{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T01:46:41Z","timestamp":1783043201640,"version":"3.54.6"},"reference-count":47,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2018,5,21]],"date-time":"2018-05-21T00:00:00Z","timestamp":1526860800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Science Foundation of Zhejiang Province of China","award":["LQ17D010003"],"award-info":[{"award-number":["LQ17D010003"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31172023"],"award-info":[{"award-number":["31172023"]}],"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>Administering an urban boundary (UB) is increasingly important for curbing disorderly urban land expansion. The traditionally manual digitalization is time-consuming, and it is difficult to connect UB in the urban fringe due to the fragmented urban pattern in daytime data. Nighttime light (NTL) data is a powerful tool used to map the urban extent, but both the blooming effect and the coarse spatial resolution make the urban product unable to meet the requirements of high-precision urban study. In this study, precise UB is extracted by a practical and effective method using NTL data and Landsat 8 data. Hangzhou, a megacity experiencing rapid urban sprawl, was selected to test the proposed method. Firstly, the rough UB was identified by the search mode of the concentric zones model (CZM) and the variance-based approach. Secondly, a buffer area was constructed to encompass the precise UB that is near the rough UB within a certain distance. Finally, the edge detection method was adopted to obtain the precise UB with a spatial resolution of 30 m. The experimental results show that a good performance was achieved and that it solved the largest disadvantage of the NTL data-blooming effect. The findings indicated that cities with a similar level of socio-economic status can be processed together when applied to larger-scale applications.<\/jats:p>","DOI":"10.3390\/rs10050799","type":"journal-article","created":{"date-parts":[[2018,5,22]],"date-time":"2018-05-22T04:34:03Z","timestamp":1526963643000},"page":"799","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Delineating Urban Boundaries Using Landsat 8 Multispectral Data and VIIRS Nighttime Light Data"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2011-9602","authenticated-orcid":false,"given":"Xingyu","family":"Xue","sequence":"first","affiliation":[{"name":"Institute of Applied Remote Sensing and Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhoulu","family":"Yu","sequence":"additional","affiliation":[{"name":"Institute of Applied Remote Sensing and Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaochun","family":"Zhu","sequence":"additional","affiliation":[{"name":"Institute of Applied Remote Sensing and Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8190-9969","authenticated-orcid":false,"given":"Qiming","family":"Zheng","sequence":"additional","affiliation":[{"name":"Institute of Applied Remote Sensing and Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Melanie","family":"Weston","sequence":"additional","affiliation":[{"name":"Institute of Applied Remote Sensing and Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ke","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute of Applied Remote Sensing and Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muye","family":"Gan","sequence":"additional","affiliation":[{"name":"Institute of Applied Remote Sensing and Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongwei","family":"Xu","sequence":"additional","affiliation":[{"name":"Institute of Applied Remote Sensing and Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,5,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.apgeog.2011.11.010","article-title":"The impacts of Atlanta\u2019s urban sprawl on forest cover and fragmentation","volume":"34","author":"Miller","year":"2012","journal-title":"Appl. Geogr."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2886","DOI":"10.1111\/gcb.12553","article-title":"Urban expansion dynamics and natural habitat loss in China: A multiscale landscape perspective","volume":"20","author":"He","year":"2014","journal-title":"Glob. Chang. Biol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"731","DOI":"10.1016\/j.apgeog.2010.02.002","article-title":"Urban sprawl measurement from remote sensing data","volume":"30","author":"Bhatta","year":"2010","journal-title":"Appl. Geogr."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.cities.2013.03.014","article-title":"Revisiting the urbanization curve","volume":"32","author":"Mulligan","year":"2013","journal-title":"Cities"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ecoser.2016.07.011","article-title":"Prioritising ecosystem services in Chinese rural and urban communities","volume":"21","author":"Pan","year":"2016","journal-title":"Ecosyst. Serv."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"4095","DOI":"10.1109\/JSTARS.2014.2302855","article-title":"Detecting China\u2019s urban expansion over the past three decades using nighttime light data","volume":"7","author":"Xiao","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.isprsjprs.2014.01.008","article-title":"A multi-index learning approach for classification of high-resolution remotely sensed images over urban areas","volume":"90","author":"Huang","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Goldblatt, R., You, W., Hanson, G., and Khandelwal, A.K. (2016). Detecting the boundaries of urban areas in India: A dataset for pixel-based image classification in google earth engine. Remote Sens., 8.","DOI":"10.3390\/rs8080634"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/j.rse.2011.11.020","article-title":"A comparison of pixel-based and object-based image analysis with selected machine learning algorithms for the classification of agricultural landscapes using SPOT-5 HRG imagery","volume":"118","author":"Duro","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_10","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_11","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1080\/15481603.2014.939539","article-title":"Built-up area extraction using Landsat 8 OLI imagery","volume":"51","author":"Bhatti","year":"2014","journal-title":"GIScience Remote Sens."},{"key":"ref_12","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_13","doi-asserted-by":"crossref","first-page":"1217","DOI":"10.1109\/JSTARS.2015.2399416","article-title":"Poverty Evaluation Using NPP-VIIRS Nighttime Light Composite Data at the County Level in China","volume":"8","author":"Yu","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4443","DOI":"10.1080\/01431160903277464","article-title":"Estimating energy consumption from night-time DMPS\/OLS imagery after correcting for saturation effects","volume":"31","author":"Letu","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_15","first-page":"8589","article-title":"Using luminosity data as a proxy for economic statistics","volume":"108","author":"Deville","year":"2014","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.rse.2005.02.002","article-title":"Spatial analysis of global urban extent from DMSP-OLS night lights","volume":"96","author":"Small","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1652","DOI":"10.1016\/j.cageo.2009.01.009","article-title":"A global poverty map derived from satellite data","volume":"35","author":"Elvidge","year":"2009","journal-title":"Comput. Geosci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1004","DOI":"10.1080\/17538947.2016.1168879","article-title":"Global mapping of urban built-up areas of year 2014 by combining MODIS multispectral data with VIIRS nighttime light data","volume":"9","author":"Sharma","year":"2016","journal-title":"Int. J. Digit. Earth"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2205","DOI":"10.1016\/j.rse.2009.06.001","article-title":"A SVM-based method to extract urban areas from DMSP-OLS and SPOT VGT data","volume":"113","author":"Cao","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Li, B., Ti, C., Zhao, Y., and Yan, X. (2016). Estimating soil moisture with Landsat data and its application in extracting the spatial distribution of winter flooded paddies. Remote Sens., 8.","DOI":"10.3390\/rs8010038"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"7671","DOI":"10.3390\/rs70607671","article-title":"Regional urban extent extraction using multi-sensor data and one-class classification","volume":"7","author":"Zhang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/j.compenvurbsys.2003.09.004","article-title":"Estimating population and energy consumption in Brazilian Amazonia using DMSP night-time satellite data","volume":"29","author":"Amaral","year":"2005","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1080\/01431160304982","article-title":"Validation of urban boundaries derived from global night-time satellite imagery","volume":"24","author":"Henderson","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_24","unstructured":"Li, B.-L., Ti, C.-P., and Yan, X.-Y. (2017). Estimating rice paddy areas in China using multi-temporal cloud-free NDVI imagery based on change detection. Pedosphere."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.rse.2014.03.004","article-title":"A cluster-based method to map urban area from DMSP\/OLS nightlights","volume":"147","author":"Zhou","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1080\/15481603.2016.1148832","article-title":"Use of an inside buffer method to extract the extent of urban areas from DMSP\/OLS nighttime light data in North China","volume":"53","author":"Tan","year":"2016","journal-title":"GIScience Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Kyba, C.C.M., Wagner, J.M., Kuechly, H.U., Walker, C.E., Elvidge, C.D., Falchi, F., Ruhtz, T., Fischer, J., and H\u00f6lker, F. (2013). Citizen science provides valuable data for monitoring global night sky luminance. Sci. Rep., 3.","DOI":"10.1038\/srep01835"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Ouyang, Z., Fan, P., and Chen, J. (2016). Urban Built-up Areas in Transitional Economies of Southeast Asia: Spatial Extent and Dynamics. Remote Sens., 8.","DOI":"10.3390\/rs8100819"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.rse.2012.10.022","article-title":"The Vegetation adjusted NTL Urban Index: A new approach to reduce saturation and increase variation in nighttime luminosity","volume":"129","author":"Zhang","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_30","first-page":"1","article-title":"A new method for extracting built-up urban areas using DMSP-OLS nighttime stable lights: A case study in the Pearl River Delta, southern China","volume":"1603","author":"Su","year":"2015","journal-title":"GIScience Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"13","DOI":"10.3390\/rs8070578","article-title":"Monitoring urban dynamics in the Southeast U.S.A. using time-series DMSP\/OLS nightlight imagery","volume":"8","author":"Li","year":"2016","journal-title":"Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2195","DOI":"10.3390\/rs6032195","article-title":"The delineation of paleo-shorelines in the lake manyara basin using terraSAR-X data","volume":"6","author":"Bachofer","year":"2014","journal-title":"Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"937","DOI":"10.1080\/0143116031000139890","article-title":"Automated extraction of coastline from satellite imagery by integrating Canny edge detection and locally adaptive thresholding methods","volume":"25","author":"Liu","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1109\/TPAMI.1986.4767851","article-title":"A Computational Approach to Edge Detection","volume":"PAMI-8","author":"Canny","year":"1986","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_35","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_36","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1016\/j.landurbplan.2014.01.018","article-title":"Urban ecology and sustainability: The state-of-the-science and future directions","volume":"125","author":"Wu","year":"2014","journal-title":"Landsc. Urban Plan."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Zheng, X., Wang, Y., Gan, M., Zhang, J., Teng, L., Wang, K., Shen, Z., and Zhang, L. (2016). Discrimination of settlement and industrial area using landscape metrics in rural region. Remote Sens., 8.","DOI":"10.3390\/rs8100845"},{"key":"ref_38","unstructured":"Murgante, B., Las Casas, G., Sansone, A., and Basilicata, U. (2007, January 18\u201322). A spatial rough set for locating the periurban fringe. Proceedings of the SAGEO 2007: Colloque International de G\u00e9omatique et d\u2019Analyse Spatiale, Saint-Etienne, France."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1033","DOI":"10.1080\/2150704X.2016.1209312","article-title":"On the application of a concentric zone model (CZM) for classifying and extracting urban boundaries using night-time stable light data in Urumqi of Xinjiang, China","volume":"7","author":"Ju","year":"2016","journal-title":"Remote Sens. Lett."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1109\/JSTARS.2016.2566682","article-title":"An Intensity Gradient\/Vegetation Fractional Coverage Approach to Mapping Urban Areas from DMSP\/OLS Nighttime Light Data","volume":"10","author":"Tan","year":"2017","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_41","first-page":"34","article-title":"A Review of Assessing the Accuracy of Classification of Remotely Sensed Data a Review of Assessing the Accuracy of Classifications of Remotely Sensed Data","volume":"4257","author":"Congalton","year":"1991","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1016\/j.rse.2014.11.022","article-title":"Night-time light derived estimation of spatio-temporal characteristics of urbanization dynamics using DMSP\/OLS satellite data","volume":"158","author":"Ma","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1559","DOI":"10.1177\/0042098015580899","article-title":"Individual and contextual determinants of victimisation in Brazilian urban centres: A multilevel approach","volume":"53","author":"Moura","year":"2016","journal-title":"Urban Stud."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.habitatint.2015.01.017","article-title":"Urban boundary extraction and sprawl analysis using Landsat images: A case study in Wuhan, China","volume":"47","author":"Hu","year":"2015","journal-title":"Habitat Int."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.landurbplan.2012.02.013","article-title":"Extracting the dynamics of urban expansion in China using DMSP-OLS nighttime light data from 1992 to 2008","volume":"106","author":"Liu","year":"2012","journal-title":"Landsc. Urban Plan."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2014.03.019","article-title":"A new source for high spatial resolution night time images\u2014The EROS-B commercial satellite","volume":"149","author":"Levin","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2011.12.005","article-title":"High spatial resolution night-time light images for demographic and socio-economic studies","volume":"119","author":"Levin","year":"2012","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/5\/799\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:05:13Z","timestamp":1760195113000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/5\/799"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,5,21]]},"references-count":47,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2018,5]]}},"alternative-id":["rs10050799"],"URL":"https:\/\/doi.org\/10.3390\/rs10050799","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,5,21]]}}}