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The method is automatic, global and uses data sets with enough duration to establish trends. Validation using ground truth from Landsat-8 OLI images revealed an overall accuracy ranging from 60% to 95%. Thus, this approach is capable of describing spatial distributions and giving detailed information of urban extents. We demonstrate the method with examples from Brisbane, Australia, Melbourne, Australia, and Beijing, China. The new method meets the criteria for studying overall trends in urban emissions.<\/jats:p>","DOI":"10.3390\/rs11242969","type":"journal-article","created":{"date-parts":[[2019,12,12]],"date-time":"2019-12-12T03:20:16Z","timestamp":1576120816000},"page":"2969","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Combining Measurements of Built-up Area, Nighttime Light, and Travel Time Distance for Detecting Changes in Urban Boundaries: Introducing the BUNTUS Algorithm"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4106-8410","authenticated-orcid":false,"given":"Muhammad","family":"Luqman","sequence":"first","affiliation":[{"name":"School of Earth Sciences, University of Melbourne, 3000 Melbourne, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7707-6298","authenticated-orcid":false,"given":"Peter J.","family":"Rayner","sequence":"additional","affiliation":[{"name":"School of Earth Sciences, University of Melbourne, 3000 Melbourne, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9218-7164","authenticated-orcid":false,"given":"Kevin R.","family":"Gurney","sequence":"additional","affiliation":[{"name":"School of Informatics, Computing and Cyber Systems, Northern Arizona University, Flagstaff, AZ 86011, USA"}]}],"member":"1968","published-online":{"date-parts":[[2019,12,11]]},"reference":[{"key":"ref_1","unstructured":"United Nations (2018, June 13). 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