{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T15:40:16Z","timestamp":1726242016415},"reference-count":136,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2021,12,2]],"date-time":"2021-12-02T00:00:00Z","timestamp":1638403200000},"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":"Urban trees and forests provide multiple ecosystem services (ES), including temperature regulation, carbon sequestration, and biodiversity. Interest in ES has increased amongst policymakers, scientists, and citizens given the extent and growth of urbanized areas globally. However, the methods and techniques used to properly assess biodiversity and ES provided by vegetation in urban environments, at large scales, are insufficient. Individual tree identification and characterization are some of the most critical issues used to evaluate urban biodiversity and ES, given the complex spatial distribution of vegetation in urban areas and the scarcity or complete lack of systematized urban tree inventories at large scales, e.g., at the regional or national levels. This often limits our knowledge on their contributions toward shaping biodiversity and ES in urban areas worldwide. This paper provides an analysis of the state-of-the-art studies and was carried out based on a systematic review of 48 scientific papers published during the last five years (2016\u20132020), related to urban tree and greenery characterization, remote sensing techniques for tree identification, processing methods, and data analysis to classify and segment trees. In particular, we focused on urban tree and forest characterization using remotely sensed data and identified frontiers in scientific knowledge that may be expanded with new developments in the near future. We found advantages and limitations associated with both data sources and processing methods, from which we drew recommendations for further development of tree inventory and characterization in urban forestry science. Finally, a critical discussion on the current state of the methods, as well as on the challenges and directions for future research, is presented.<\/jats:p>","DOI":"10.3390\/rs13234889","type":"journal-article","created":{"date-parts":[[2021,12,2]],"date-time":"2021-12-02T07:56:14Z","timestamp":1638431774000},"page":"4889","source":"Crossref","is-referenced-by-count":10,"title":["Remotely Sensed Tree Characterization in Urban Areas: A Review"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"http:\/\/orcid.org\/0000-0002-8790-0065","authenticated-orcid":false,"given":"Luisa","family":"Velasquez-Camacho","sequence":"first","affiliation":[{"name":"Unit of Applied Artificial Intelligence, Eurecat, Centre Tecnol\u00f2gic de Catalunya, 08005 Barcelona, Spain"},{"name":"Department of Crop and Forest Sciences, University of Lleida, 25198 Lleida, Spain"}]},{"given":"Adri\u00e1n","family":"Cardil","sequence":"additional","affiliation":[{"name":"Department of Crop and Forest Sciences, University of Lleida, 25198 Lleida, Spain"},{"name":"Joint Research Unit CTFC\u2014Agrotecnio\u2014CERCA, 25280 Solsona, Spain"},{"name":"Technosylva Inc., La Jolla, CA 92037, USA"}]},{"given":"Midhun","family":"Mohan","sequence":"additional","affiliation":[{"name":"Department of Geography, University of California-Berkeley, Berkeley, CA 94709, USA"}]},{"given":"Maddi","family":"Etxegarai","sequence":"additional","affiliation":[{"name":"Unit of Applied Artificial Intelligence, Eurecat, Centre Tecnol\u00f2gic de Catalunya, 08005 Barcelona, Spain"}]},{"given":"Gabriel","family":"Anzaldi","sequence":"additional","affiliation":[{"name":"Unit of Applied Artificial Intelligence, Eurecat, Centre Tecnol\u00f2gic de Catalunya, 08005 Barcelona, Spain"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-9738-0657","authenticated-orcid":false,"given":"Sergio","family":"de-Miguel","sequence":"additional","affiliation":[{"name":"Department of Crop and Forest Sciences, University of Lleida, 25198 Lleida, Spain"},{"name":"Joint Research Unit CTFC\u2014Agrotecnio\u2014CERCA, 25280 Solsona, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1016\/j.ufug.2015.06.006","article-title":"Assessing street-level urban greenery using Google Street View and a modified green view index","volume":"14","author":"Li","year":"2015","journal-title":"Urban For. 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