{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T10:34:42Z","timestamp":1783766082784,"version":"3.55.0"},"reference-count":77,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2016,8,1]],"date-time":"2016-08-01T00:00:00Z","timestamp":1470009600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Urbanization often occurs in an unplanned and uneven manner, resulting in profound changes in patterns of land cover and land use. Understanding these changes is fundamental for devising environmentally responsible approaches to economic development in the rapidly urbanizing countries of the emerging world. One indicator of urbanization is built-up land cover that can be detected and quantified at scale using satellite imagery and cloud-based computational platforms. This process requires reliable and comprehensive ground-truth data for supervised classification and for validation of classification products. We present a new dataset for India, consisting of 21,030 polygons from across the country that were manually classified as \u201cbuilt-up\u201d or \u201cnot built-up,\u201d which we use for supervised image classification and detection of urban areas. As a large and geographically diverse country that has been undergoing an urban transition, India represents an ideal context to develop and test approaches for the detection of features related to urbanization. We perform the analysis in Google Earth Engine (GEE) using three types of classifiers, based on imagery from Landsat 7 and Landsat 8 as inputs. The methodology produces high-quality maps of built-up areas across space and time. Although the dataset can facilitate supervised image classification in any platform, we highlight its potential use in GEE for temporal large-scale analysis of the urbanization process. Our methodology can easily be applied to other countries and regions.<\/jats:p>","DOI":"10.3390\/rs8080634","type":"journal-article","created":{"date-parts":[[2016,8,3]],"date-time":"2016-08-03T03:47:39Z","timestamp":1470196059000},"page":"634","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":187,"title":["Detecting the Boundaries of Urban Areas in India: A Dataset for Pixel-Based Image Classification in Google Earth Engine"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7792-9510","authenticated-orcid":false,"given":"Ran","family":"Goldblatt","sequence":"first","affiliation":[{"name":"School of Global Policy and Strategy, University of California, San Diego, CA 92093, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"You","sequence":"additional","affiliation":[{"name":"Department of Economics, University of California, San Diego, CA 92093, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gordon","family":"Hanson","sequence":"additional","affiliation":[{"name":"School of Global Policy and Strategy, University of California, San Diego, CA 92093, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amit","family":"Khandelwal","sequence":"additional","affiliation":[{"name":"Columbia Business School, Columbia University, New York, NY 10027, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2016,8,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.gloenvcha.2012.10.016","article-title":"An urbanization bomb? Population growth and social disorder in cities","volume":"23","author":"Buhaug","year":"2013","journal-title":"Glob. Environ. Chang."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1154","DOI":"10.1111\/jeea.12100","article-title":"A world of cities: The causes and consequences of urbanization in poorer countries","volume":"12","author":"Glaeser","year":"2014","journal-title":"J. Eur. Econ. Assoc."},{"key":"ref_3","unstructured":"Department of Economic and Social Affairs, Population Division, United Nations (2015). World Urbanization Prospects: The 2014 Revision, United Nations."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"16083","DOI":"10.1073\/pnas.1211658109","article-title":"Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools","volume":"109","author":"Seto","year":"2012","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1016\/j.cities.2012.08.003","article-title":"Impacts of land use\/land cover change and socioeconomic development on regional ecosystem services: The case of fast-growing Hangzhou metropolitan area, China","volume":"31","author":"Wu","year":"2013","journal-title":"Cities"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"883","DOI":"10.1641\/0006-3568(2002)052[0883:UBAC]2.0.CO;2","article-title":"Urbanization, Biodiversity, and Conservation: The impacts of urbanization on native species are poorly studied, but educating a highly urbanized human population about these impacts can greatly improve species conservation in all ecosystems","volume":"52","author":"McKinney","year":"2002","journal-title":"Bioscience"},{"key":"ref_7","unstructured":"Pugh, C. (1996). Sustainability the Environment and Urbanisation, Earthscan."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/j.rse.2011.09.015","article-title":"Monitoring urbanization in mega cities from space","volume":"117","author":"Esch","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1016\/j.apgeog.2008.12.005","article-title":"Land use and land cover change in Greater Dhaka, Bangladesh: Using remote sensing to promote sustainable urbanization","volume":"29","author":"Dewan","year":"2009","journal-title":"Appl. Geogr."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"4733","DOI":"10.1080\/01431160802651967","article-title":"Analysis of urban growth pattern using remote sensing and GIS: A case study of Kolkata, India","volume":"30","author":"Bhatta","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Gaughan, A.E., Stevens, F.R., Linard, C., Jia, P., and Tatem, A.J. (2013). High resolution population distribution maps for Southeast Asia in 2010 and 2015. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0055882"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"6531","DOI":"10.1080\/01431160903121134","article-title":"Mapping urban areas on a global scale: Which of the eight maps now available is more accurate?","volume":"30","author":"Potere","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1733","DOI":"10.1016\/j.rse.2010.03.003","article-title":"Mapping global urban areas using MODIS 500-m data: New methods and datasets based on \u2018urban ecoregions\u2019","volume":"114","author":"Schneider","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Gamba, P., and Herold, M. (2009). Global Mapping of Human Settlement: Experiences, Datasets, and Prospects, CRC Press, Taylor and Francis Group.","DOI":"10.1201\/9781420083408"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Stevens, F.R., Gaughan, A.E., Linard, C., and Tatem, A.J. (2015). Disaggregating census data for population mapping using random forests with remotely-sensed and ancillary data. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0107042"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.isprsjprs.2014.07.002","article-title":"Comparing supervised and unsupervised multiresolution segmentation approaches for extracting buildings from very high resolution imagery","volume":"96","author":"Belgiu","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Jokar Arsanjani, J., Zipf, A., Mooney, P., and Helbich, M. (2015). OpenStreetMap in GIScience, Springer International Publishing.","DOI":"10.1007\/978-3-319-14280-7"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Jokar Arsanjani, J., Zipf, A., Mooney, P., and Helbich, M. (2015). OpenStreetMap in GIScience, Springer International Publishing.","DOI":"10.1007\/978-3-319-14280-7"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.apgeog.2015.12.006","article-title":"Integrating OpenStreetMap crowdsourced data and Landsat time-series imagery for rapid land use\/land cover (LULC) mapping: Case study of the Laguna de Bay area of the Philippines","volume":"67","author":"Johnson","year":"2016","journal-title":"Appl. Geogr."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1177","DOI":"10.3390\/rs3061177","article-title":"Development of a new ground truth database for global urban area mapping from a gazetteer","volume":"3","author":"Miyazaki","year":"2011","journal-title":"Remote Sens."},{"key":"ref_21","unstructured":"The dataset can be accessed online as a Google Fusion Table at: https:\/\/www.google.com\/fusiontables\/DataSource?docid=1fWY4IyYiV-BA5HsAKi2V9LdoQgsbFtKK2BoQiHb0#rows:id=1 (Note: class \u201c1\u201d = \u201cBU\u201d, class \u201c2\u201d = \u201cNBU\u201d)."},{"key":"ref_22","first-page":"29","article-title":"Urban sprawl: Metrics, dynamics and modelling using GIS","volume":"5","author":"Sudhira","year":"2004","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"775","DOI":"10.1162\/qjec.122.2.775","article-title":"Did highways cause suburbanization?","volume":"122","year":"2007","journal-title":"Q. J. Econ."},{"key":"ref_24","unstructured":"Sudhira, H.S., and Ramachandra, T.V. (2007, January 11\u201313). Characterizing urban sprawl from remote sensing data and using landscape metrics. Proceedings of the 10th International Conference on Computers in Urban Planning and Urban Management, Iguassu Falls, Brazil."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1109\/JSTARS.2010.2084072","article-title":"Monitoring urban sprawl using remote sensing and GIS techniques of a fast growing urban centre, India","volume":"4","author":"Rahman","year":"2011","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_26","unstructured":"Barnes, K.B., Morgan, J.M., Roberge, M.C., and Lowe, S. (2001). Sprawl Devlopment: Its Patterns, Consequences, and Measurement, Towson University."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1016\/j.rse.2012.06.006","article-title":"Monitoring land cover change in urban and peri-urban areas using dense time stacks of Landsat satellite data and a data mining approach","volume":"124","author":"Schneider","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_28","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_29","first-page":"26","article-title":"Monitoring and modelling of urban sprawl using remote sensing and GIS techniques","volume":"10","author":"Jat","year":"2008","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1068\/b32155","article-title":"Measuring urban sprawl: How can we deal with it?","volume":"35","author":"Frenkel","year":"2008","journal-title":"Environ. Plan. B Plan. Des."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1016\/j.landusepol.2012.07.018","article-title":"Measuring urban sprawl and its drivers in large Chinese cities: The case of Hangzhou","volume":"31","author":"Yue","year":"2013","journal-title":"Land Use Policy"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1407","DOI":"10.1016\/j.socscimed.2006.11.019","article-title":"Quantifying the urban environment: A scale measure of urbanicity outperforms the urban\u2013rural dichotomy","volume":"64","author":"Dahly","year":"2007","journal-title":"Soc. Sci. Med."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1016\/S0034-4257(03)00075-0","article-title":"The spatiotemporal form of urban growth: Measurement, analysis and modeling","volume":"86","author":"Herold","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_34","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_35","doi-asserted-by":"crossref","unstructured":"Lunetta, R.S., and Lyon, J.G. (2004). Remote Sensing and GIS Accuracy Assessment, CRC Press.","DOI":"10.1201\/9780203497586"},{"key":"ref_36","unstructured":"Whiteside, T., and Ahmad, W. (2005, January 12\u201316). A comparison of object-oriented and pixel-based classification methods for mapping land cover in northern Australia. Proceedings of the SSC2005 Spatial Intelligence, Innovation and Praxis: The National Biennial Conference of the Spatial Sciences Institute, Melbourne, Australia."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1016\/j.rse.2010.12.017","article-title":"Per-pixel vs. object-based classification of urban land cover extraction using high spatial resolution imagery","volume":"115","author":"Myint","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_38","first-page":"884","article-title":"Comparing object-based and pixel-based classifications for mapping savannas","volume":"13","author":"Whiteside","year":"2011","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_39","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_40","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_41","doi-asserted-by":"crossref","first-page":"1505","DOI":"10.1080\/01431160903571791","article-title":"Comparison of pixel-and object-based classification in land cover change mapping","volume":"32","author":"Robertson","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_42","unstructured":"Breiman, L., Friedman, J.H., Stone, C.J., and Olshen, R.A. (1984). Classification and Regression Trees, Wadsworth."},{"key":"ref_43","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_44","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/BF00994018","article-title":"Support vector networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Mach. Learn."},{"key":"ref_45","unstructured":"IASRI (2006). Study Relating to Formulating Long Term Mechanization Strategy for Each Agro-Climatic Zone\/State in India, Indian Agriculture Statistics Research Institute (IASRI). Final report."},{"key":"ref_46","unstructured":"World Bank. Available online: http:\/\/data.worldbank.org\/country\/india."},{"key":"ref_47","unstructured":"Census of India (2011). Office of Registrar General & Census commissioner, Ministry of Home Affairs, Government of India, Available online: http:\/\/censusindia.gov.in\/."},{"key":"ref_48","unstructured":"Chen, M., and Raveendran, G. (2011). Urban India 2011: Evidence, Indian Institute for Human Settlements Publications."},{"key":"ref_49","first-page":"37","article-title":"Population crunch in India: Is it urban or still rural?","volume":"103","author":"Sudhira","year":"2012","journal-title":"Curr. Sci."},{"key":"ref_50","first-page":"150","article-title":"Land use and land cover change detection through remote sensing approach: A case study of Kodaikanal taluk, Tamil Nadu","volume":"1","author":"Prakasam","year":"2010","journal-title":"Int. J. Geomat. Geosci."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.apgeog.2013.01.009","article-title":"Spatiotemporal urbanization processes in the megacity of Mumbai, India: A Markov chains-cellular automata urban growth model","volume":"40","author":"Moghadam","year":"2013","journal-title":"Appl. Geogr."},{"key":"ref_52","first-page":"329","article-title":"Insights to urban dynamics through landscape spatial pattern analysis","volume":"18","author":"Ramachandra","year":"2012","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.ijsbe.2012.05.001","article-title":"An analysis of urban growth trends in the post-economic reforms period in India","volume":"1","author":"Chadchan","year":"2012","journal-title":"Int. J. Sustain. Built Environ."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1007\/s12524-012-0248-x","article-title":"Monitoring urban landscape dynamics over Delhi (India) using remote sensing (1998\u20132011) inputs","volume":"41","author":"Sharma","year":"2013","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_55","unstructured":"Singh, P. (2006). Agro-Climatic Zonal Planning Including Agriculture Development in North Eastern India, for XI FIVE YEAR PLAN (2007\u201312)."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/00220380412331293647","article-title":"What has luck got to do with it? A regional analysis of poverty and agricultural growth in rural India","volume":"40","author":"Sen","year":"2003","journal-title":"J. Dev. Stud."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1016\/j.tree.2005.05.011","article-title":"Using the satellite-derived NDVI to assess ecological responses to environmental change","volume":"20","author":"Pettorelli","year":"2005","journal-title":"Trends Ecol. Evol."},{"key":"ref_58","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_59","unstructured":"Kohavi, R. (1995, January 20\u201325). A study of cross-validation and bootstrap for accuracy estimation and model selection. Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI\u201995), Montreal, QC, Canada."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1109\/TPAMI.2009.187","article-title":"Sensitivity analysis of k-fold cross validation in prediction error estimation","volume":"32","author":"Rodriguez","year":"2010","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1023\/A:1009752403260","article-title":"On comparing classifiers: Pitfalls to avoid and a recommended approach","volume":"1","author":"Salzberg","year":"1997","journal-title":"Data Min. Knowl. Discov."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1214\/09-SS054","article-title":"A survey of cross-validation procedures for model selection","volume":"4","author":"Arlot","year":"2010","journal-title":"Stat. Surv."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Liu, L., and \u00d6zsu, M.T. (2009). Encyclopedia of Database Systems, Springer US.","DOI":"10.1007\/978-0-387-39940-9"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Blum, A., Kalai, A., and Langford, J. (1999, January 7\u20139). Beating the hold-out: Bounds for k-fold and progressive cross-validation. Proceedings of the 12th Annual Conference on Computational Learning Theory, Santa Cruz, CA, USA.","DOI":"10.1145\/307400.307439"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1023\/A:1007613918580","article-title":"The effect of instance-space partition on significance","volume":"42","author":"Bradford","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_66","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. Remote Sens."},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Tatem, A.J., Noor, A.M., Von Hagen, C., Di Gregorio, A., and Hay, S.I. (2007). High resolution population maps for low income nations: Combining land cover and census in East Africa. PLoS ONE, 2.","DOI":"10.1371\/journal.pone.0001298"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"2621","DOI":"10.1080\/01431161003713036","article-title":"How much is built? Quantifying and interpreting patterns of built space from different data sources","volume":"32","author":"Orenstein","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_69","unstructured":"CIESIN, Columbia University Gridded Population of the World, Version 3 (GPWv3) Data Collection. Available online: http:\/\/sedac.ciesin.columbia.edu\/data\/collection\/gpw-v3."},{"key":"ref_70","first-page":"199","article-title":"Multitemporal settlement and population mapping from Landsat using Google Earth Engine","volume":"35","author":"Patel","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_71","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_72","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.isprsjprs.2012.04.001","article-title":"Comparison of support vector machine, neural network, and CART algorithms for the land-cover classification using limited training data points","volume":"70","author":"Shao","year":"2012","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"2912","DOI":"10.3390\/rs6042912","article-title":"Performance evaluation of machine learning algorithms for urban pattern recognition from multi-spectral satellite images","volume":"6","author":"Wieland","year":"2014","journal-title":"Remote Sens."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Xie, M., Jean, N., Burke, M., Lobell, D., and Ermon, S. (arXiv Preprint, 2015). Transfer learning from deep features for remote sensing and poverty mapping, arXiv Preprint.","DOI":"10.1609\/aaai.v30i1.9906"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"3710","DOI":"10.1109\/JSTARS.2015.2398032","article-title":"Scaling up to national\/regional urban extent mapping using Landsat data","volume":"8","author":"Trianni","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1126\/science.1244693","article-title":"High-resolution global maps of 21st-century forest cover change","volume":"342","author":"Hansen","year":"2013","journal-title":"Science"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"153","DOI":"10.3390\/rs70100153","article-title":"Comparing machine learning classifiers for object-based land cover classification using very high resolution imagery","volume":"7","author":"Qian","year":"2015","journal-title":"Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/8\/634\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:27:31Z","timestamp":1760210851000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/8\/634"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,8,1]]},"references-count":77,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2016,8]]}},"alternative-id":["rs8080634"],"URL":"https:\/\/doi.org\/10.3390\/rs8080634","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,8,1]]}}}