{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T10:57:11Z","timestamp":1771930631837,"version":"3.50.1"},"reference-count":42,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2023,6,14]],"date-time":"2023-06-14T00:00:00Z","timestamp":1686700800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2022YFE0119500"],"award-info":[{"award-number":["2022YFE0119500"]}]},{"name":"National Key R&amp;D Program of China","award":["22010503600"],"award-info":[{"award-number":["22010503600"]}]},{"name":"National Key R&amp;D Program of China","award":["41771372"],"award-info":[{"award-number":["41771372"]}]},{"name":"Science and Technology Commission of Shanghai Municipality, China","award":["2022YFE0119500"],"award-info":[{"award-number":["2022YFE0119500"]}]},{"name":"Science and Technology Commission of Shanghai Municipality, China","award":["22010503600"],"award-info":[{"award-number":["22010503600"]}]},{"name":"Science and Technology Commission of Shanghai Municipality, China","award":["41771372"],"award-info":[{"award-number":["41771372"]}]},{"name":"National Natural Science Foundation of China","award":["2022YFE0119500"],"award-info":[{"award-number":["2022YFE0119500"]}]},{"name":"National Natural Science Foundation of China","award":["22010503600"],"award-info":[{"award-number":["22010503600"]}]},{"name":"National Natural Science Foundation of China","award":["41771372"],"award-info":[{"award-number":["41771372"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Understanding changes in urban internal structure and land surface temperature (LST) is essential. The local climate zone (LCZ) scheme has been extensively applied to characterize urban spatial structure, which has potential for urban climate research. We combined optical imagery and synthetic aperture radar (SAR) data (Landsat-5 and PALSAR for 2008; Sentinel-2 and PALSAR-2 for 2020) to map the LCZs in Shanghai, China. The results showed that the areas of open high-rise and open mid-rise buildings significantly increased from 2008 to 2020. Then, we investigated the spatiotemporal variations in LST based on the LCZ data from 2008 to 2020 using the grid method. The mean daytime LST (obtained from Landsat-5 and Landsat-8) was higher in 2020 than in 2008 for each LCZ type in spring. The mean daytime LSTs of compact mid-rise, compact low-rise, large low-rise and heavy industry zones were higher than those of other LCZ types in spring and summer. The mean nighttime LST (obtained from ASTER) in the downtown area was higher than that in the suburbs in summer. Furthermore, the mean nighttime LST of the built types was also generally higher than that of the natural types in summer. A comparison of the mean daytime LSTs in 2008 and 2020 revealed that the expansion trend of the higher LST areas in spring and summer is consistent with the expansion areas of the mid-rise and high-rise built types.<\/jats:p>","DOI":"10.3390\/rs15123106","type":"journal-article","created":{"date-parts":[[2023,6,15]],"date-time":"2023-06-15T02:03:19Z","timestamp":1686794599000},"page":"3106","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Exploring Spatiotemporal Variations in Land Surface Temperature Based on Local Climate Zones in Shanghai from 2008 to 2020"],"prefix":"10.3390","volume":"15","author":[{"given":"Xinyan","family":"Hou","sequence":"first","affiliation":[{"name":"School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China"}]},{"given":"Xuan","family":"Xie","sequence":"additional","affiliation":[{"name":"School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0471-7135","authenticated-orcid":false,"given":"Hasi","family":"Bagan","sequence":"additional","affiliation":[{"name":"School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China"},{"name":"Regional Environment Conservation Division, National Institute for Environmental Studies, Tsukuba 305-8506, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8933-9259","authenticated-orcid":false,"given":"Chaomin","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7723-5412","authenticated-orcid":false,"given":"Qinxue","family":"Wang","sequence":"additional","affiliation":[{"name":"Regional Environment Conservation Division, National Institute for Environmental Studies, Tsukuba 305-8506, Japan"}]},{"given":"Takahiro","family":"Yoshida","sequence":"additional","affiliation":[{"name":"Center for Spatial Information Science, The University of Tokyo, Kashiwa 277-8568, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1879","DOI":"10.1175\/BAMS-D-11-00019.1","article-title":"Local Climate Zones for Urban Temperature Studies","volume":"93","author":"Stewart","year":"2012","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"867434","DOI":"10.3389\/fenvs.2022.867434","article-title":"Urban Climate Informatics: An Emerging Research Field","volume":"10","author":"Middel","year":"2022","journal-title":"Front. Environ. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"101120","DOI":"10.1016\/j.uclim.2022.101120","article-title":"The use of local climate zones in the urban environment: A systematic review of data sources, methods, and themes","volume":"42","author":"Aslam","year":"2022","journal-title":"Urban Clim."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"528","DOI":"10.1080\/10095020.2021.1892459","article-title":"Mapping and analyzing the local climate zones in China\u2019s 32 major cities using Landsat imagery based on a novel convolutional neural network","volume":"24","author":"Huang","year":"2021","journal-title":"Geo-Spat. Inf. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"3835","DOI":"10.5194\/essd-14-3835-2022","article-title":"A global map of local climate zones to support earth system modelling and urban-scale environmental science","volume":"14","author":"Demuzere","year":"2022","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"130744","DOI":"10.1016\/j.jclepro.2022.130744","article-title":"Exploring thermal comfort of urban buildings based on local climate zones","volume":"340","author":"Ren","year":"2022","journal-title":"J. Clean. Prod."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"74394","DOI":"10.1007\/s11356-022-21037-9","article-title":"Urban ventilation corridors and spatiotemporal divergence patterns of urban heat island intensity: A local climate zone perspective","volume":"29","author":"Shi","year":"2022","journal-title":"Environ. Sci. Pollut. Res."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.rse.2011.07.020","article-title":"Assessment of spectral, polarimetric, temporal, and spatial dimensions for urban and peri-urban land cover classification using Landsat and SAR data","volume":"117","author":"Zhu","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"100661","DOI":"10.1016\/j.uclim.2020.100661","article-title":"Urban land cover mapping under the Local Climate Zone scheme using Sentinel-2 and PALSAR-2 data","volume":"33","author":"La","year":"2020","journal-title":"Urban Clim."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"100451","DOI":"10.1016\/j.uclim.2019.01.005","article-title":"SUHI analysis using Local Climate Zones\u2014A comparison of 50 cities","volume":"28","author":"Bechtel","year":"2019","journal-title":"Urban Clim."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"106541","DOI":"10.1016\/j.buildenv.2019.106541","article-title":"Quantifying the cooling effect of urban vegetation by mobile traverse method: A local-scale urban heat island study in a subtropical megacity","volume":"169","author":"Yan","year":"2020","journal-title":"Build. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Chen, C., Bagan, H., Xie, X., La, Y., and Yamagata, Y. (2021). Combination of Sentinel-2 and PALSAR-2 for Local Climate Zone Classification: A Case Study of Nanchang, China. Remote Sens., 13.","DOI":"10.3390\/rs13101902"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"102877","DOI":"10.1016\/j.scs.2021.102877","article-title":"Analyses of land surface temperature (LST) variability among local climate zones (LCZs) comparing Landsat-8 and ENVI-met model data","volume":"69","author":"Cilek","year":"2021","journal-title":"Sustain. Cities Soc."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"100846","DOI":"10.1016\/j.uclim.2021.100846","article-title":"LCZ scheme for assessing Urban Heat Island intensity in a complex urban area (Beirut, Lebanon)","volume":"37","author":"Zaarour","year":"2021","journal-title":"Urban Clim."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"113573","DOI":"10.1016\/j.rse.2023.113573","article-title":"Mapping local climate zones for cities: A large review","volume":"292","author":"Huang","year":"2023","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"103989","DOI":"10.1016\/j.landurbplan.2020.103989","article-title":"Evidence of urban heat island impacts on the vegetation growing season length in a tropical city","volume":"206","author":"Kabano","year":"2021","journal-title":"Landsc. Urban Plan."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"106666","DOI":"10.1016\/j.eiar.2021.106666","article-title":"The spatiotemporal dynamics of urbanisation and local climate: A case study of Islamabad, Pakistan","volume":"91","author":"Aslam","year":"2021","journal-title":"Environ. Impact Assess. Rev."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"103798","DOI":"10.1016\/j.scs.2022.103798","article-title":"The role of blue green infrastructure in the urban thermal environment across seasons and local climate zones in East Africa","volume":"80","author":"Li","year":"2022","journal-title":"Sustain. Cities Soc."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.uclim.2012.10.008","article-title":"Urbanization and its environmental effects in Shanghai, China","volume":"2","author":"Cui","year":"2012","journal-title":"Urban Clim."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3961","DOI":"10.1007\/s12517-013-1053-8","article-title":"Monitoring of urban heat island in Shanghai, China, from 1981 to 2010 with satellite data","volume":"7","author":"Li","year":"2014","journal-title":"Arab. J. Geosci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"783","DOI":"10.1007\/s00477-012-0623-8","article-title":"Economic development, urban expansion, and sustainable development in Shanghai","volume":"28","author":"Yue","year":"2014","journal-title":"Stoch. Environ. Res. Risk Assess."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"115775","DOI":"10.1016\/j.envpol.2020.115775","article-title":"Relationship between summertime concurring PM2.5 and O3 pollution and boundary layer height differs between Beijing and Shanghai, China","volume":"268","author":"Miao","year":"2021","journal-title":"Environ. Pollut."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.habitatint.2004.02.005","article-title":"Metropolitan spatial dynamics: Shanghai","volume":"30","author":"Walcott","year":"2006","journal-title":"Habitat Int."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Frazier, M.W. (2019). The Power of Place Contentious Politics in Twentieth-Century Shanghai and Bombay, Cambridge University Press. [1st ed.].","DOI":"10.1017\/9781108698450"},{"key":"ref_25","first-page":"24","article-title":"Random forest in remote sensing: A review of applications and future directions","volume":"114","author":"Belgiu","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_26","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_27","doi-asserted-by":"crossref","first-page":"2674","DOI":"10.1109\/TGRS.2003.818464","article-title":"Revised Landsat-5 TM radiometric calibration procedures and postcalibration dynamic ranges","volume":"41","author":"Chander","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","first-page":"28\u201332, 36, 41","article-title":"The estimation of land surface emissivity for Landsat TM6","volume":"16","author":"Qin","year":"2004","journal-title":"Remote Sens. Land Res."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1016\/j.isprsjprs.2019.11.018","article-title":"Remote sensing algorithms for estimation of fractional vegetation cover using pure vegetation index values: A review","volume":"159","author":"Gao","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1080\/15481603.2015.1072400","article-title":"Analysis of urban growth and estimating population density using satellite images of nighttime lights and land-use and population data","volume":"52","author":"Bagan","year":"2015","journal-title":"GIScience Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1111\/j.1538-4632.1992.tb00261.x","article-title":"The analysis of spatial association by use of distance statistics","volume":"24","author":"Getis","year":"1992","journal-title":"Geog. Anal."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1111\/j.1538-4632.1995.tb00338.x","article-title":"Local indicators of spatial association\u2014LISA","volume":"27","author":"Anselin","year":"1995","journal-title":"Geogr. Anal."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1080\/13574809.2011.552705","article-title":"Shaping Lujiazui: The formation and building of the CBD in Pudong, Shanghai","volume":"16","author":"Xue","year":"2011","journal-title":"J. Urban Des."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1007\/s11355-010-0147-7","article-title":"Urbanization and green space dynamics in Greater Dhaka, Bangladesh","volume":"8","author":"Byomkesh","year":"2012","journal-title":"Landsc. Ecol. Eng."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"105501","DOI":"10.1016\/j.ecolind.2019.105501","article-title":"Urban blue-green space planning based on thermal environment simulation: A case study of Shanghai, China","volume":"106","author":"Du","year":"2019","journal-title":"Ecol. Indic."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"102818","DOI":"10.1016\/j.scs.2021.102818","article-title":"Understanding land surface temperature impact factors based on local climate zones","volume":"69","author":"Yang","year":"2021","journal-title":"Sustain. Cities Soc."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"100540","DOI":"10.1016\/j.uclim.2019.100540","article-title":"Inter-local climate zone differentiation of land surface temperatures for management of urban heat in Nairobi City, Kenya","volume":"31","author":"Ochola","year":"2020","journal-title":"Urban Clim."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"100727","DOI":"10.1016\/j.uclim.2020.100727","article-title":"Investigating thermal behavior pattern (TBP) of local climatic zones (LCZs): A study on industrial cities of Asansol-Durgapur development area (ADDA), eastern India","volume":"35","author":"Choudhury","year":"2021","journal-title":"Urban Clim."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"101248","DOI":"10.1016\/j.uclim.2022.101248","article-title":"Quantitative analysis of the building-level relationship between building form and land surface temperature using airborne LiDAR and thermal infrared data","volume":"45","author":"Chen","year":"2022","journal-title":"Urban Clim."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2209970","DOI":"10.1080\/15481603.2023.2209970","article-title":"Multiscale mapping of local climate zones in Tokyo using airborne LiDAR data, GIS vectors, and Sentinel-2 imagery","volume":"60","author":"Chen","year":"2023","journal-title":"GIScience Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"103228","DOI":"10.1016\/j.scs.2021.103228","article-title":"Urban morphology detection and it\u2019s linking with land surface temperature: A case study for Tehran Metropolis, Iran","volume":"74","author":"Khoshnoodmotlagh","year":"2021","journal-title":"Sustain. Cities Soc."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"e01339","DOI":"10.1016\/j.heliyon.2019.e01339","article-title":"Urban green space cooling effect in cities","volume":"5","author":"Aram","year":"2019","journal-title":"Heliyon"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/12\/3106\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:54:36Z","timestamp":1760126076000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/12\/3106"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,14]]},"references-count":42,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2023,6]]}},"alternative-id":["rs15123106"],"URL":"https:\/\/doi.org\/10.3390\/rs15123106","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6,14]]}}}