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In this study, we retrieved two types of land surface temperature (LST) data and constructed 12 SUHI scenarios over the Guangdong\u2013Hong Kong\u2013Macao Greater Bay Area Central region using six SUHI identification methods. It compared the SUHI sensitivity differences among different types of LCZ and UFZ to analyze the global and local sensitivity differences of influencing factors in the 12 SUHI scenarios by utilizing the spatial gradient boosting trees, geographically weighted regression, and the coefficient of variation model. Results showed the following: (1) The sensitivity of different LCZ and UFZ types to multi-scenario SUHI was significantly affected by differences in SUHI identification methods and non-urban references. (2) In the morning, the shading effect of building clusters reduced the surface urban heat island intensity (SUHII) of some built environment types (such as LCZ 1 (compact high-rise zone) to LCZ 5 (open midrise zone)). The SUHIIs of LCZ E (bare rock or paved zone) and LCZ 10 (industry zone) were 4.22 \u00b0C and 3.87 \u00b0C, respectively, and both are classified as highly sensitive to SUHI. (3) The sensitivity of SUHI influencing factors exhibited regional variability, with importance differences in the sensitivity of importance for factors such as the impervious surface ratio, elevation, average building height, vegetation coverage, and average building volume between LCZs and UFZs. Amongst the 12 SUHI scenarios, an average of 87.43% and 89.97% of areas in LCZs and UFZs, respectively, were found to have low spatial sensitivity types. Overall, this study helps urban planners and managers gain a more comprehensive understanding of the complexity of the SUHI effect in high-density cities, providing a scientific basis for future urban climate adaptability planning.<\/jats:p>","DOI":"10.3390\/rs16163048","type":"journal-article","created":{"date-parts":[[2024,8,19]],"date-time":"2024-08-19T10:11:28Z","timestamp":1724062288000},"page":"3048","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Sensitivity of Local Climate Zones and Urban Functional Zones to Multi-Scenario Surface Urban Heat Islands"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3724-8571","authenticated-orcid":false,"given":"Haojian","family":"Deng","sequence":"first","affiliation":[{"name":"School of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China"}]},{"given":"Shiran","family":"Zhang","sequence":"additional","affiliation":[{"name":"Faculty of Architecture, The University of Hong Kong, Hong Kong 999077, China"}]},{"given":"Minghui","family":"Chen","sequence":"additional","affiliation":[{"name":"Dongguan Geographic Information and Planning Research Center, Dongguan 523000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8082-5525","authenticated-orcid":false,"given":"Jiali","family":"Feng","sequence":"additional","affiliation":[{"name":"Guangdong-Hong Kong-Macao Greater Bay Area Weather Research Center for Monitoring Warning and Forecasting, Shenzhen Institute of Meteorological Innovation, Shenzhen 518000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1829-7557","authenticated-orcid":false,"given":"Kai","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China"},{"name":"Guangdong Provincial Key Laboratory of Urbanization and Geo-Simulation, Guangzhou 510006, China"},{"name":"Guangdong Provincial Engineering Research Center for Public Security and Disaster, Sun Yat-sen University, Guangzhou 510006, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519000, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,19]]},"reference":[{"key":"ref_1","unstructured":"United Nations Department of Economic Social Affairs (2019). 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