Simulating land surface temperature using biophysical variables related to building density and height in Dar Es Salaam, Tanzania
Land use and land cover dynamics are pivotal to communicating land surface temperature (LST) scenarios. This study characterises the influence of biophysical variables on LSTs in the Dar es Salaam Metropolitan City (DMC). Landsat images were analysed using geographically weighted regression (GWR) an...
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Taylor & Francis Group
2023-12-01
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| Series: | Geocarto International |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/10106049.2022.2142971 |
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| author | Olipa Simon Nestory Yamungu James Lyimo |
| author_facet | Olipa Simon Nestory Yamungu James Lyimo |
| author_sort | Olipa Simon |
| collection | DOAJ |
| description | Land use and land cover dynamics are pivotal to communicating land surface temperature (LST) scenarios. This study characterises the influence of biophysical variables on LSTs in the Dar es Salaam Metropolitan City (DMC). Landsat images were analysed using geographically weighted regression (GWR) and ordinary least square (OLS) models to determine biophysical variables (soil adjusted vegetation index, normalized difference built-up index, and normalised difference bareness index) and LST relationships. The GWR analysis resultsrevealed that LST had a weak to strong negative correlation with the soil adjusted vegetation index, a moderate positive correlation with normalized difference built-up index, and a low positive correlation with the normalised difference bareness index. GWR predicted LST better than OLS, with coefficient of determination -R2 values of 55%, 80%, and 62% for 1995, 2009, and 2017, respectively. In addition, higher model residuals values were observed in high building density compared to low building density areas. This study provides a broad understanding of the biophysical variables’ impact on LST in DMC and provides reference for site-specific urban land-use planning and designing strategies for LST mitigation. |
| format | Article |
| id | doaj-art-255927efd4474660a6b5a959c1e61a5d |
| institution | Kabale University |
| issn | 1010-6049 1752-0762 |
| language | English |
| publishDate | 2023-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geocarto International |
| spelling | doaj-art-255927efd4474660a6b5a959c1e61a5d2024-11-25T13:41:45ZengTaylor & Francis GroupGeocarto International1010-60491752-07622023-12-0138110.1080/10106049.2022.2142971Simulating land surface temperature using biophysical variables related to building density and height in Dar Es Salaam, TanzaniaOlipa Simon0Nestory Yamungu1James Lyimo2Institute of Resource Assessment, University of Dar es Salaam, Dar es Salaam, TanzaniaDepartment of Geography, University of Dar es Salaam, Dar es Salaam, TanzaniaInstitute of Resource Assessment, University of Dar es Salaam, Dar es Salaam, TanzaniaLand use and land cover dynamics are pivotal to communicating land surface temperature (LST) scenarios. This study characterises the influence of biophysical variables on LSTs in the Dar es Salaam Metropolitan City (DMC). Landsat images were analysed using geographically weighted regression (GWR) and ordinary least square (OLS) models to determine biophysical variables (soil adjusted vegetation index, normalized difference built-up index, and normalised difference bareness index) and LST relationships. The GWR analysis resultsrevealed that LST had a weak to strong negative correlation with the soil adjusted vegetation index, a moderate positive correlation with normalized difference built-up index, and a low positive correlation with the normalised difference bareness index. GWR predicted LST better than OLS, with coefficient of determination -R2 values of 55%, 80%, and 62% for 1995, 2009, and 2017, respectively. In addition, higher model residuals values were observed in high building density compared to low building density areas. This study provides a broad understanding of the biophysical variables’ impact on LST in DMC and provides reference for site-specific urban land-use planning and designing strategies for LST mitigation.https://www.tandfonline.com/doi/10.1080/10106049.2022.2142971biophysical variablegeographically weighted regressionland surface temperatureordinary least squareurbanisation |
| spellingShingle | Olipa Simon Nestory Yamungu James Lyimo Simulating land surface temperature using biophysical variables related to building density and height in Dar Es Salaam, Tanzania Geocarto International biophysical variable geographically weighted regression land surface temperature ordinary least square urbanisation |
| title | Simulating land surface temperature using biophysical variables related to building density and height in Dar Es Salaam, Tanzania |
| title_full | Simulating land surface temperature using biophysical variables related to building density and height in Dar Es Salaam, Tanzania |
| title_fullStr | Simulating land surface temperature using biophysical variables related to building density and height in Dar Es Salaam, Tanzania |
| title_full_unstemmed | Simulating land surface temperature using biophysical variables related to building density and height in Dar Es Salaam, Tanzania |
| title_short | Simulating land surface temperature using biophysical variables related to building density and height in Dar Es Salaam, Tanzania |
| title_sort | simulating land surface temperature using biophysical variables related to building density and height in dar es salaam tanzania |
| topic | biophysical variable geographically weighted regression land surface temperature ordinary least square urbanisation |
| url | https://www.tandfonline.com/doi/10.1080/10106049.2022.2142971 |
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