Assessment of Urban Land Surface Temperature and Vertical City Associated with Dengue Incidences
Rapid population and urban growth in Bangkok increases the need for vertical city development because of the limited territory. This might lead to increasing land surface temperatures (LST), which makes some urban areas significantly warmer and leads to hot spots known as urban heat islands. It is k...
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MDPI AG
2020-11-01
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Series: | Remote Sensing |
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Online Access: | https://www.mdpi.com/2072-4292/12/22/3802 |
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author | Kanchana Nakhapakorn Warisara Sancharoen Auemphorn Mutchimwong Supet Jirakajohnkool Rattapon Onchang Chawarat Rotejanaprasert Kraichat Tantrakarnapa Richard Paul |
author_facet | Kanchana Nakhapakorn Warisara Sancharoen Auemphorn Mutchimwong Supet Jirakajohnkool Rattapon Onchang Chawarat Rotejanaprasert Kraichat Tantrakarnapa Richard Paul |
author_sort | Kanchana Nakhapakorn |
collection | DOAJ |
description | Rapid population and urban growth in Bangkok increases the need for vertical city development because of the limited territory. This might lead to increasing land surface temperatures (LST), which makes some urban areas significantly warmer and leads to hot spots known as urban heat islands. It is known that climatic factors, such as rainfall and temperature, influence increases in dengue incidences. Thus, this research uses spatial statistical analysis to consider the association of urban LST with dengue incidences. The LST calculation methods are based on LANDSAT imageries in 2009 and 2014. Pearson correlation and Bayesian hierarchical modeling were used for predicting dengue incidences. This study found the highest correlation between the density of high-rise buildings, which had a significant influence on LST, and dengue incidences. Both the number of high-rise buildings and the surface temperature of low-rise buildings increased dengue incidence between 2009 and 2014. Overall, it was found that for every increase of 1000 high-rise buildings, the dengue incidence increased 2.19 on average during that period. |
first_indexed | 2024-03-10T14:42:50Z |
format | Article |
id | doaj.art-6047e7d8b96044858bcea7b717491af9 |
institution | Directory Open Access Journal |
issn | 2072-4292 |
language | English |
last_indexed | 2024-03-10T14:42:50Z |
publishDate | 2020-11-01 |
publisher | MDPI AG |
record_format | Article |
series | Remote Sensing |
spelling | doaj.art-6047e7d8b96044858bcea7b717491af92023-11-20T21:37:29ZengMDPI AGRemote Sensing2072-42922020-11-011222380210.3390/rs12223802Assessment of Urban Land Surface Temperature and Vertical City Associated with Dengue IncidencesKanchana Nakhapakorn0Warisara Sancharoen1Auemphorn Mutchimwong2Supet Jirakajohnkool3Rattapon Onchang4Chawarat Rotejanaprasert5Kraichat Tantrakarnapa6Richard Paul7Faculty of Environment and Resource Studies, Mahidol University, Nakhon Pathom 73170, ThailandFaculty of Environment and Resource Studies, Mahidol University, Nakhon Pathom 73170, ThailandFaculty of Environment and Resource Studies, Mahidol University, Nakhon Pathom 73170, ThailandFaculty of Science and Technology, Thammasat University, Pathum Thani 12120, ThailandDepartment of Environmental Science, Faculty of Science, Silapakorn University, Nakhon Pathom 73000, ThailandDepartment of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, ThailandDepartment of Social and Environmental Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, ThailandInstitut Pasteur, Functional Genetics of Infectious Disease Unit, UMR 2000 CNRS, 25 Rue du Dr. Roux, CEDEX 15, 75724 Paris, FranceRapid population and urban growth in Bangkok increases the need for vertical city development because of the limited territory. This might lead to increasing land surface temperatures (LST), which makes some urban areas significantly warmer and leads to hot spots known as urban heat islands. It is known that climatic factors, such as rainfall and temperature, influence increases in dengue incidences. Thus, this research uses spatial statistical analysis to consider the association of urban LST with dengue incidences. The LST calculation methods are based on LANDSAT imageries in 2009 and 2014. Pearson correlation and Bayesian hierarchical modeling were used for predicting dengue incidences. This study found the highest correlation between the density of high-rise buildings, which had a significant influence on LST, and dengue incidences. Both the number of high-rise buildings and the surface temperature of low-rise buildings increased dengue incidence between 2009 and 2014. Overall, it was found that for every increase of 1000 high-rise buildings, the dengue incidence increased 2.19 on average during that period.https://www.mdpi.com/2072-4292/12/22/3802land surface temperature (LST)vertical cityurban heat islands (UHIs)dengue incidencesPearson correlationBayesian hierarchical modeling |
spellingShingle | Kanchana Nakhapakorn Warisara Sancharoen Auemphorn Mutchimwong Supet Jirakajohnkool Rattapon Onchang Chawarat Rotejanaprasert Kraichat Tantrakarnapa Richard Paul Assessment of Urban Land Surface Temperature and Vertical City Associated with Dengue Incidences Remote Sensing land surface temperature (LST) vertical city urban heat islands (UHIs) dengue incidences Pearson correlation Bayesian hierarchical modeling |
title | Assessment of Urban Land Surface Temperature and Vertical City Associated with Dengue Incidences |
title_full | Assessment of Urban Land Surface Temperature and Vertical City Associated with Dengue Incidences |
title_fullStr | Assessment of Urban Land Surface Temperature and Vertical City Associated with Dengue Incidences |
title_full_unstemmed | Assessment of Urban Land Surface Temperature and Vertical City Associated with Dengue Incidences |
title_short | Assessment of Urban Land Surface Temperature and Vertical City Associated with Dengue Incidences |
title_sort | assessment of urban land surface temperature and vertical city associated with dengue incidences |
topic | land surface temperature (LST) vertical city urban heat islands (UHIs) dengue incidences Pearson correlation Bayesian hierarchical modeling |
url | https://www.mdpi.com/2072-4292/12/22/3802 |
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