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However, few studies have comprehensively explored the effects of two\/three-dimensional (2D\/3D) building patterns on LST, particularly by comparing their relative contribution to the spatial variety of LST. This study adopted the ordinary least squares regression, spatial autoregression and variance partitioning methods to investigate the relationship between 2D\/3D building patterns and summertime LST across 2016\u20132017 in Shanghai. The 2D and 3D building patterns in this study were quantified by four 2D and six 3D metrics. The results showed that: (1) During the daytime, 2D\/3D building metrics had significant correlation with LST. However, 3D building patterns played a significant role in predicting LST. They explained 51.0% and 10.2% of the variance in LST, respectively. (2) The building coverage ratio, building density, mean building projection area, the standard deviation of building height, and mean building height highly correlated with LST. Specifically, the building coverage ratio was the main predictor, which was obviously positively correlated with LST. The correlation of building density and average projected area with LST was positive and significant, while the correlation of building height standard deviation and average building height with LST was negative. The increase in average height and standard deviation of buildings and the decrease in building coverage ratio, average projected area, and density of buildings, can effectively improve the urban thermal environment at the census tract level. (3) Spatial autocorrelation analysis can elaborate the spatial relationship between building patterns and LST. The findings from our research will provide important insights for urban planners and decision makers to mitigate urban heat island problems through urban planning and building design.<\/jats:p>","DOI":"10.3390\/rs14164098","type":"journal-article","created":{"date-parts":[[2022,8,22]],"date-time":"2022-08-22T01:56:40Z","timestamp":1661133400000},"page":"4098","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":46,"title":["Quantifying the Relationship between 2D\/3D Building Patterns and Land Surface Temperature: Study on the Metropolitan Shanghai"],"prefix":"10.3390","volume":"14","author":[{"given":"Rui","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China"}]},{"given":"Hongchao","family":"Xu","sequence":"additional","affiliation":[{"name":"CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China"},{"name":"College of Geography and Environment, Shandong Normal University, Jinan 250300, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9735-1098","authenticated-orcid":false,"given":"Hao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Laboratory for Applied Earth Observation and Spatial Analysis (LAEOSA), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China"}]},{"given":"Jie","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3372-9186","authenticated-orcid":false,"given":"Miao","family":"Liu","sequence":"additional","affiliation":[{"name":"CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China"}]},{"given":"Tianxing","family":"He","sequence":"additional","affiliation":[{"name":"School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China"}]},{"given":"Jun","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1987-7174","authenticated-orcid":false,"given":"Chunlin","family":"Li","sequence":"additional","affiliation":[{"name":"CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.rse.2015.11.027","article-title":"Urban thermal environment dynamics and associated landscape pattern factors: A case study in the Beijing metropolitan region","volume":"173","author":"Peng","year":"2016","journal-title":"Remote Sens. 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