{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T22:40:47Z","timestamp":1767912047813,"version":"3.49.0"},"reference-count":53,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2020,12,22]],"date-time":"2020-12-22T00:00:00Z","timestamp":1608595200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002855","name":"Ministry of Science and Technology of the People's Republic of China","doi-asserted-by":"publisher","award":["2018YFB1004604"],"award-info":[{"award-number":["2018YFB1004604"]}],"id":[{"id":"10.13039\/501100002855","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Monitoring urban compositions spatially and temporally is a crucial issue for urban planning and management. Nowadays, remote sensing techniques have been widely applied for urban compositions extraction. Compared with other remote sensing techniques, spectral indices have significant advantages due to their parameter-free and easy implementation. However, existing indices cannot extract different urban compositions well, and some of them can only extract one composition with less attention to other urban compositions. In this study, based on the water- impervious surface-pervious surface (W-I-P) model, a novel urban composition index (UCI) was developed by analyzing the robust features from the global spectral samples. Additionally, a semi-empirical threshold of UCI was proposed to extract different urban compositions (water, impervious surface area and pervious surface area). Four cities of China were selected as study areas, Landsat-8 images and Google Earth images were used for quantitative analysis. Correlation analysis, separability analysis, and accuracy assessment were conducted among UCI and five other existed indices (single and multiple composition indices) at the urban and global scales. Results indicated that UCI had a stronger correlation with the ISA proportion and a higher separability between each urban composition. UCI also achieved the highest overall accuracy and Kappa coefficient in urban compositions extraction. The suggested semi-empirical threshold was also testified to be reliable and can be a reference for practical application. There is convincing evidence that UCI is a simple, efficient, and reliable index for urban compositions extraction.<\/jats:p>","DOI":"10.3390\/rs13010003","type":"journal-article","created":{"date-parts":[[2020,12,22]],"date-time":"2020-12-22T20:39:29Z","timestamp":1608669569000},"page":"3","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["A Novel Urban Composition Index Based on Water-Impervious Surface-Pervious Surface (W-I-P) Model for Urban Compositions Mapping Using Landsat Imagery"],"prefix":"10.3390","volume":"13","author":[{"given":"Lihao","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yugang","family":"Tian","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingwei","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/S0169-2046(03)00026-4","article-title":"Landscape change and the urbanization process in Europe","volume":"67","author":"Antrop","year":"2004","journal-title":"Landsc. Urban Plan."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1080\/01944369408975555","article-title":"A practical method for estimating the impact of land-use change on surface runoff, groundwater recharge and wetland hydrology","volume":"60","author":"Harbor","year":"1994","journal-title":"J. Am. Plan. Assoc."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.rse.2011.02.030","article-title":"Remote sensing of impervious surfaces in the urban areas: Requirements, methods, and trends","volume":"117","author":"Weng","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.rse.2005.09.023","article-title":"An analysis of urban thermal characteristics and associated land cover in Tampa Bay and Las Vegas using Landsat satellite data","volume":"104","author":"Xian","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"557","DOI":"10.14358\/PERS.76.5.557","article-title":"Analysis of impervious surface and its impact on urban heat environment using the normalized difference impervious surface index (NDISI)","volume":"76","author":"Xu","year":"2010","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Yan, Y., Zhang, C., Hu, Y., and Kuang, W. (2016). Urban land-cover change and its impact on the ecosystem carbon storage in a dryland city. Remote Sens., 8.","DOI":"10.3390\/rs8010006"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.rse.2012.10.025","article-title":"Urban growth of the Washington, DC\u2014Baltimore, MD metropolitan region from 1984 to 2010 by annual, Landsat-based estimates of impervious cover","volume":"129","author":"Sexton","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2015.12.027","article-title":"Characterizing the magnitude, timing and duration of urban growth from time series of Landsat-based estimates of impervious cover","volume":"175","author":"Song","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_9","first-page":"169","article-title":"Monitoring and analyzing the spatial dynamics and patterns of megacities along the Maritime Silk Road","volume":"21","author":"Yu","year":"2017","journal-title":"J. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.isprsjprs.2016.01.003","article-title":"Annual dynamics of impervious surface in the Pearl River Delta, China, from 1988 to 2013, using time series Landsat imagery","volume":"113","author":"Zhang","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.rse.2011.06.024","article-title":"Impervious surface quantification using a synthesis of artificial immune networks and decision\/regression trees from multi-sensor data","volume":"117","author":"Im","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"298","DOI":"10.1016\/j.isprsjprs.2010.10.010","article-title":"Detection of impervious surface change with multitemporal Landsat images in an urban-rural frontier","volume":"66","author":"Lu","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2089","DOI":"10.1016\/j.rse.2009.05.014","article-title":"Estimating impervious surfaces from medium spatial resolution imagery using the self-organizing map and multi-layer perceptron neural networks","volume":"113","author":"Hu","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1329","DOI":"10.14358\/PERS.76.12.1329","article-title":"High resolution impervious surface estimation","volume":"76","author":"Mohapatra","year":"2010","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"650","DOI":"10.1016\/j.apgeog.2010.01.009","article-title":"Per-pixel and object-oriented classification methods for mapping urban features using Ikonos satellite data","volume":"30","author":"Bhaskaran","year":"2010","journal-title":"Appl. Geogr."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Richards, J.A., and Richards, J. (1999). Remote Sensing Digital Image Analysis, Springer.","DOI":"10.1007\/978-3-662-03978-6"},{"key":"ref_17","first-page":"58","article-title":"Building extraction from high-resolution optical spaceborne images using the integration of support vector machine (SVM) classification, Hough transformation and perceptual grouping","volume":"34","author":"Turker","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"053501","DOI":"10.1117\/1.3539767","article-title":"Estimating urban impervious surfaces from Landsat-5 TM imagery using multilayer perceptron neural network and support vector machine","volume":"5","author":"Sun","year":"2011","journal-title":"J. Appl. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.rse.2015.07.017","article-title":"A linear dirichlet mixture model for decomposing scenes: Application to analyzing urban functional zonings","volume":"169","author":"Zhang","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1712","DOI":"10.1016\/j.rse.2009.03.018","article-title":"Hierarchical multiple endmember spectral mixture analysis (MESMA) of hyperspectral imagery for urban environments","volume":"113","author":"Franke","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/j.rse.2006.09.005","article-title":"Sub-pixel mapping of urban land cover using multiple endmember spectral mixture analysis: Manaus, Brazil","volume":"106","author":"Powell","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1016\/S0034-4257(98)00037-6","article-title":"Mapping chaparral in the Santa Monica Mountains using multiple endmember spectral mixture models","volume":"65","author":"Roberts","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2165","DOI":"10.1080\/01431169508954549","article-title":"Exploring a VIS (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_24","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.ecolind.2015.03.037","article-title":"Classification and change detection of built-up lands from Landsat-7 ETM+ and Landsat-8 OLI\/TIRS imageries: A comparative assessment of various spectral indices","volume":"56","author":"Estoque","year":"2015","journal-title":"Ecol. Indic."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1425","DOI":"10.1080\/01431169608948714","article-title":"The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features","volume":"17","author":"McFeeters","year":"1996","journal-title":"Int. J. Remote Sens."},{"key":"ref_26","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_27","first-page":"309","article-title":"Monitoring vegetation systems in the Great Plains with ERTS","volume":"351","author":"Rouse","year":"1973","journal-title":"NASA Spec. Publ."},{"key":"ref_28","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_29","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_30","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_31","doi-asserted-by":"crossref","unstructured":"Tian, Y., Chen, H., Song, Q., and Zheng, K. (2018). A novel index for impervious surface area mapping: Development and validation. Remote Sens., 10.","DOI":"10.3390\/rs10101521"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"41224","DOI":"10.1109\/ACCESS.2018.2857405","article-title":"Combinational Biophysical Composition Index (CBCI) for Effective Mapping Biophysical Composition in Urban Areas","volume":"6","author":"Zhang","year":"2018","journal-title":"IEEE Access"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"016502","DOI":"10.1117\/1.JRS.13.016502","article-title":"Enhanced normalized difference index for impervious surface area estimation at the plateau basin scale","volume":"13","author":"Chen","year":"2019","journal-title":"J. Appl. Remote Sens."},{"key":"ref_34","unstructured":"Kauth, R.J., and Thomas, G. (July, January 29). The tasselled cap\u2014A graphic description of the spectral-temporal development of agricultural crops as seen by Landsat. Proceedings of the LARS Symposia, Purdue University, West Lafayette, IN, USA."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.landurbplan.2018.07.007","article-title":"Six fundamental aspects for conceptualizing multidimensional urban form: A spatial mapping perspective","volume":"179","author":"Wentz","year":"2018","journal-title":"Landsc. Urban Plan."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1007\/s10980-016-0432-4","article-title":"Shifting concepts of urban spatial heterogeneity and their implications for sustainability","volume":"32","author":"Zhou","year":"2017","journal-title":"Landsc. Ecol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/j.buildenv.2011.07.014","article-title":"A study on the cooling effects of greening in a high-density city: An experience from Hong Kong","volume":"47","author":"Ng","year":"2012","journal-title":"Build. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"4795","DOI":"10.1080\/01431161.2014.930202","article-title":"Towards a common validation sample set for global land-cover mapping","volume":"35","author":"Zhao","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_39","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_40","doi-asserted-by":"crossref","first-page":"289","DOI":"10.32614\/RJ-2016-021","article-title":"mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture Models","volume":"8","author":"Scrucca","year":"2016","journal-title":"R J."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Kokaly, R.F., Clark, R.N., Swayze, G.A., Livo, K.E., Hoefen, T.M., Pearson, N.C., Wise, R.A., Benzel, W.M., Lowers, H.A., and Driscoll, R.L. (2017). USGS Spectral Library Version 7.","DOI":"10.3133\/ds1035"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1907","DOI":"10.1109\/TGRS.2003.815238","article-title":"Spectral resolution requirements for mapping urban areas","volume":"41","author":"Herold","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1016\/j.rse.2004.02.013","article-title":"Spectrometry for urban area remote sensing\u2014Development and analysis of a spectral library from 350 to 2400 nm","volume":"91","author":"Herold","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_44","first-page":"2193","article-title":"A spectral based recognition of the urban environment using the visible and near-infrared spectral region (0.4\u20131.1 \u00b5m). A case study over Tel-Aviv, Israel","volume":"22","author":"Levin","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","article-title":"A threshold selection method from gray-level histograms","volume":"9","author":"Otsu","year":"1979","journal-title":"IEEE Trans. Syst. ManCybern."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/0734-189X(85)90125-2","article-title":"A new method for gray-level picture thresholding using the entropy of the histogram","volume":"29","author":"Kapur","year":"1985","journal-title":"Comput. Vis. Graph. Image Process."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/0031-3203(86)90030-0","article-title":"Minimum error thresholding","volume":"19","author":"Kittler","year":"1986","journal-title":"Pattern Recognit."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1109\/TPAMI.1981.4767177","article-title":"Remote sensing: The quantitative approach","volume":"10","author":"Swain","year":"1981","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1080\/01431168708948645","article-title":"Review Article A review of multi-channel indices of class separability","volume":"8","author":"Thomas","year":"1987","journal-title":"Int. J. Remote Sens."},{"key":"ref_50","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_51","first-page":"826","article-title":"Quantifying the impact of urban area expansion on groundwater recharge and surface runoff","volume":"61","author":"Eshtawi","year":"2016","journal-title":"Hydrol. Sci. J."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2019WR026574","article-title":"Impacts of Urbanization on Watershed Water Balances Across the Conterminous United States","volume":"56","author":"Li","year":"2020","journal-title":"Water Resour. Res."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.jhydrol.2015.06.028","article-title":"Hydrological modelling of urbanized catchments: A review and future directions","volume":"529","author":"Salvadore","year":"2015","journal-title":"J. Hydrol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/1\/3\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:48:18Z","timestamp":1760179698000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/1\/3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,22]]},"references-count":53,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2021,1]]}},"alternative-id":["rs13010003"],"URL":"https:\/\/doi.org\/10.3390\/rs13010003","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,12,22]]}}}