{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T23:10:42Z","timestamp":1784589042103,"version":"3.55.0"},"reference-count":74,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,4,30]],"date-time":"2022-04-30T00:00:00Z","timestamp":1651276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the Strategic Priority Research Program of the Chinese Academy of Sciences","doi-asserted-by":"publisher","award":["XDA19030502"],"award-info":[{"award-number":["XDA19030502"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"the Strategic Priority Research Program of the Chinese Academy of Sciences","doi-asserted-by":"publisher","award":["42071321"],"award-info":[{"award-number":["42071321"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Understanding the spatiotemporal patterns of urban heat islands and the factors that influence this phenomenon can help to alleviate the heat stress exacerbated by urban warming and strengthen heat-related urban resilience, thereby contributing to the achievement of the United Nations Sustainable Development Goals. The association between surface urban heat island (SUHI) effects and land use\/land cover features has been studied extensively, but the situation in tropical cities is not well-understood due to the lack of consistent data. This study aimed to explore land use\/land cover (LULC) changes and their impact on the urban thermal environment in a tropical megacity\u2014Karachi, Pakistan. Land cover maps were produced, and the land surface temperature (LST) was estimated using Landsat images from five different years over the period 2000\u20132020. The surface urban heat island intensity (SUHII) was then quantified based on the LST data. Statistical analyses, including geographically weighted regression (GWR) and correlation analyses, were performed in order to analyze the relationship between the land cover composition and LST. The results indicated that the built-up area of Karachi increased from 97.6 km\u00b2 to 325.33 km\u00b2 during the period 2000\u20132020. Among the different land cover types, the areas classified as built-up or bare land exhibited the highest LST, and a change from vegetation to bare land led to an increase in LST. The correlation analysis indicated that the correlation coefficients between the normalized difference built-up index (NDBI) and LST ranged from 0.14 to 0.18 between 2000 and 2020 and that NDBI plays a dominant role in influencing the LST. The GWR analysis revealed the spatial variation in the association between the land cover composition and the SUHII. Parks with large areas of medium- and high-density vegetation play a significant role in regulating the thermal environment, whereas the scattered vegetation patches in the urban core do not have a significant relationship with the LST. These findings can be used to inform adaptive land use planning that aims to mitigate the effects of the UHI and aid efforts to achieve sustainable urban growth.<\/jats:p>","DOI":"10.3390\/rs14092164","type":"journal-article","created":{"date-parts":[[2022,5,2]],"date-time":"2022-05-02T07:08:58Z","timestamp":1651475338000},"page":"2164","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":75,"title":["Characterizing Spatiotemporal Variations in the Urban Thermal Environment Related to Land Cover Changes in Karachi, Pakistan, from 2000 to 2020"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4165-6802","authenticated-orcid":false,"given":"Muhammad Fahad","family":"Baqa","sequence":"first","affiliation":[{"name":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Science, Beijing 100049, China"},{"name":"International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1647-1950","authenticated-orcid":false,"given":"Linlin","family":"Lu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fang","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4146-9481","authenticated-orcid":false,"given":"Syed","family":"Nawaz-ul-Huda","sequence":"additional","affiliation":[{"name":"Dawn GIS, Geospatial Statistical Research & Analysis Division, Karachi 75300, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2207-0942","authenticated-orcid":false,"given":"Luyang","family":"Pan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1196-1248","authenticated-orcid":false,"given":"Aqil","family":"Tariq","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7955-7490","authenticated-orcid":false,"given":"Salman","family":"Qureshi","sequence":"additional","affiliation":[{"name":"Institute of Geography, Humboldt University of Berlin, 12489 Berlin, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingting","family":"Li","sequence":"additional","affiliation":[{"name":"Airborne Remote Sensing Center, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.progress.2011.04.001","article-title":"The dimensions of global urban expansion: Estimates and projections for all countries, 2000\u20132050","volume":"75","author":"Angel","year":"2011","journal-title":"Prog. 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