{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T01:46:31Z","timestamp":1768009591348,"version":"3.49.0"},"reference-count":32,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2014,9,30]],"date-time":"2014-09-30T00:00:00Z","timestamp":1412035200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Detection of urban area extents by means of remotely sensed data is a difficult task, especially because of the multiple, diverse definitions of what an \u201curban area\u201d is. The models of urban areas listed in technical literature are based on the combination of spectral information with spatial patterns, possibly at different spatial resolutions. Starting from the same data set, \u201curban area\u201d extraction may thus lead to multiple outputs. If this is done in a well-structured framework, however, this may be considered as an advantage rather than an issue. This paper proposes a novel framework for urban area extent extraction from multispectral Earth Observation (EO) data. The key is to compute and combine spectral and multi-scale spatial features. By selecting the most adequate features, and combining them with proper logical rules, the approach allows matching multiple urban area models. Experimental results for different locations in Brazil and Kenya using High-Resolution (HR) data prove the usefulness and flexibility of the framework.<\/jats:p>","DOI":"10.3390\/s141018337","type":"journal-article","created":{"date-parts":[[2014,9,30]],"date-time":"2014-09-30T10:57:30Z","timestamp":1412074650000},"page":"18337-18352","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Urban Area Extent Extraction in Spaceborne HR and VHR Data Using Multi-Resolution Features"],"prefix":"10.3390","volume":"14","author":[{"given":"Gianni","family":"Iannelli","sequence":"first","affiliation":[{"name":"Department of Industrial and Information Engineering, University of Pavia, Via Ferrata 5,  Pavia 27100, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gianni","family":"Lisini","sequence":"additional","affiliation":[{"name":"Institute for Advanced Studies, Palazzo della Vittoria, Pavia 27100, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fabio","family":"Dell'Acqua","sequence":"additional","affiliation":[{"name":"Department of Industrial and Information Engineering, University of Pavia, Via Ferrata 5,  Pavia 27100, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Raul","family":"Feitosa","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Pontifical Catholic University of Rio de Janeiro,  Marqu\u00eas de S\u00e3o Vicente, 225, G\u00e1vea 22451-900, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gilson","family":"Costa","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Pontifical Catholic University of Rio de Janeiro,  Marqu\u00eas de S\u00e3o Vicente, 225, G\u00e1vea 22451-900, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paolo","family":"Gamba","sequence":"additional","affiliation":[{"name":"Department of Industrial and Information Engineering, University of Pavia, Via Ferrata 5,  Pavia 27100, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2014,9,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1962","DOI":"10.3390\/s7091962","article-title":"Global distribution and density of constructed impervious surfaces","volume":"7","author":"Elvidge","year":"2007","journal-title":"Sensors"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2184","DOI":"10.1109\/JSTARS.2012.2235410","article-title":"Fast and efficient urban extent extraction using ASAR Wide Swath Mode data","volume":"6","author":"Gamba","year":"2013","journal-title":"IEEE J. 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