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Application of GIS-Based Neighborhood Analysis to Assess The Impacts of Land Cover on Land Surface Temperature in Ho Chi Minh City
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Abstract
Land surface temperature (LST) monitoring using remote sensing is widely applied, but the influence of land cover on LST has received limited attention in the literature. This study aims to analyze the impact of various land cover types on LST in Ho Chi Minh City (HCMC), one of the fastest-growing urban areas in Southeast Asia. Based on Landsat 8 satellite imagery acquired on March 29, 2015, the maximum likelihood classification method was used to classify land cover into seven types: impervious surfaces, bare land, water bodies, clouds, dense vegetation, sparse vegetation, and moderate vegetation. LST values were extracted using the land surface emissivity coefficient and vegetation index. The impact of land cover on LST was assessed using neighborhood analysis in GIS. The results show that impervious surfaces are the dominant land cover in HCMC, with most areas having an LST of 34.9°C or lower. Additionally, the average LST of impervious surfaces and bare land decreases as neighboring pixels have higher vegetation cover. Impervious surfaces and bare land in neighboring pixels increase the average LST of water body pixels. The average LST of vegetation pixels is inversely correlated with the vegetation cover of neighboring pixels. These findings provide crucial insights into urban heat management and can inform strategies for mitigating the impact of LST on the urban environment, such as increasing green spaces and improving urban planning.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Keywords
Neighborhood analysis, land cover, land surface temperature, Landsat 8, Ho Chi Minh City
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