{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T18:31:52Z","timestamp":1770834712588,"version":"3.50.1"},"reference-count":49,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,1,5]],"date-time":"2021-01-05T00:00:00Z","timestamp":1609804800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No. 42071309"],"award-info":[{"award-number":["No. 42071309"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the National Key R &amp; D Program of China","award":["No. 2016YFC0600501"],"award-info":[{"award-number":["No. 2016YFC0600501"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>As the capital city of China, Beijing has experienced unprecedented economic and population growth and dramatic impervious surface changes during the last few decades. An application of the classification method combining the spectral and textural features based on Random Forest was conducted to monitor the spatial and temporal changes of Beijing\u2019s impervious surfaces. This classification strategy achieved excellent performance in the impervious surface extraction in complex urban areas, as the Kappa coefficient reached 0.850. Based on this strategy, the impervious surfaces inside Beijing\u2019s sixth ring road in 1997, 2002, 2007, 2013, and 2017 were extracted. As the development of Beijing has a special regional feature, the changes of impervious surfaces within the sixth ring road were assessed. The findings are as follows: (1) the textural features can significantly improve the classification accuracy of land cover in urban areas, especially for the impervious surface with high albedo. (2) Impervious surfaces within the sixth ring road expanded dramatically from 1997 to 2017, had three expanding periods: 1997\u20132002, 2002\u20132007, and 2013\u20132017, and only shrank in 2007\u20132013. There are different possible major driving factors for each period. (3) The region between the fifth and sixth ring roads in Beijing underwent the most significant changes in the two decades. (4) The inner three regions are relatively highly urbanized areas compared to the outer two regions. Urbanization processes in the interior regions tend to be completed compared to the exterior regions.<\/jats:p>","DOI":"10.3390\/rs13010153","type":"journal-article","created":{"date-parts":[[2021,1,5]],"date-time":"2021-01-05T21:18:57Z","timestamp":1609881537000},"page":"153","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Monitoring Spatiotemporal Changes of Impervious Surfaces in Beijing City Using Random Forest Algorithm and Textural Features"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0802-5929","authenticated-orcid":false,"given":"Xuegang","family":"Dong","sequence":"first","affiliation":[{"name":"College of Geoexploration Science and Technology, Jilin University, Changchun 130026, China"},{"name":"Institute of National Development and Security Studies, Jilin University, Changchun 130026, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4598-087X","authenticated-orcid":false,"given":"Zhiguo","family":"Meng","sequence":"additional","affiliation":[{"name":"College of Geoexploration Science and Technology, Jilin University, Changchun 130026, China"},{"name":"Institute of National Development and Security Studies, Jilin University, Changchun 130026, China"},{"name":"Key Laboratory of Lunar and Deep-Space Exploration, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3093-7545","authenticated-orcid":false,"given":"Yongzhi","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Geoexploration Science and Technology, Jilin University, Changchun 130026, China"},{"name":"Institute of Integrated Information for Mineral Resources Prediction, Jilin University, Changchun 130061, China"}]},{"given":"Yuanzhi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Lunar and Deep-Space Exploration, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Haoteng","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Physics, Jilin University, Changchun 130026, China"}]},{"given":"Qingshuai","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Geoexploration Science and Technology, Jilin University, Changchun 130026, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,5]]},"reference":[{"key":"ref_1","unstructured":"United Nations, Department of Economic and Social Affairs, Population Division (2014). World Urbanization Prospects: The 2014 Revision Highlights, (ST\/ESA\/SER.A\/352), UN."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1080\/01944369608975688","article-title":"Impervious surface coverage: The emergence of a key environmental indicator","volume":"62","author":"Arnold","year":"1996","journal-title":"J. Am. Plan. Assoc."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/j.rse.2006.09.003","article-title":"Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery","volume":"106","author":"Yuan","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.jhydrol.2012.09.045","article-title":"Mapping impervious surface change from remote sensing for hydrological modeling","volume":"485","author":"Dams","year":"2013","journal-title":"J. Hydrol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1080\/17538947.2013.866173","article-title":"Methods to extract impervious surface areas from satellite images","volume":"7","author":"Lu","year":"2014","journal-title":"Int. J. Digit. Earth"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.catena.2007.05.001","article-title":"Impervious surface impacts to runoff and sediment discharge under laboratory rainfall simulation","volume":"72","author":"Pappas","year":"2008","journal-title":"Catena"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2165","DOI":"10.1080\/01431169508954549","article-title":"Exploring a V-I-S (vegetation-impervious surface-soil) model for urban ecosystem analysis through remote sensing: Comparative anatomy for cities","volume":"16","author":"Ridd","year":"1995","journal-title":"Int. J. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1080\/01431160051060200","article-title":"Appraising the anatomy and spatial growth of the Bangkok Metropolitan area using a vegetation-impervious-soil model through remote sensing","volume":"22","author":"Madhavan","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1016\/S0034-4257(02)00136-0","article-title":"Estimating impervious surface distribution by spectral mixture analysis","volume":"84","author":"Wu","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_10","first-page":"1150","article-title":"A new remote sensing index for fastly extracting impervious surface information","volume":"33","author":"Xu","year":"2008","journal-title":"Geomat. Inf. Sci. Wuhan Univ."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Shao, Z., Fu, H., Fu, P., and Yin, L. (2016). Mapping urban impervious surface by fusing optical and SAR data at the decision level. Remote Sens., 8.","DOI":"10.3390\/rs8110945"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.rse.2013.10.028","article-title":"Improving the impervious surface estimation with combined use of optical and SAR remote sensing images","volume":"141","author":"Zhang","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.isprsjprs.2011.11.002","article-title":"An assessment of the effectiveness of a random forest classifier for land-cover classification","volume":"67","author":"Ghimire","year":"2012","journal-title":"ISPRS J. Photogramm."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1016\/j.patrec.2005.08.011","article-title":"Random Forests for land cover classification","volume":"27","author":"Gislason","year":"2006","journal-title":"Pattern Recognit. Lett."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"602","DOI":"10.1080\/21642583.2014.956265","article-title":"Random Forests: From Early Developments to Recent Advancements","volume":"2","author":"Fawagreh","year":"2014","journal-title":"Syst. Sci. Control Eng."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10462-009-9124-7","article-title":"Ensemble-based classifiers","volume":"33","author":"Rokach","year":"2010","journal-title":"Artif. Intell. Rev."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1127\/0941-2948\/2006\/0130","article-title":"World map of the K\u00f6ppen-Geiger climate classification updated","volume":"15","author":"Kottek","year":"2006","journal-title":"Meteorol. Z."},{"key":"ref_19","first-page":"D02116","article-title":"Impacts of urban expansion and future green planting on summer precipitation in the Beijing metropolitan area","volume":"114","author":"Zhang","year":"2009","journal-title":"J. Geophys. Res."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1002\/cjg2.624","article-title":"Interdecadal changes of temperature in the Beijing region and its heat island effect","volume":"48","author":"Lin","year":"2005","journal-title":"Chin. J. Geophys."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Zhang, L., Gao, S., Wei, B., Li, Y., Li, H., Wang, L., and Ye, B. (2017). Effects of urbanization on rural drinking water quality in Beijing, China. Sustainability, 9.","DOI":"10.3390\/su9040461"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.rse.2011.12.003","article-title":"Random Forest classification of Mediterranean land cover using multi-seasonal imagery and multi-seasonal texture","volume":"121","author":"Atkinson","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1080\/01431168708948658","article-title":"Thematic Mapper bandpass solar exoatmospheric irradiances","volume":"8","author":"Markham","year":"1987","journal-title":"Int. J. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1109\/TGRS.1990.572937","article-title":"Evaluation of The Grey-level Co-occurrence Matrix Method for Land-cover Classification Using Spot Imagery","volume":"28","author":"Marceau","year":"1990","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1359","DOI":"10.1080\/01431169308953962","article-title":"A comparative analysis of standardised and unstandardised Principal Components Analysis in remote sensing","volume":"14","author":"Eklundh","year":"1993","journal-title":"Int. J. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2224","DOI":"10.1109\/JSTARS.2013.2279693","article-title":"(Semi-) supervised probabilistic principal component analysis for hyperspectral remote sensing image classification","volume":"7","author":"Xia","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1109\/36.3001","article-title":"A transformation for ordering multispectral data in terms of image quality with implications for noise removal","volume":"26","author":"Green","year":"1988","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1109\/TSMC.1973.4309314","article-title":"Textural features for image classification","volume":"6","author":"Haralick","year":"1973","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"786","DOI":"10.1109\/PROC.1979.11328","article-title":"Statistical and structural approaches to texture","volume":"67","author":"Haralick","year":"1979","journal-title":"Proc. IEEE"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1016\/S0098-3004(99)00118-1","article-title":"Computing geostatistical image texture for remotely sensed data classification","volume":"26","year":"2000","journal-title":"Comput. Geosci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1080\/01431161.2014.995276","article-title":"Integrating multiple texture methods and NDVI to the Random Forest classification algorithm to detect tea and hazelnut plantation areas in northeast Turkey","volume":"36","author":"Akar","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.chemolab.2004.02.005","article-title":"Image texture analysis: Methods and comparisons","volume":"72","author":"Bharati","year":"2004","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"ref_33","first-page":"272","article-title":"Random Forests and Decision Trees","volume":"9","author":"Ali","year":"2012","journal-title":"Int. J. Comput. Sci. Issues."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2564","DOI":"10.1016\/j.rse.2011.05.013","article-title":"Object-oriented mapping of landslides using Random Forests","volume":"115","author":"Stumpf","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_35","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_36","first-page":"298","article-title":"A comparison of selected classification algorithms for mapping bamboo patches in lower Gangetic plains using very high resolution WorldView 2 imagery","volume":"26","author":"Ghosh","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinform."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.isprsjprs.2016.01.011","article-title":"Random forest in remote sensing: A review of applications and future directions","volume":"114","author":"Belgiu","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_38","unstructured":"(2020, December 01). Beijing Statistical Year Book 2019, Available online: http:\/\/nj.tjj.beijing.gov.cn\/nj\/main\/2019-tjnj\/zk\/indexee.htm."},{"key":"ref_39","unstructured":"Gold, J.R., and Gold, M.M. (2016). Olympic Cities: City Agendas, Planning, and the World\u2019s Games, 1896\u20132020, Routledge. [3rd ed.]."},{"key":"ref_40","first-page":"1640","article-title":"Changes of extreme temperature events in Beijing during 1960\u20132014","volume":"35","author":"Li","year":"2015","journal-title":"Sci. Geogr. Sin."},{"key":"ref_41","unstructured":"CCTV.com (2020, December 24). Available online: http:\/\/www.cctv.com\/english\/special\/excl\/20090703\/108728.shtml."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Chao, Z., Wang, L., Che, M., and Hou, S. (2020). Effects of Different Urbanization Levels on Land Surface Temperature Change: Taking Tokyo and Shanghai for Example. Remote Sens., 12.","DOI":"10.3390\/rs12122022"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"763","DOI":"10.1007\/s10980-014-0034-y","article-title":"How much of the world\u2019s land has been urbanized, really? A hierarchical framework for avoiding confusion","volume":"29","author":"Liu","year":"2014","journal-title":"Landsc. Ecol."},{"key":"ref_44","unstructured":"China.org.cn (2020, November 27). Available online: http:\/\/www.china.org.cn\/environment\/2012-04\/02\/content_25052715.htm."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Wu, D., Gong, J., Liang, J., Sun, J., and Zhang, G. (2020). Analyzing the Influence of Urban Street Greening and Street Buildings on Summertime Air Pollution Based on Street View Image Data. ISPRS Int. J. Geo-Inf., 9.","DOI":"10.3390\/ijgi9090500"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Sun, Z., Wang, C., Guo, H., and Shang, R. (2017). A Modified Normalized Difference Impervious Surface Index (MNDISI) for Automatic Urban Mapping from Landsat Imagery. Remote Sens., 9.","DOI":"10.3390\/rs9090942"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Chang, S., Wang, Z., Mao, D., Guan, K., Jia, M., and Chen, C. (2020). Mapping the Essential Urban Land Use in Changchun by Applying Random Forest and Multi-Source Geospatial Data. Remote Sens., 12.","DOI":"10.3390\/rs12152488"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Pilant, A., Endres, K., Rosenbaum, D., and Gundersen, G. (2020). US EPA EnviroAtlas Meter-Scale Urban Land Cover (MULC): 1-m Pixel Land Cover Class Definitions and Guidance. Remote Sens., 12.","DOI":"10.3390\/rs12121909"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"111757","DOI":"10.1016\/j.rse.2020.111757","article-title":"Incorporating synthetic aperture radar and optical images to investigate the annual dynamics of anthropogenic impervious surface at large scale","volume":"242","author":"Lin","year":"2020","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/1\/153\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:07:15Z","timestamp":1760159235000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/1\/153"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,5]]},"references-count":49,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2021,1]]}},"alternative-id":["rs13010153"],"URL":"https:\/\/doi.org\/10.3390\/rs13010153","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,5]]}}}