{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T19:13:57Z","timestamp":1775243637872,"version":"3.50.1"},"reference-count":88,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2023,6,2]],"date-time":"2023-06-02T00:00:00Z","timestamp":1685664000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31770679"],"award-info":[{"award-number":["31770679"]}],"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":["BS2022-15"],"award-info":[{"award-number":["BS2022-15"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Postgraduate Research and Practice Innovation Program of Jiangsu Province","award":["31770679"],"award-info":[{"award-number":["31770679"]}]},{"name":"Postgraduate Research and Practice Innovation Program of Jiangsu Province","award":["BS2022-15"],"award-info":[{"award-number":["BS2022-15"]}]},{"name":"Suzhou Polytechnic Institute of Agriculture Doctoral Promotion Program Research Fund","award":["31770679"],"award-info":[{"award-number":["31770679"]}]},{"name":"Suzhou Polytechnic Institute of Agriculture Doctoral Promotion Program Research Fund","award":["BS2022-15"],"award-info":[{"award-number":["BS2022-15"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Land use and land cover (LULC) changes resulting from rapid urbanization are the foremost causes of increases in land surface temperature (LST) in urban areas. Exploring the impact of LULC changes on the spatiotemporal patterns of LST under future climate change scenarios is critical for sustainable urban development. This study aimed to project the LST of Nanjing for 2025 and 2030 under different climate change scenarios using simulated LULC and land coverage indicators. Thermal infrared data from Landsat images were used to derive spatiotemporal patterns of LST in Nanjing from 1990 to 2020. The patch-generating land use simulation (PLUS) model was applied to simulate the LULC of Nanjing for 2025 and 2030 using historical LULC data and spatial driving factors. We simulated the corresponding land coverage indicators using simulated LULC data. We then generated LSTs for 2025 and 2030 under different climate change scenarios by applying regression relationships between LST and land coverage indicators. The results show that the LST of Nanjing has been increasing since 1990, with the mean LST increased from 23.44 \u00b0C in 1990 to 25.40 \u00b0C in 2020, and the mean LST estimated to reach 26.73 \u00b0C in 2030 (SSP585 scenario, integrated scenario of SSP5 and RCP5.8). There were significant differences in the LST under different climate scenarios, with increases in LST gradually decreasing under the SSP126 scenario (integrated scenario of SSP1 and RCP2.6). LST growth was similar to the historical trend under the SSP245 scenario (integrated scenario of SSP2 and RCP4.5), and an extreme increase in LST was observed under the SSP585 scenario. Our results suggest that the increase in impervious surface area is the main reason for the LST increase and urban heat island (UHI) effect. Overall, we proposed a method to project future LST considering land use change effects and provide reasonable LST scenarios for Nanjing, which may be useful for mitigating the UHI effect.<\/jats:p>","DOI":"10.3390\/rs15112914","type":"journal-article","created":{"date-parts":[[2023,6,2]],"date-time":"2023-06-02T10:08:41Z","timestamp":1685700521000},"page":"2914","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Prediction of Land Surface Temperature Considering Future Land Use Change Effects under Climate Change Scenarios in Nanjing City, China"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6740-1608","authenticated-orcid":false,"given":"Lei","family":"Tian","sequence":"first","affiliation":[{"name":"Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"}]},{"given":"Yu","family":"Tao","sequence":"additional","affiliation":[{"name":"Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"},{"name":"Anhui Province Key Laboratory of Physical Geographical Environment, Chuzhou 239000, China"}]},{"given":"Mingyang","family":"Li","sequence":"additional","affiliation":[{"name":"Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"}]},{"given":"Chunhua","family":"Qian","sequence":"additional","affiliation":[{"name":"College of Smart Agricultural, Suzhou Polytechnic Institute of Agriculture, Suzhou 215008, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5258-7849","authenticated-orcid":false,"given":"Tao","family":"Li","sequence":"additional","affiliation":[{"name":"Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"}]},{"given":"Yi","family":"Wu","sequence":"additional","affiliation":[{"name":"Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"}]},{"given":"Fang","family":"Ren","sequence":"additional","affiliation":[{"name":"Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1016\/j.ecolind.2015.10.014","article-title":"Classification of the heterogeneous structure of urban landscapes (STURLA) as an indicator of landscape function applied to surface temperature in New York City","volume":"70","author":"Hamstead","year":"2016","journal-title":"Ecol. Indic."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"112350","DOI":"10.1016\/j.rser.2022.112350","article-title":"Beating the urban heat: Situation, background, impacts and the way forward in China","volume":"161","author":"He","year":"2022","journal-title":"Renew. Sust. Energy Rev."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.isprsjprs.2021.04.009","article-title":"Statistical estimation of next-day nighttime surface urban heat islands","volume":"176","author":"Lai","year":"2021","journal-title":"ISPRS J. Photogramm."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1223","DOI":"10.1007\/s11069-022-05224-y","article-title":"Effect of land use land cover changes on land surface temperature during 1984\u20132020: A case study of Baghdad city using landsat image","volume":"112","author":"Hashim","year":"2022","journal-title":"Nat. Hazards"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.scs.2016.03.009","article-title":"Assessment of Urban Heat Island based on the relationship between land surface temperature and Land Use\/Land Cover in Tehran","volume":"23","author":"Bokaie","year":"2016","journal-title":"Sustain. Cities Soc."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"112585","DOI":"10.1016\/j.rse.2021.112585","article-title":"Croplands intensify regional and global warming according to satellite observations","volume":"264","author":"Zhou","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"e2020JD033521","DOI":"10.1029\/2020JD033521","article-title":"Perturbation of Urbanization to Earth\u2019s Surface Energy Balance","volume":"126","author":"Shen","year":"2021","journal-title":"J. Geophys. Res.-Atmos."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.scs.2017.02.018","article-title":"Impact of land use change and urbanization on urban heat island in Lucknow city, Central India. A remote sensing based estimate","volume":"32","author":"Singh","year":"2017","journal-title":"Sustain. Cities Soc."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"109000","DOI":"10.1016\/j.buildenv.2022.109000","article-title":"Contribution of urban functional zones to the spatial distribution of urban thermal environment","volume":"216","author":"Chen","year":"2022","journal-title":"Build. Environ."},{"key":"ref_10","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 U.S. Communities","volume":"119","author":"Anderson","year":"2011","journal-title":"Environ. Health Perspect."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"e2022GL100689","DOI":"10.1029\/2022GL100689","article-title":"Urban-Rural Gradient in Urban Heat Island Variations Responsive to Large-Scale Human Activity Changes During Chinese New Year Holiday","volume":"49","author":"Zhan","year":"2022","journal-title":"Geophys. Res. Lett."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"102373","DOI":"10.1016\/j.scs.2020.102373","article-title":"Low impact development techniques to mitigate the impacts of climate-change-induced urban floods: Current trends, issues and challenges","volume":"62","author":"Pour","year":"2020","journal-title":"Sustain. Cities Soc."},{"key":"ref_13","unstructured":"United Nations (2022, December 27). World Urbanization Prospectus: The 2014 Revision, Available online: https:\/\/population.un.org\/wup\/Publications\/Files\/WUP2014-Report.pdf."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1016\/j.scitotenv.2016.03.027","article-title":"Seasonality in the daytime and night-time intensity of land surface temperature in a tropical city area","volume":"557","author":"Ayanlade","year":"2016","journal-title":"Sci. Total Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"153381","DOI":"10.1016\/j.scitotenv.2022.153381","article-title":"The impacts of landscape patterns spatio-temporal changes on land surface temperature from a multi-scale perspective: A case study of the Yangtze River Delta","volume":"821","author":"Xiao","year":"2022","journal-title":"Sci. Total Environ."},{"key":"ref_16","first-page":"115","article-title":"The impact of land-use changes on the spatio-temporal variation of carbon storage in the central mountainous area of Hainan Island","volume":"47","author":"Zhang","year":"2023","journal-title":"J. Nanjing For. Univ."},{"key":"ref_17","first-page":"221","article-title":"Evolutions and driving mechanisms of urban blue-green spaces in northeast China: A case study with the urban central district of Harbin City","volume":"46","author":"Song","year":"2022","journal-title":"J. Nanjing For. Univ."},{"key":"ref_18","first-page":"37","article-title":"Research on remote sensing change monitoring of urban land types based on BOVW and SVM","volume":"47","author":"Huang","year":"2023","journal-title":"J. Nanjing For. Univ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1007\/s10980-009-9402-4","article-title":"Urban heat islands and landscape heterogeneity: Linking spatiotemporal variations in surface temperatures to land-cover and socioeconomic patterns","volume":"25","author":"Buyantuyev","year":"2010","journal-title":"Landsc. Ecol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.gloplacha.2018.05.007","article-title":"Projection of land surface temperature considering the effects of future land change in the Taihu Lake Basin of China","volume":"167","author":"Feng","year":"2018","journal-title":"Glob. Planet. Chang."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.ecoenv.2015.07.004","article-title":"Statistical analysis of land surface temperature-vegetation indexes relationship through thermal remote sensing","volume":"121","author":"Kumar","year":"2015","journal-title":"Ecotoxicol. Environ. Safe."},{"key":"ref_22","first-page":"1","article-title":"Review on monitoring methods of the effects of forest changes on regional temperature based on multi-source remote sensing data","volume":"46","author":"Shen","year":"2022","journal-title":"J. Nanjing For. Univ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1038\/s43247-022-00539-x","article-title":"Surface warming in global cities is substantially more rapid than in rural background areas","volume":"3","author":"Liu","year":"2022","journal-title":"Commun. Earth Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1109\/TGRS.2016.2611566","article-title":"A Physics-Based Algorithm for the Simultaneous Retrieval of Land Surface Temperature and Emissivity From VIIRS Thermal Infrared Data","volume":"55","author":"Islam","year":"2017","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/S0034-4257(03)00007-5","article-title":"Satellite-measured growth of the urban heat island of Houston, Texas","volume":"85","author":"Streutker","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"826","DOI":"10.1016\/j.rse.2017.09.019","article-title":"Characterizing spatial and temporal trends of surface urban heat island effect in an urban main built-up area: A 12-year case study in Beijing, China","volume":"204","author":"Meng","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_27","first-page":"256","article-title":"Bi-temporal characterization of land surface temperature in relation to impervious surface area, NDVI and NDBI, using a sub-pixel image analysis","volume":"11","author":"Zhang","year":"2009","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"You, M.Z., Lai, R.W., Lin, J.Y., and Zhu, Z.S. (2021). Quantitative Analysis of a Spatial Distribution and Driving Factors of the Urban Heat Island Effect: A Case Study of Fuzhou Central Area, China. Int. J. Environ. Res. Public Health, 18.","DOI":"10.3390\/ijerph182413088"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1007\/s12665-016-5457-0","article-title":"Urbanization and its related environmental problem in Srirangam Island, Tiruchirappalli district of Tamil Nadu, India-Thermal Remote Sensing and GIS approach","volume":"75","author":"Muthamilselvan","year":"2016","journal-title":"Environ. Earth Sci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1007\/s10546-014-9980-9","article-title":"Interfacing the Urban Land-Atmosphere System Through Coupled Urban Canopy and Atmospheric Models","volume":"154","author":"Song","year":"2015","journal-title":"Bound.-Layer Meteorol."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Meng, C.L. (2020). Variational Assimilation of the Impervious Surfaces Temperature. Atmosphere, 11.","DOI":"10.3390\/atmos11040380"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"3249","DOI":"10.1016\/j.rse.2011.07.008","article-title":"Impacts of landscape structure on surface urban heat islands: A case study of Shanghai, China","volume":"115","author":"Li","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.isprsjprs.2017.01.001","article-title":"Characterizing the relationship between land use land cover change and land surface temperature","volume":"124","author":"Tran","year":"2017","journal-title":"ISPRS J. Photogramm."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"101569","DOI":"10.1016\/j.compenvurbsys.2020.101569","article-title":"Understanding the drivers of sustainable land expansion using a patch-generating land use simulation (PLUS) model: A case study in Wuhan, China","volume":"85","author":"Liang","year":"2021","journal-title":"Comput. Environ. Urban"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"108499","DOI":"10.1016\/j.ecolind.2021.108499","article-title":"Dynamic simulation of land use change and assessment of carbon storage based on climate change scenarios at the city level: A case study of Bortala, China","volume":"134","author":"Wang","year":"2022","journal-title":"Ecol. Indic."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Tian, L., Tao, Y., Fu, W.X., Li, T., Ren, F., and Li, M.Y. (2022). Dynamic Simulation of Land Use\/Cover Change and Assessment of Forest Ecosystem Carbon Storage under Climate Change Scenarios in Guangdong Province, China. Remote Sens., 14.","DOI":"10.3390\/rs14102330"},{"key":"ref_37","unstructured":"Nanjing Municipal Bureau of Statistics (2021). Nanjing Statistical Yearbook."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"3907","DOI":"10.5194\/essd-13-3907-2021","article-title":"The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019","volume":"13","author":"Yang","year":"2021","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Ermida, S.L., Soares, P., Mantas, V., Gottsche, F.M., and Trigo, I.E. (2020). Google Earth Engine Open-Source Code for Land Surface Temperature Estimation from the Landsat Series. Remote Sens., 12.","DOI":"10.3390\/rs12091471"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Kumar, L., and Mutanga, O. (2018). Google Earth Engine Applications Since Inception: Usage, Trends, and Potential. Remote Sens., 10.","DOI":"10.3390\/rs10101509"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1016\/j.rse.2017.03.026","article-title":"Cloud detection algorithm comparison and validation for operational Landsat data products","volume":"194","author":"Foga","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_43","unstructured":"U.S. Geological Survey (2015). Landsat Surface Reflectance Data, 2015\u20133034."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"e1601063","DOI":"10.1126\/sciadv.1601063","article-title":"Carbon emissions from land-use change and management in China between 1990 and 2010","volume":"2","author":"Lai","year":"2016","journal-title":"Sci. Adv."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Elvidge, C.D., Zhizhin, M., Ghosh, T., Hsu, F.C., and Taneja, J. (2021). Annual Time Series of Global VIIRS Nighttime Lights Derived from Monthly Averages: 2012 to 2019. Remote Sens., 13.","DOI":"10.3390\/rs13050922"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.agrformet.2016.11.129","article-title":"Spatiotemporal change and trend analysis of potential evapotranspiration over the Loess Plateau of China during 2011\u20132100","volume":"233","author":"Peng","year":"2017","journal-title":"Agric. Forest Meteorol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"760306","DOI":"10.3389\/fbuil.2021.760306","article-title":"Gridded GDP Projections Compatible with the Five SSPs (Shared Socioeconomic Pathways)","volume":"7","author":"Murakami","year":"2021","journal-title":"Front. Built Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1038\/s41597-020-0421-y","article-title":"Provincial and gridded population projection for China under shared socioeconomic pathways from 2010 to 2100","volume":"7","author":"Chen","year":"2020","journal-title":"Sci. Data"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1175\/1520-0477(2000)081<0313:TCMIPC>2.3.CO;2","article-title":"The Coupled Model Intercomparison Project (CMIP)","volume":"81","author":"Meehl","year":"2000","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1383","DOI":"10.1175\/BAMS-88-9-1383","article-title":"The WCRP CMIP3 multimodel dataset\u2014A new era in climate change research","volume":"88","author":"Meehl","year":"2007","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1937","DOI":"10.5194\/gmd-9-1937-2016","article-title":"Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization","volume":"9","author":"Eyring","year":"2016","journal-title":"Geosci. Model Dev."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"e2019EF001461","DOI":"10.1029\/2019EF001461","article-title":"Twenty-First Century Drought Projections in the CMIP6 Forcing Scenarios","volume":"8","author":"Cook","year":"2020","journal-title":"Earths Future"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"5425","DOI":"10.5194\/gmd-13-5425-2020","article-title":"Harmonization of global land use change and management for the period 850\u20132100 (LUH2) for CMIP6","volume":"13","author":"Hurtt","year":"2020","journal-title":"Geosci. Model Dev."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"147322","DOI":"10.1016\/j.scitotenv.2021.147322","article-title":"Can reservoir regulation mitigate future climate change induced hydrological extremes in the Lancang-Mekong River Basin?","volume":"785","author":"Yun","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_55","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_56","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1186\/s40068-017-0103-8","article-title":"Effects of soil and water conservation on vegetation cover: A remote sensing based study in the Middle Suluh River Basin, northern Ethiopia","volume":"6","author":"Hishe","year":"2017","journal-title":"Environ. Syst. Res."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"2025","DOI":"10.1080\/01431169308954018","article-title":"Effect of atmospheric absorption and surface emissivity on the determination of land surface temperature from infrared satellite data","volume":"14","author":"Ottle","year":"1993","journal-title":"Int. J. Remote Sens."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"4799","DOI":"10.3390\/rs5104799","article-title":"Global Trends in Seasonality of Normalized Difference Vegetation Index (NDVI), 1982\u20132011","volume":"5","author":"Eastman","year":"2013","journal-title":"Remote Sens."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/0034-4257(79)90013-0","article-title":"Red and photographic infrared linear combinations for monitoring vegetation","volume":"8","author":"Tucker","year":"1979","journal-title":"Remote Sens. Environ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1038\/s43017-022-00298-5","article-title":"Optical vegetation indices for monitoring terrestrial ecosystems globally","volume":"3","author":"Zeng","year":"2022","journal-title":"Nat. Rev. Earth Environ."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1080\/01431160304987","article-title":"Use of normalized difference built-up index in automatically mapping urban areas from TM imagery","volume":"24","author":"Zha","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1080\/2150704X.2013.763297","article-title":"Improved NDBI differencing algorithm for built-up regions change detection from remote-sensing data: An automated approach","volume":"4","author":"Varshney","year":"2013","journal-title":"Remote Sens. Lett."},{"key":"ref_63","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_64","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.rse.2013.08.029","article-title":"Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery","volume":"140","author":"Feyisa","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"552","DOI":"10.1016\/j.rse.2009.10.009","article-title":"Wetland monitoring using classification trees and SPOT-5 seasonal time series","volume":"114","author":"Davranche","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"5767","DOI":"10.1080\/01431160802060912","article-title":"Modelling spatial-temporal change of Poyang Lake using multitemporal Landsat imagery","volume":"29","author":"Hui","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"1602","DOI":"10.1016\/j.rse.2010.02.014","article-title":"Ecological assessment of Phragmites australis wetlands using multi-season SPOT-5 scenes","volume":"114","author":"Poulin","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"4026","DOI":"10.3390\/rs70404026","article-title":"Evaluating Multispectral Images and Vegetation Indices for Precision Farming Applications from UAV Images","volume":"7","author":"Candiago","year":"2015","journal-title":"Remote Sens."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/0034-4257(88)90106-X","article-title":"A soil-adjusted vegetation index (SAVI)","volume":"25","author":"Huete","year":"1988","journal-title":"Remote Sens. Environ."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1080\/01431161.2014.995274","article-title":"Comparison of tasselled cap transformations based on the selective bands of Landsat 8 OLI TOA reflectance images","volume":"36","author":"Liu","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/0034-4257(85)90102-6","article-title":"A TM Tasseled Cap equivalent transformation for reflectance factor data","volume":"17","author":"Crist","year":"1985","journal-title":"Remote Sens. Environ."},{"key":"ref_72","unstructured":"Unger, J., G\u00e1l, T., Rakonczai, J., Mucsi, L., Szatm\u00e1ri, J., Tobak, Z., Van Leeuwen, B., and Fiala, K. (2009, January 17). Air temperature versus surface temperature in urban environmen. Proceedings of the Seventh International Conference on Urban Climate, Yokohama, Japan."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"107936","DOI":"10.1016\/j.ecolind.2021.107936","article-title":"Coupled SSPs-RCPs scenarios to project the future dynamic variations of water-soil-carbon-biodiversity services in Central Asia","volume":"129","author":"Li","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Zhai, H., Lv, C.Q., Liu, W.Z., Yang, C., Fan, D.S., Wang, Z.K., and Guan, Q.F. (2021). Understanding Spatio-Temporal Patterns of Land Use\/Land Cover Change under Urbanization in Wuhan, China, 2000\u20132019. Remote Sens., 13.","DOI":"10.3390\/rs13163331"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1007\/s10113-011-0272-3","article-title":"Modeling spatio-temporal change patterns of forest cover: A case study from the Himalayan foothills (India)","volume":"12","author":"Munsi","year":"2012","journal-title":"Reg. Environ. Chang."},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"Rahman, M.T., Aldosary, A.S., and Mortoja, M.G. (2017). Modeling Future Land Cover Changes and Their Effects on the Land Surface Temperatures in the Saudi Arabian Eastern Coastal City of Dammam. Land, 6.","DOI":"10.3390\/land6020036"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"3421","DOI":"10.1080\/01431161.2018.1547448","article-title":"Analysis of remotely-sensed ecological indexes\u2019 influence on urban thermal environment dynamic using an integrated ecological index: A case study of Xi\u2019an, China","volume":"40","author":"Zhu","year":"2019","journal-title":"Int. J. Remote Sens."},{"key":"ref_78","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_79","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1002\/wics.51","article-title":"Partial least squares regression and projection on latent structure regression (PLS Regression)","volume":"2","author":"Abdi","year":"2010","journal-title":"Wiley Interdiscip. Rev. Comput. Stat."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"1613","DOI":"10.1175\/JCLI-D-14-00111.1","article-title":"Dynamical Adjustment of the Northern Hemisphere Surface Air Temperature Field: Methodology and Application to Observations","volume":"28","author":"Smoliak","year":"2015","journal-title":"J. Clim."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"108589","DOI":"10.1016\/j.ecolind.2022.108589","article-title":"Dynamics of the alpine timberline and its response to climate change in the Hengduan mountains over the period 1985\u20132015","volume":"135","author":"Tian","year":"2022","journal-title":"Ecol. Indic."},{"key":"ref_82","unstructured":"Hulley, G., and Hook, S. (2018). VIIRS\/NPP Land Surface Temperature and Emissivity Daily L3 Global 1 km SIN Grid Day V001."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1016\/j.scs.2016.06.018","article-title":"Spatial and temporal variations of urban heat island effect and the effect of percentage impervious surface area and elevation on land surface temperature: Study of Chandigarh city, India","volume":"26","author":"Mathew","year":"2016","journal-title":"Sustain. Cities Soc."},{"key":"ref_84","first-page":"100299","article-title":"Exploring temperature indices by deriving relationship between land surface temperature and urban landscape","volume":"18","author":"Nimish","year":"2020","journal-title":"Remote Sens. Appl."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.isprsjprs.2013.08.010","article-title":"Diurnal and seasonal impacts of urbanization on the urban thermal environment: A case study of Beijing using MODIS data","volume":"85","author":"Qiao","year":"2013","journal-title":"ISPRS J. Photogramm."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"1831","DOI":"10.1007\/s12524-019-01023-4","article-title":"Impacts of Large-Area Impervious Surfaces on Regional Land Surface Temperature in the Great Pearl River Delta, China","volume":"47","author":"Ma","year":"2019","journal-title":"J. Indian Soc. Remote"},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"103722","DOI":"10.1016\/j.scs.2022.103722","article-title":"The dominant factors and influence of urban characteristics on land surface temperature using random forest algorithm","volume":"79","author":"Wang","year":"2022","journal-title":"Sustain. Cities Soc."},{"key":"ref_88","first-page":"41","article-title":"Comparative study on spatial distributions and influencing factors of national forest cities and national garden cities","volume":"46","author":"Zhang","year":"2022","journal-title":"J. Nanjing For. Univ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/11\/2914\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:48:16Z","timestamp":1760125696000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/11\/2914"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,2]]},"references-count":88,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2023,6]]}},"alternative-id":["rs15112914"],"URL":"https:\/\/doi.org\/10.3390\/rs15112914","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6,2]]}}}