Simulating land surface temperature using biophysical variables related to building density and height in Dar Es Salaam, Tanzania

Simon, Olipa; Yamungu, Nestory; Lyimo, James

doi:10.1080/10106049.2022.2142971

Cited by 5 publications

(1 citation statement)

References 48 publications

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“…Duncan [20] used the model to investigate the local relationship between land cover/use (LUC) patterns and the surface temperature. The study by Siomn [21] using the GWR model similarly demonstrated the existence of a non-smooth relationship between buildings and vegetation on the surface temperature. In addition, since the classical GWR model has a uniform bandwidth for each influencing factor, some scholars have improved it using the MGWR model [22], which allows for differences in each influencing factor's range of influence and allows for a more specific representation of spatial morphological parameters' ability to influence the surface temperature [23].…”

Section: The Application Of Gwr and Mgwr To Model The Surface Tempera...mentioning

confidence: 90%

Analysis and Optimization of Thermal Environment in Old Urban Areas from the Perspective of “Function–Form” Differentiation

2023

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High-density urban areas have spatial characteristics, such as complex functions, population gathering, and complex forms, that lead to more severe urban heat island effects. Systematically evaluating the thermal environmental benefits of urban spatial forms to optimize the urban physical environment is important. In this study, Tianjin’s central urban area, which is a typical representative of high-density urban areas, was selected to invert the multi-period land surface temperature by relying on the existing two- and three-dimensional morphological data set of communities. The multi-scale geographically weighted regression model was used to fit the regression relationship between the urban land surface temperature and spatial morphological parameters. From this, the influencing factors of different types of existing community spaces and their spatial stabilities were explored. The results show the following: (1) The summer surface temperature varies greatly in the central urban area, and the high-temperature areas are mainly distributed in the industrial, residential, and commercial districts. (2) The MGWR model has the better model-fitting ability. The positive influence coefficients of temperature include ISP and BD, while the negative influence coefficients are BSD, BH, NDVI, and SVF. (3) There is significant spatial heterogeneity in the impact coefficients among the blocks that can be targeted to mitigate the heat island effect. This study provides ideas for optimizing the spatial morphological parameters of surface temperature in urban centers. Future challenges include increasing the spatial morphological parameter selection range, dissecting the interactive relationships between spatial morphological parameters and their effectiveness on the surface temperature, and refining the study’s spatial and temporal granularity.

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Section: The Application Of Gwr and Mgwr To Model The Surface Tempera...mentioning

confidence: 90%

Analysis and Optimization of Thermal Environment in Old Urban Areas from the Perspective of “Function–Form” Differentiation

2023

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Land use and cover change in Dar es Salaam metropolitan city: satellite data and CA-Markov chain analysis

Simon,

Lyimo,

Yamungu

2023

GeoJournal

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Exploring the impact of socioeconomic factors on land use and cover changes in Dar es Salaam, Tanzania: a remote sensing and GIS approach

Simon,

Lyimo,

Yamungu

2024

Arab J Geosci

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Simulating land surface temperature using biophysical variables related to building density and height in Dar Es Salaam, Tanzania

Cited by 5 publications

References 48 publications

Analysis and Optimization of Thermal Environment in Old Urban Areas from the Perspective of “Function–Form” Differentiation

Analysis and Optimization of Thermal Environment in Old Urban Areas from the Perspective of “Function–Form” Differentiation

Land use and cover change in Dar es Salaam metropolitan city: satellite data and CA-Markov chain analysis

Exploring the impact of socioeconomic factors on land use and cover changes in Dar es Salaam, Tanzania: a remote sensing and GIS approach

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