Homer Pagkalinawan , Laurence L Delina , Sharon Feliza Ann Macagba
{"title":"Gridded dataset on land surface temperature and selected environmental and socioeconomic features in Southeast Asian metropolises","authors":"Homer Pagkalinawan , Laurence L Delina , Sharon Feliza Ann Macagba","doi":"10.1016/j.dib.2024.110848","DOIUrl":null,"url":null,"abstract":"<div><p>As Southeast Asia grapples with extreme heat occurrences in recent years, mapping which areas are clustered with elevated temperatures is crucial for monitoring the at-risk population. Identifying the contributing factors to the warming trends in these areas is also vital in formulating adaptation and mitigation strategies. This dataset comprises land surface temperature (LST) in three metropolises in the region – Metropolitan Manila, Bangkok Metropolitan Area, and Greater Jakarta – downloaded and processed from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. We used MODIS’ inherent grid system to map LST values at the satellite image's most granular level. We combined them with selected environmental and socioeconomic variables, including building and built-up areas, areas of greeneries, industrial zones, and water bodies, nighttime light (to approximate areas of economic activities), gridded population, distance from water bodies, and indicators on which urban infrastructures, i.e. roads and airports, are present in each grid. Available in shapefile and comma-separate variable file format, this dataset is useful for urban studies in these three cities. The dataset can be easily updated as additional data on LST and other variables becomes available.</p></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352340924008126/pdfft?md5=d8e98cc25fc12fb6608f446c4c943cfe&pid=1-s2.0-S2352340924008126-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data in Brief","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352340924008126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
As Southeast Asia grapples with extreme heat occurrences in recent years, mapping which areas are clustered with elevated temperatures is crucial for monitoring the at-risk population. Identifying the contributing factors to the warming trends in these areas is also vital in formulating adaptation and mitigation strategies. This dataset comprises land surface temperature (LST) in three metropolises in the region – Metropolitan Manila, Bangkok Metropolitan Area, and Greater Jakarta – downloaded and processed from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. We used MODIS’ inherent grid system to map LST values at the satellite image's most granular level. We combined them with selected environmental and socioeconomic variables, including building and built-up areas, areas of greeneries, industrial zones, and water bodies, nighttime light (to approximate areas of economic activities), gridded population, distance from water bodies, and indicators on which urban infrastructures, i.e. roads and airports, are present in each grid. Available in shapefile and comma-separate variable file format, this dataset is useful for urban studies in these three cities. The dataset can be easily updated as additional data on LST and other variables becomes available.
期刊介绍:
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