{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T09:37:32Z","timestamp":1780047452829,"version":"3.53.1"},"reference-count":40,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2013,3,13]],"date-time":"2013-03-13T00:00:00Z","timestamp":1363132800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>We assessed the potential of multi-spectral GeoEye imagery for biodiversity assessment in an urban context in Bangalore, India. Twenty one grids of 150 by 150 m were randomly located in the city center and all tree species within these grids mapped in the field. The six most common species, collectively representing 43% of the total trees sampled, were selected for mapping using pixel-based and object-based approaches.  All pairs of species were separable based on spectral reflectance values in at least one band, with Peltophorum pterocarpum being most distinct from other species. Object-based approaches were consistently superior to pixel-based methods, which were particularly low in accuracy for tree species with small canopy sizes, such as Cocos nucifera and Roystonea regia. There was a strong and significant correlation between the number of trees determined on the ground and from object-based classification. Overall, object-based approaches appear capable of discriminating the six most common species in a challenging urban environment, with substantial heterogeneity of tree canopy sizes.<\/jats:p>","DOI":"10.3390\/ijgi2010220","type":"journal-article","created":{"date-parts":[[2013,3,13]],"date-time":"2013-03-13T12:14:49Z","timestamp":1363176889000},"page":"220-236","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":49,"title":["Mapping Urban Tree Species Using Very High Resolution Satellite Imagery: Comparing Pixel-Based and Object-Based Approaches"],"prefix":"10.3390","volume":"2","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6999-650X","authenticated-orcid":false,"given":"Shivani","family":"Agarwal","sequence":"first","affiliation":[{"name":"Ashoka Trust for Research in Ecology and the Environment, Royal Enclave, Srirampura,  Jakkur P.O., Bangalore 560064, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lionel","family":"Vailshery","sequence":"additional","affiliation":[{"name":"Ashoka Trust for Research in Ecology and the Environment, Royal Enclave, Srirampura,  Jakkur P.O., Bangalore 560064, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Madhumitha","family":"Jaganmohan","sequence":"additional","affiliation":[{"name":"Ashoka Trust for Research in Ecology and the Environment, Royal Enclave, Srirampura,  Jakkur P.O., Bangalore 560064, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harini","family":"Nagendra","sequence":"additional","affiliation":[{"name":"Ashoka Trust for Research in Ecology and the Environment, Royal Enclave, Srirampura,  Jakkur P.O., Bangalore 560064, India"},{"name":"Centre for the Study of Institutions, Population and Environmental Change (CIPEC),  Indiana University, 408 North Indiana Avenue, Bloomington, IN 47408, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2013,3,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2377","DOI":"10.1080\/01431160117096","article-title":"Using remote sensing to assess biodiversity","volume":"22","author":"Nagendra","year":"2001","journal-title":"Int. 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