{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T22:04:47Z","timestamp":1761948287226,"version":"build-2065373602"},"reference-count":46,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2017,9,2]],"date-time":"2017-09-02T00:00:00Z","timestamp":1504310400000},"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":["41330747"],"award-info":[{"award-number":["41330747"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Unprecedented rapid urbanization in China during the past several decades has been accompanied by extensive urban landscape renewal, which has increased the urban thermal environmental risk. However, landscape change is a sufficient but not necessary condition for land surface temperature (LST) variation. Many studies have merely highlighted the correlation between landscape pattern and LST, while neglecting to comprehensively present the spatiotemporal diversification of LST change under urban landscape renewal. Taking the main city of Shenzhen as a case study area, this study tracked the landscape renewal and LST variation for the period 1987\u20132015 using 49 Landsat images. A decision tree algorithm suitable for fast landscape type interpretation was developed to map the landscape renewal. Analytical tools that identified hot-cold spots, the gravity center, and transect of LST movement were adopted to identify LST changes. The results showed that the spatial variation of LST was not completely consistent with landscape change. The transformation from Green landscape to Grey landscape usually increased the LST within a median of 0.2 \u00b0C, while the reverse transformation did not obviously decrease the LST (the median was nearly 0 \u00b0C). The median of LST change from Blue landscape to Grey landscape was 1.0 \u00b0C, corresponding to 0.5 \u00b0C in the reverse transformation. The imbalance of LST change between the loss and gain of Green or Blue landscape indicates the importance of protecting natural space, where the benefits in terms of temperature mitigation cannot be completely substituted by reverse transformation.<\/jats:p>","DOI":"10.3390\/rs9090919","type":"journal-article","created":{"date-parts":[[2017,9,4]],"date-time":"2017-09-04T11:11:52Z","timestamp":1504523512000},"page":"919","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":43,"title":["Diversification of Land Surface Temperature Change under Urban Landscape Renewal: A Case Study in the Main City of Shenzhen, China"],"prefix":"10.3390","volume":"9","author":[{"given":"Yanxu","family":"Liu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China"}]},{"given":"Jian","family":"Peng","sequence":"additional","affiliation":[{"name":"Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China"}]},{"given":"Yanglin","family":"Wang","sequence":"additional","affiliation":[{"name":"Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China"}]}],"member":"1968","published-online":{"date-parts":[[2017,9,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1038\/509158a","article-title":"Realizing China\u2019s urban dream","volume":"509","author":"Bai","year":"2014","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"756","DOI":"10.1126\/science.1150195","article-title":"Global change and the ecology of cities","volume":"319","author":"Grimm","year":"2008","journal-title":"Science"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Bahi, H., Rhinane, H., Bensalmia, A., Fehrenbach, U., and Scherer, D. (2016). Effects of urbanization and seasonal cycle on the surface urban heat island patterns in the coastal growing cities: A case study of Casablanca, Morocco. Remote Sens., 8.","DOI":"10.3390\/rs8100829"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Shahraiyni, H.T., Sodoudi, S., El-Zafarany, A., Abou El Seoud, T., Ashraf, H., and Krone, K. (2016). A comprehensive statistical study on daytime surface urban heat island during summer in urban areas, case study: Cairo and its new towns. Remote Sens., 8.","DOI":"10.3390\/rs8080643"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Wang, C.Y., Myint, S.W., Wang, Z.H., and Song, J.Y. (2016). Spatio-temporal modeling of the urban heat island in the Phoenix metropolitan area: Land use change implications. Remote Sens., 8.","DOI":"10.3390\/rs8030185"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Deilami, K., Kamruzzaman, M., and Hayes, J.F. (2016). Correlation or causality between land cover patterns and the urban heat island effect? Evidence from Brisbane, Australia. Remote Sens., 8.","DOI":"10.3390\/rs8090716"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Haashemi, S., Weng, Q.H., Darvishi, A., and Alavipanah, S.K. (2016). Seasonal variations of the surface urban heat island in a semi-arid city. Remote Sens., 8.","DOI":"10.3390\/rs8040352"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Zhao, G.S., Dong, J.W., Liu, J.Y., Zhai, J., Cui, Y.P., He, T., and Xiao, X.M. (2017). Different patterns in daytime and nighttime thermal effects of urbanization in Beijing-Tianjin-Hebei urban agglomeration. Remote Sens., 9.","DOI":"10.3390\/rs9020121"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Geletic, J., Lehnert, M., and Dobrovolny, P. (2016). Land surface temperature differences within local climate zones, based on two central European cities. Remote Sens., 8.","DOI":"10.3390\/rs8100788"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Liao, W.L., Liu, X.P., Wang, D.G., and Sheng, Y.L. (2017). The impact of energy consumption on the surface urban heat island in China\u2019s 32 major cities. Remote Sens., 9.","DOI":"10.3390\/rs9030250"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"522","DOI":"10.1016\/j.jenvman.2017.03.095","article-title":"The urban heat island effect, its causes, and mitigation, with reference to the thermal properties of asphalt concrete","volume":"197","author":"Mohajerani","year":"2017","journal-title":"J. Environ. Manag."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1007\/s10980-013-9950-5","article-title":"Relationships between land cover and the surface urban heat island: Seasonal variability and effects of spatial and thematic resolution of land cover data on predicting land surface temperatures","volume":"29","author":"Zhou","year":"2014","journal-title":"Landsc. Ecol."},{"key":"ref_13","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_14","doi-asserted-by":"crossref","first-page":"887","DOI":"10.1007\/s10980-012-9731-6","article-title":"Spatial pattern of greenspace affects land surface temperature: Evidence from the heavily urbanized beijing metropolitan area, China","volume":"27","author":"Li","year":"2012","journal-title":"Landsc. Ecol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"763","DOI":"10.1007\/s10980-016-0484-5","article-title":"Urban expansion and local land-cover change both significantly contribute to urban warming, but their relative importance changes over time","volume":"32","author":"Hu","year":"2017","journal-title":"Landsc. Ecol."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Cheng, X.Y., Wei, B.S., Chen, G.J., Li, J.X., and Song, C.H. (2015). Influence of park size and its surrounding urban landscape patterns on the park cooling effect. J. Urban Plan. Dev., 141.","DOI":"10.1061\/(ASCE)UP.1943-5444.0000256"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"424","DOI":"10.1016\/j.ecolind.2014.05.002","article-title":"How many metrics are required to identify the effects of the landscape pattern on land surface temperature?","volume":"45","author":"Chen","year":"2014","journal-title":"Ecol. Indic."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.buildenv.2013.04.001","article-title":"Assessing the stability of annual temperatures for different urban functional zones","volume":"65","author":"Sun","year":"2013","journal-title":"Build. Environ."},{"key":"ref_19","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_20","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.ecoser.2016.11.011","article-title":"Effects of green space dynamics on urban heat islands: Mitigation and diversification","volume":"23","author":"Sun","year":"2017","journal-title":"Ecosyst. Serv."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Yu, W.J., and Zhou, W.Q. (2017). The spatiotemporal pattern of urban expansion in China: A comparison study of three urban megaregions. Remote Sens., 9.","DOI":"10.3390\/rs9010045"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2365","DOI":"10.1007\/s12665-012-1918-2","article-title":"Impervious surface impact on water quality in the process of rapid urbanization in Shenzhen, China","volume":"68","author":"Liu","year":"2013","journal-title":"Environ. Earth Sci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1007\/s11252-013-0325-0","article-title":"Assessment of landscape patterns affecting land surface temperature in different biophysical gradients in Shenzhen, China","volume":"16","author":"Xie","year":"2013","journal-title":"Urban Ecosyst."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.landurbplan.2015.06.007","article-title":"Linking ecosystem services and landscape patterns to assess urban ecosystem health: A case study in Shenzhen city, China","volume":"143","author":"Peng","year":"2015","journal-title":"Landsc. Urban Plan."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1016\/j.landurbplan.2014.01.025","article-title":"Assessing urban environmental resources and services of Shenzhen, China: A landscape-based approach for urban planning and sustainability","volume":"125","author":"Shi","year":"2014","journal-title":"Landsc. Urban Plan."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"888","DOI":"10.1109\/TGRS.1985.289474","article-title":"Multitemporal dimensionality of images of normalized difference vegetation index at continental scales","volume":"23","author":"Townshend","year":"1985","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_27","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_28","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1016\/S0034-4257(01)00318-2","article-title":"Detection of forest harvest type using multiple dates of Landsat TM imagery","volume":"80","author":"Wilson","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_29","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_30","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.rse.2012.09.009","article-title":"Bci: A biophysical composition index for remote sensing of urban environments","volume":"127","author":"Deng","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.rse.2016.03.031","article-title":"Continuous monitoring of coastline dynamics in western Florida with a 30-year time series of landsat imagery","volume":"179","author":"Li","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/j.rse.2015.12.022","article-title":"Remote sensing of the surface urban heat island and land architecture in Phoenix, Arizona: Combined effects of land composition and configuration and cadastral-demographic-economic factors","volume":"174","author":"Li","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"893","DOI":"10.1016\/j.rse.2009.01.007","article-title":"Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors","volume":"113","author":"Chander","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.rse.2015.11.005","article-title":"Long-term and fine-scale satellite monitoring of the urban heat island effect by the fusion of multi-temporal and multi-sensor remote sensed data: A 26-year case study of the city of Wuhan in China","volume":"172","author":"Shen","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1016\/S1001-0742(07)60041-2","article-title":"Spatial pattern of impervious surfaces and their impacts on land surface temperature in Beijing, China","volume":"19","author":"Xiao","year":"2007","journal-title":"J. Environ. Sci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"555","DOI":"10.14358\/PERS.69.5.555","article-title":"Fractal analysis of satellite-detected urban heat island effect","volume":"69","author":"Weng","year":"2003","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.apgeog.2016.07.007","article-title":"Spatial identification of multifunctional landscapes and associated influencing factors in the Beijing-Tianjin-Hebei region, China","volume":"74","author":"Peng","year":"2016","journal-title":"Appl. Geogr."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.habitatint.2016.12.005","article-title":"Spatial-temporal dynamics and associated driving forces of urban ecological land: A case study in Shenzhen city, China","volume":"60","author":"Peng","year":"2017","journal-title":"Habitat Int."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1016\/j.rse.2009.10.008","article-title":"Remote sensing of the urban heat island effect across biomes in the continental USA","volume":"114","author":"Imhoff","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1016\/j.scitotenv.2016.11.069","article-title":"Variation in the urban vegetation, surface temperature, air temperature nexus","volume":"579","author":"Shiflett","year":"2017","journal-title":"Sci. Total Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"925","DOI":"10.1080\/2150704X.2016.1182656","article-title":"Multi-dimensional histogram-based information capacity analysis of urban heat island effect using Landsat 8 data","volume":"7","author":"Mao","year":"2016","journal-title":"Remote Sens. Lett."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.landurbplan.2014.11.007","article-title":"Impacts of urban biophysical composition on land surface temperature in urban heat island clusters","volume":"135","author":"Guo","year":"2015","journal-title":"Landsc. Urban Plan."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1161","DOI":"10.1007\/s11252-014-0372-1","article-title":"Size matters: Vegetation patch size and surface temperature relationship in foothills cities of northwestern Argentina","volume":"17","author":"Gioia","year":"2014","journal-title":"Urban Ecosyst."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Wu, Z.F., Kong, F.H., Wang, Y.N., Sun, R.H., and Chen, L.D. (2016). The impact of greenspace on thermal comfort in a residential quarter of Beijing, China. Int. J. Environ. Res. Public Health, 13.","DOI":"10.3390\/ijerph13121217"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"7135","DOI":"10.1109\/TGRS.2016.2596290","article-title":"An integrated framework for the spatio-temporal-spectral fusion of remote sensing images","volume":"54","author":"Shen","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1080\/17538947.2013.783131","article-title":"Land-surface temperature retrieval at high spatial and temporal resolutions based on multi-sensor fusion","volume":"6","author":"Wu","year":"2013","journal-title":"Int. J. Digit. Earth"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/9\/919\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:43:59Z","timestamp":1760208239000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/9\/919"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,9,2]]},"references-count":46,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2017,9]]}},"alternative-id":["rs9090919"],"URL":"https:\/\/doi.org\/10.3390\/rs9090919","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2017,9,2]]}}}