235 2022-12-20T10:46:13Z 2022-12-20T10:46:13Z 2022-11 research article https://cris.library.msu.ac.zw//handle/11408/5321 DOI:10.1080/2150704X.2022.2142073 en Remote Sensing Letters open Taylor and Francis Online |
| spellingShingle | spatial configuration urban vegetation land surface temperature (LST) Normalized Difference Vegetation Index (NDVI) Normalized Difference Built-Up Index (NDBI) Pedzisai Kowe Data Science and Spatial Analytics Lab PhD (GIScience and Remote Sensing) Terence Darlington Mushore Amos Ncube Tatenda Nyenda Godfrey Mutowo Tsikai Solomon Chinembiri Mamadou Traore Gökhan Kizilirmak Impacts of the spatial configuration of built-up areas and urban vegetation on land surface temperature using spectral and local spatial autocorrelation indices |
| title | Impacts of the spatial configuration of built-up areas and urban vegetation on land surface temperature using spectral and local spatial autocorrelation indices |
| title_full | Impacts of the spatial configuration of built-up areas and urban vegetation on land surface temperature using spectral and local spatial autocorrelation indices |
| title_fullStr | Impacts of the spatial configuration of built-up areas and urban vegetation on land surface temperature using spectral and local spatial autocorrelation indices |
| title_full_unstemmed | Impacts of the spatial configuration of built-up areas and urban vegetation on land surface temperature using spectral and local spatial autocorrelation indices |
| title_short | Impacts of the spatial configuration of built-up areas and urban vegetation on land surface temperature using spectral and local spatial autocorrelation indices |
| title_sort | impacts of the spatial configuration of built-up areas and urban vegetation on land surface temperature using spectral and local spatial autocorrelation indices |
| topic | spatial configuration urban vegetation land surface temperature (LST) Normalized Difference Vegetation Index (NDVI) Normalized Difference Built-Up Index (NDBI) |
| url | https://cris.library.msu.ac.zw//handle/11408/5321 |
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