{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T02:28:47Z","timestamp":1783477727899,"version":"3.55.0"},"reference-count":79,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China Major Program","award":["42192580"],"award-info":[{"award-number":["42192580"]}]},{"name":"National Natural Science Foundation of China Major Program","award":["42192584"],"award-info":[{"award-number":["42192584"]}]},{"name":"National Natural Science Foundation of China Major Program","award":["42171357"],"award-info":[{"award-number":["42171357"]}]},{"name":"National Natural Science Foundation of China Major Program","award":["2020YFC0833100"],"award-info":[{"award-number":["2020YFC0833100"]}]},{"name":"National Natural Science Foundation of China Major Program","award":["2019-2.1.11-T\u00c9T-2020-00171"],"award-info":[{"award-number":["2019-2.1.11-T\u00c9T-2020-00171"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42192580"],"award-info":[{"award-number":["42192580"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42192584"],"award-info":[{"award-number":["42192584"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42171357"],"award-info":[{"award-number":["42171357"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2020YFC0833100"],"award-info":[{"award-number":["2020YFC0833100"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2019-2.1.11-T\u00c9T-2020-00171"],"award-info":[{"award-number":["2019-2.1.11-T\u00c9T-2020-00171"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key Research and Development Program","award":["42192580"],"award-info":[{"award-number":["42192580"]}]},{"name":"National Key Research and Development Program","award":["42192584"],"award-info":[{"award-number":["42192584"]}]},{"name":"National Key Research and Development Program","award":["42171357"],"award-info":[{"award-number":["42171357"]}]},{"name":"National Key Research and Development Program","award":["2020YFC0833100"],"award-info":[{"award-number":["2020YFC0833100"]}]},{"name":"National Key Research and Development Program","award":["2019-2.1.11-T\u00c9T-2020-00171"],"award-info":[{"award-number":["2019-2.1.11-T\u00c9T-2020-00171"]}]},{"name":"Bilateral Chinese-Hungarian Project","award":["42192580"],"award-info":[{"award-number":["42192580"]}]},{"name":"Bilateral Chinese-Hungarian Project","award":["42192584"],"award-info":[{"award-number":["42192584"]}]},{"name":"Bilateral Chinese-Hungarian Project","award":["42171357"],"award-info":[{"award-number":["42171357"]}]},{"name":"Bilateral Chinese-Hungarian Project","award":["2020YFC0833100"],"award-info":[{"award-number":["2020YFC0833100"]}]},{"name":"Bilateral Chinese-Hungarian Project","award":["2019-2.1.11-T\u00c9T-2020-00171"],"award-info":[{"award-number":["2019-2.1.11-T\u00c9T-2020-00171"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Urban environments have a strong influence on the land surface temperature (LST) in urban areas. Understanding the relationship between LST and urban environmental factors can help develop effective strategies to reduce high LSTs in urban areas, which is critical for mitigating the urban heat island effect. Previous studies have focused on the correlation between LST and the environmental factors that drive its formation, without considering the influences of the neighboring environment and the vertical expansion of highly urbanized areas. Notably, the correlation between LST and its neighboring environment in different seasons remains unclear. In this study, we selected central Beijing in China as our study area and employed the moving window method to characterize the environmental factors of the neighboring environment of the central LST cell. We explored eight environmental factors from three layers: normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), modified normalized difference water index (MNDWI), building density (BD), building height (BH), building volume (BV), sky view factor (SVF), and road density (RD). The Pearson correlation and extreme gradient boosting (XGB) regression methods were applied to measure the correlation between LST and the different factors in moving windows of different sizes. The results indicated that the correlation between NDVI, MNDWI, and LST was considerably different in the winter and other seasons. However, NDBI was positively correlated with LST in all seasons, although the correlation was strongest\/weakest in summer\/winter. Among building-related factors, BD and BH were more strongly correlated with LST, and the positive\/negative correlation between BD\/BH and LST was stronger in summer\/winter. The correlation between LST and its neighboring environment varied with increasing window size, and this variation differs significantly between winter and other seasons. In spring, summer, and autumn, the strength of the correlation between LST and its neighboring environment showed an \u201cinverted V\u201d pattern with increasing window size. The optimal spatial scales to explore the influence of neighboring environments on the LST of 30-m cells were 210 m and 270 m. This study revealed the seasonal correlation between LST and its neighboring environment while explaining the variation at a spatial scale. Notably, this study can provide a new perspective for understanding the driving mechanism of the urban thermal environment, while contributing to its scientific optimization and management.<\/jats:p>","DOI":"10.3390\/rs14174340","type":"journal-article","created":{"date-parts":[[2022,9,2]],"date-time":"2022-09-02T00:19:01Z","timestamp":1662077941000},"page":"4340","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":51,"title":["Relationships between Land Surface Temperatures and Neighboring Environment in Highly Urbanized Areas: Seasonal and Scale Effects Analyses of Beijing, China"],"prefix":"10.3390","volume":"14","author":[{"given":"Qingyan","family":"Meng","sequence":"first","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Earth Observation of Hainan Province, Hainan Aerospace Information Research Institute, Sanya 572029, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenxiu","family":"Liu","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linlin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Earth Observation of Hainan Province, Hainan Aerospace Information Research Institute, Sanya 572029, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5835-1829","authenticated-orcid":false,"given":"Mona","family":"Allam","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"Environment & Climate Changes Research Institute, National Water Research Centre, El Qanater EI Khairiya 13621\/5, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yaxin","family":"Bi","sequence":"additional","affiliation":[{"name":"School of Computing, Ulster University, Shore Rd., Newtownabbey BT37 0QB, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinli","family":"Hu","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Earth Observation of Hainan Province, Hainan Aerospace Information Research Institute, Sanya 572029, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianfeng","family":"Gao","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Die","family":"Hu","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tam\u00e1s","family":"Jancs\u00f3","sequence":"additional","affiliation":[{"name":"Alba Regia Technical Faculty, \u00d3buda University, Budai ut 45., H-8000 Szekesfehervar, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,1]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"The energetic basis of the urban heat island","volume":"108","author":"Oke","year":"1982","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"7575","DOI":"10.1073\/pnas.1817561116","article-title":"Scale-dependent interactions between tree canopy cover and impervious surfaces reduce daytime urban heat during summer","volume":"116","author":"Ziter","year":"2019","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1038\/nclimate3322","article-title":"Global risk of deadly heat","volume":"7","author":"Mora","year":"2017","journal-title":"Nat. Clim. Chang."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2318","DOI":"10.1016\/j.rser.2017.06.040","article-title":"Modeling the heating and cooling energy demand of urban buildings at city scale","volume":"81","author":"Frayssinet","year":"2018","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/S0378-7788(96)01003-1","article-title":"Peak power and cooling energy savings of shade trees","volume":"25","author":"Akbari","year":"1997","journal-title":"Energy Build."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1016\/j.uclim.2015.08.001","article-title":"Mapping the effects of urban heat island, housing, and age on excess heat-related mortality in London","volume":"14","author":"Taylor","year":"2015","journal-title":"Urban Clim."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1289\/ehp.1002313","article-title":"Heat waves in the United States: Mortality risk during heat waves and effect modification by heat wave characteristics in 43 US communities","volume":"119","author":"Anderson","year":"2011","journal-title":"Environ. Health Perspect."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"745","DOI":"10.1007\/s10980-015-0284-3","article-title":"Micro-scale urban surface temperatures are related to land-cover features and residential heat related health impacts in Phoenix, AZ USA","volume":"31","author":"Jenerette","year":"2016","journal-title":"Landsc. Ecol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"108132","DOI":"10.1016\/j.buildenv.2021.108132","article-title":"Quantifying 3D building form effects on urban land surface temperature and modeling seasonal correlation patterns","volume":"204","author":"Li","year":"2021","journal-title":"Build. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/j.rse.2018.06.010","article-title":"Seasonal contrast of the dominant factors for spatial distribution of land surface temperature in urban areas","volume":"215","author":"Peng","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Do Nascimento, A.C.L., Galvani, E., Gobo, J.P.A., and Wollmann, C.A. (2022). Comparison between air temperature and land surface temperature for the city of S\u00e3o Paulo, Brazil. Atmosphere, 13.","DOI":"10.3390\/atmos13030491"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"107650","DOI":"10.1016\/j.buildenv.2021.107650","article-title":"Separate and combined impacts of building and tree on urban thermal environment from two-and three-dimensional perspectives","volume":"194","author":"Chen","year":"2021","journal-title":"Build. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Wollmann, C.A., Hoppe, I.L., Gobo, J.P.A., Simioni, J.P.D., Costa, I.T., Baratto, J., and Shooshtarian, S. (2021). Thermo-hygrometric variability on waterfronts in negative radiation balance: A case study of balne\u00e1rio Cambori\u00fa\/SC, Brazil. Atmosphere, 12.","DOI":"10.3390\/atmos12111453"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.scitotenv.2016.04.009","article-title":"Effects of road network on diversiform forest cover changes in the highest coverage region in China: An analysis of sampling strategies","volume":"565","author":"Hu","year":"2016","journal-title":"Sci. Total Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1040","DOI":"10.1016\/j.scitotenv.2017.01.158","article-title":"Utilising green and bluespace to mitigate urban heat island intensity","volume":"584","author":"Gunawardena","year":"2017","journal-title":"Sci. Total Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"667","DOI":"10.1080\/22797254.2018.1474494","article-title":"Analytical study of land surface temperature with NDVI and NDBI using Landsat 8 OLI and TIRS data in Florence and Naples city, Italy","volume":"51","author":"Guha","year":"2018","journal-title":"Eur. J. Remote Sens."},{"key":"ref_17","first-page":"102013","article-title":"Normalised difference spectral indices and urban land cover as indicators of land surface temperature (LST)","volume":"86","author":"Alexander","year":"2020","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3025","DOI":"10.1080\/01431160600589179","article-title":"Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery","volume":"27","author":"Xu","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.pce.2019.01.008","article-title":"The higher, the cooler? Effects of building height on land surface temperatures in residential areas of Beijing","volume":"110","author":"Zheng","year":"2019","journal-title":"Phys. Chem. Earth Parts A\/B\/C"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"120706","DOI":"10.1016\/j.jclepro.2020.120706","article-title":"The effects of 3D architectural patterns on the urban surface temperature at a neighborhood scale: Relative contributions and marginal effects","volume":"258","author":"Sun","year":"2020","journal-title":"J. Clean. Prod."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1016\/j.envsoft.2016.06.021","article-title":"Characterizing the impact of urban morphology heterogeneity on land surface temperature in Guangzhou, China","volume":"84","author":"Guo","year":"2016","journal-title":"Environ. Model. Softw."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"100591","DOI":"10.1016\/j.uclim.2020.100591","article-title":"Assessing the relationship between local climatic zones (LCZs) and land surface temperature (LST)\u2014A case study of Sriniketan-Santiniketan Planning Area (SSPA), West Bengal, India","volume":"32","author":"Das","year":"2020","journal-title":"Urban Clim."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"100657","DOI":"10.1016\/j.uclim.2020.100657","article-title":"Understanding the seasonal variations of land surface temperature in Nanjing urban area based on local climate zone","volume":"33","author":"Du","year":"2020","journal-title":"Urban Clim."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.jclepro.2017.12.187","article-title":"The effect of multi-dimensional indicators on urban thermal conditions","volume":"177","author":"Alavipanah","year":"2018","journal-title":"J. Clean. Prod."},{"key":"ref_25","first-page":"102265","article-title":"Influence of the proportion, height and proximity of vegetation and buildings on urban land surface temperature","volume":"95","author":"Alexander","year":"2021","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"110424","DOI":"10.1016\/j.jenvman.2020.110424","article-title":"Modeling the impact of 2D\/3D urban indicators on the urban heat island over different seasons: A boosted regression tree approach","volume":"266","author":"Hu","year":"2020","journal-title":"J. Environ. Manag."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1002\/joc.3370010304","article-title":"Canyon geometry and the nocturnal urban heat island: Comparison of scale model and field observations","volume":"1","author":"Oke","year":"1981","journal-title":"J. Climatol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/0378-7788(88)90026-6","article-title":"Street design and urban canopy layer climate","volume":"11","author":"Oke","year":"1988","journal-title":"Energy Build."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1175\/1520-0450(1996)035<0135:HRSTPR>2.0.CO;2","article-title":"High-resolution surface temperature patterns related to urban morphology in a tropical city: A satellite-based study","volume":"35","author":"Nichol","year":"1996","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"103794","DOI":"10.1016\/j.landurbplan.2020.103794","article-title":"Effects of building density on land surface temperature in China: Spatial patterns and determinants","volume":"198","author":"Song","year":"2020","journal-title":"Landsc. Urban Plan."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"102454","DOI":"10.1016\/j.scs.2020.102454","article-title":"Detecting factors controlling spatial patterns in urban land surface temperatures: A case study of Beijing","volume":"63","author":"Wu","year":"2020","journal-title":"Sustain. Cities Soc."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.ecolind.2016.02.040","article-title":"Research on the cooling island effects of water body: A case study of Shanghai, China","volume":"67","author":"Du","year":"2016","journal-title":"Ecol. Indic."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"101864","DOI":"10.1016\/j.scs.2019.101864","article-title":"The roles of landscape both inside the park and the surroundings in park cooling effect","volume":"52","author":"Qiu","year":"2020","journal-title":"Sustain. Cities Soc."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"118383","DOI":"10.1016\/j.envpol.2021.118383","article-title":"Do industrial parks generate intra-heat island effects in cities? New evidence, quantitative methods, and contributing factors from a spatiotemporal analysis of top steel plants in China","volume":"292","author":"Meng","year":"2022","journal-title":"Environ. Pollut."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"301","DOI":"10.2747\/1548-1603.47.3.301","article-title":"Combined effects of impervious surface and vegetation cover on air temperature variations in a rapidly expanding desert city","volume":"47","author":"Myint","year":"2010","journal-title":"GIScience Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"102714","DOI":"10.1016\/j.apgeog.2022.102714","article-title":"Exploring the multitemporal surface urban heat island effect and its driving relation in the Beijing-Tianjin-Hebei urban agglomeration","volume":"144","author":"Fu","year":"2022","journal-title":"Appl. Geogr."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"9829","DOI":"10.3390\/rs6109829","article-title":"Land surface temperature retrieval from Landsat 8 TIRS\u2014Comparison between radiative transfer equation-based method, split window algorithm and single channel method","volume":"6","author":"Yu","year":"2014","journal-title":"Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1016\/j.rse.2004.02.003","article-title":"Land surface temperature retrieval from LANDSAT TM 5","volume":"90","author":"Sobrino","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"398","DOI":"10.3390\/rs3020398","article-title":"Sky-view factor as a relief visualization technique","volume":"3","author":"Kokalj","year":"2011","journal-title":"Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1016\/j.rse.2003.11.005","article-title":"Estimation of land surface temperature\u2013vegetation abundance relationship for urban heat island studies","volume":"89","author":"Weng","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"3622","DOI":"10.1016\/j.asr.2021.07.008","article-title":"Quantitative analysis of spatial distribution of land surface temperature (LST) in relation Ecohydrological, terrain and socio-economic factors based on Landsat data in mountainous area","volume":"68","author":"Taripanah","year":"2021","journal-title":"Adv. Space Res."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.rse.2017.02.020","article-title":"Spatio-temporal analysis of the relationship between 2D\/3D urban site characteristics and land surface temperature","volume":"193","author":"Berger","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_43","first-page":"205","article-title":"A computational framework for generalized moving windows and its application to landscape pattern analysis","volume":"44","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_44","first-page":"102610","article-title":"Evaluation of urban green space in terms of thermal environmental benefits using geographical detector analysis","volume":"105","author":"Wang","year":"2021","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"108354","DOI":"10.1016\/j.buildenv.2021.108354","article-title":"3D building configuration as the driver of diurnal and nocturnal land surface temperatures: Application in Beijing\u2019s old city","volume":"206","author":"Guo","year":"2021","journal-title":"Build. Environ."},{"key":"ref_46","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. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"101789","DOI":"10.1016\/j.compenvurbsys.2022.101789","article-title":"Interpretable machine learning models for crime prediction","volume":"94","author":"Zhang","year":"2022","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"138229","DOI":"10.1016\/j.scitotenv.2020.138229","article-title":"Exploring the relationship between 2D\/3D landscape pattern and land surface temperature based on explainable eXtreme Gradient Boosting tree: A case study of Shanghai, China","volume":"725","author":"Yu","year":"2020","journal-title":"Sci. Total Environ."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1177\/0361198118780204","article-title":"A comparative analysis of tree-based ensemble methods for detecting imminent lane change maneuvers in connected vehicle environments","volume":"2672","author":"Mousa","year":"2018","journal-title":"Transp. Res. Rec."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"101116","DOI":"10.1016\/j.uclim.2022.101116","article-title":"Machine learning algorithm based prediction of land use land cover and land surface temperature changes to characterize the surface urban heat island phenomena over Ahmedabad city, India","volume":"42","author":"Mohammad","year":"2022","journal-title":"Urban Clim."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Zhang, H., Eziz, A., Xiao, J., Tao, S., Wang, S., Tang, Z., Zhu, J., and Fang, J. (2019). High-resolution vegetation mapping using eXtreme gradient boosting based on extensive features. Remote Sens., 11.","DOI":"10.3390\/rs11121505"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"102006","DOI":"10.1016\/j.algal.2020.102006","article-title":"Predicting algal biochar yield using eXtreme Gradient Boosting (XGB) algorithm of machine learning methods","volume":"50","author":"Pathy","year":"2020","journal-title":"Algal Res."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"3301","DOI":"10.1016\/j.asr.2022.02.027","article-title":"Flood susceptibility modeling based on new hybrid intelligence model: Optimization of XGboost model using GA metaheuristic algorithm","volume":"69","author":"Linh","year":"2022","journal-title":"Adv. Space Res."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"101659","DOI":"10.1016\/j.scs.2019.101659","article-title":"Evaluating urban heat island intensity and its associated determinants of towns and cities continuum in the Yangtze River Delta Urban Agglomerations","volume":"50","author":"Sun","year":"2019","journal-title":"Sustain. Cities Soc."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.buildenv.2012.07.012","article-title":"An evaluation of outdoor and building environment cooling achieved through combination modification of trees with ground materials","volume":"58","author":"Shahidan","year":"2012","journal-title":"Build. Environ."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1007\/s11252-014-0407-7","article-title":"A comparison of the growth and cooling effectiveness of five commonly planted urban tree species","volume":"18","author":"Rahman","year":"2015","journal-title":"Urban Ecosyst."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"101932","DOI":"10.1016\/j.scs.2019.101932","article-title":"How can urban blue-green space be planned for climate adaption in high-latitude cities? A seasonal perspective","volume":"53","author":"Yang","year":"2020","journal-title":"Sustain. Cities Soc."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1016\/j.foreco.2019.05.046","article-title":"Strong contribution of rapid urbanization and urban agglomeration development to regional thermal environment dynamics and evolution","volume":"446","author":"Yu","year":"2019","journal-title":"For. Ecol. Manag."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Chen, L., Li, M., Huang, F., and Xu, S. (2013, January 16\u201318). Relationships of LST to NDBI and NDVI in Wuhan City based on Landsat ETM+ image. Proceedings of the 2013 6th International Congress on Image and Signal Processing (CISP), Hangzhou, China.","DOI":"10.1109\/CISP.2013.6745282"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"2503","DOI":"10.1080\/01431161.2015.1041175","article-title":"Evaluation of LST downscaling algorithms on seasonal thermal data in humid subtropical regions of India","volume":"36","author":"Mukherjee","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Sun, D., and Kafatos, M. (2007). Note on the NDVI-LST relationship and the use of temperature-related drought indices over North America. Geophys. Res. Lett., 34.","DOI":"10.1029\/2007GL031485"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"105778","DOI":"10.1016\/j.ecolind.2019.105778","article-title":"Effects of changing spatial extent on the relationship between urban forest patterns and land surface temperature","volume":"109","author":"Zhou","year":"2020","journal-title":"Ecol. Indic."},{"key":"ref_63","first-page":"30","article-title":"Urban heat island effect: A systematic review of spatio-temporal factors, data, methods, and mitigation measures","volume":"67","author":"Deilami","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1136","DOI":"10.1016\/j.scitotenv.2018.01.165","article-title":"Spatial regression models of park and land-use impacts on the urban heat island in central Beijing","volume":"626","author":"Dai","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_65","first-page":"636","article-title":"Impacts of urban cooling effect based on landscape scale: A review","volume":"26","author":"Yu","year":"2015","journal-title":"J. Appl. Ecol."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"102286","DOI":"10.1016\/j.scs.2020.102286","article-title":"Exploring the relationships between urban spatial form factors and land surface temperature in mountainous area: A case study in Chongqing city, China","volume":"61","author":"Guo","year":"2020","journal-title":"Sustain. Cities Soc."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"4080","DOI":"10.1109\/TGRS.2011.2128874","article-title":"Modeling urban heat islands and their relationship with impervious surface and vegetation abundance by using ASTER images","volume":"49","author":"Weng","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"142334","DOI":"10.1016\/j.scitotenv.2020.142334","article-title":"Surface urban heat islands in Italian metropolitan cities: Tree cover and impervious surface influences","volume":"751","author":"Morabito","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.geog.2021.05.002","article-title":"Land surface temperature and spectral indices: A seasonal study of Raipur City","volume":"13","author":"Guha","year":"2022","journal-title":"Geod. Geodyn."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"101726","DOI":"10.1016\/j.jobe.2020.101726","article-title":"Evaluation and mapping of building overheating risk and air conditioning use due to the urban heat island effect","volume":"32","author":"Hwang","year":"2020","journal-title":"J. Build. Eng."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"118917","DOI":"10.1016\/j.envpol.2022.118917","article-title":"Improved anthropogenic heat flux model for fine spatiotemporal information in Southeast China","volume":"299","author":"Qian","year":"2022","journal-title":"Environ. Pollut."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"103692","DOI":"10.1016\/j.scs.2022.103692","article-title":"A spatial quantile regression model for driving mechanism of urban heat island by considering the spatial dependence and heterogeneity: An example of Beijing, China","volume":"79","author":"Gu","year":"2022","journal-title":"Sustain. Cities Soc."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.buildenv.2015.03.037","article-title":"The impact of building density and building height heterogeneity on average urban albedo and street surface temperature","volume":"90","author":"Yang","year":"2015","journal-title":"Build. Environ."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"6910","DOI":"10.1080\/01431161.2017.1368099","article-title":"Assessing the relationship between sky view factor and land surface temperature to the spatial resolution","volume":"38","author":"Scarano","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1016\/j.scitotenv.2018.11.108","article-title":"Quantifying and simulating landscape composition and pattern impacts on land surface temperature: A decadal study of the rapidly urbanizing city of Beijing, China","volume":"654","author":"Guo","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"104043","DOI":"10.1016\/j.landurbplan.2021.104043","article-title":"Quantifying the local cooling effects of urban green spaces: Evidence from Bengaluru, India","volume":"209","author":"Shah","year":"2021","journal-title":"Landsc. Urban Plan."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"682","DOI":"10.1068\/b35097","article-title":"How good is volunteered geographical information? A comparative study of OpenStreetMap and Ordnance Survey datasets","volume":"37","author":"Haklay","year":"2010","journal-title":"Environ. Plan. B Plan. Des."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Gong, P., Chen, B., Li, X., Liu, H., Wang, J., Bai, Y., Chen, J., Chen, X., Fang, L., and Feng, S. (2020). Mapping Essential Urban Land Use Categories in China (EULUC-China): Preliminary Results for 2018, Lanzhou University.","DOI":"10.1016\/j.scib.2019.12.007"},{"key":"ref_79","doi-asserted-by":"crossref","unstructured":"Liu, W., Meng, Q., Allam, M., Zhang, L., Hu, D., and Menenti, M. (2021). Driving factors of land surface temperature in urban agglomerations: A case study in the Pearl River Delta, China. Remote Sens., 13.","DOI":"10.3390\/rs13152858"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/17\/4340\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:22:00Z","timestamp":1760142120000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/17\/4340"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,1]]},"references-count":79,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2022,9]]}},"alternative-id":["rs14174340"],"URL":"https:\/\/doi.org\/10.3390\/rs14174340","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,1]]}}}