{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T20:15:20Z","timestamp":1771272920372,"version":"3.50.1"},"reference-count":63,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2021,11,27]],"date-time":"2021-11-27T00:00:00Z","timestamp":1637971200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006541","name":"Comunidad de Madrid","doi-asserted-by":"publisher","award":["CM\/JIN\/2019-011"],"award-info":[{"award-number":["CM\/JIN\/2019-011"]}],"id":[{"id":"10.13039\/501100006541","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Romanian National Authority for Scientific Research and Innovation","award":["P_37_651\/105058"],"award-info":[{"award-number":["P_37_651\/105058"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This study tested the ability of Sentinel-1 C-band to separate forest from other common land use classes (i.e., urban, low vegetation and water) at two different sites. The first site is characterized by temperate forests and rough terrain while the second by tropical forest and near-flat terrain. We trained a support vector machine classifier using increasing feature sets starting from annual backscatter statistics (average, standard deviation) and adding long-term coherence (i.e., coherence estimate for two acquisitions with a large time difference), as well as short-term (six to twelve days) coherence statistics from annual time series. Classification accuracies using all feature sets was high (&gt;92% overall accuracy). For temperate forests the overall accuracy improved by up to 5% when coherence features were added: long-term coherence reduced misclassification of forest as urban, whereas short-term coherence statistics reduced the misclassification of low vegetation as forest. Classification accuracy for tropical forests showed little differences across feature sets, as the annual backscatter statistics sufficed to separate forest from low vegetation, the other dominant land cover. Our results show the importance of coherence for forest classification over rough terrain, where forest omission error was reduced up to 11%.<\/jats:p>","DOI":"10.3390\/rs13234814","type":"journal-article","created":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T01:45:02Z","timestamp":1638323102000},"page":"4814","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Assessing the Utility of Sentinel-1 Coherence Time Series for Temperate and Tropical Forest Mapping"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5444-6177","authenticated-orcid":false,"given":"Ignacio","family":"Borlaf-Mena","sequence":"first","affiliation":[{"name":"Department of Geology, Geography and Environment, University of Alcal\u00e1, Calle Colegios 2, 28801 Alcal\u00e1 de Henares, Spain"}]},{"given":"Ovidiu","family":"Badea","sequence":"additional","affiliation":[{"name":"Department of Forest Monitoring, Romanian National Institute for Research and Development in Forestry, INCDS \u201cMarin Dr\u0103cea\u201d, Bulevardul Eroilor 128, 077190 Voluntari, Romania"},{"name":"Department of Forest Engineering, Forest Management Planning and Terrestrial Measurements, Faculty of Silviculture and Forest Engineering, Transilvania University of Brasov, Ludwig van Beethoven Str. 1, 500123 Bra\u015fov, Romania"}]},{"given":"Mihai Andrei","family":"Tanase","sequence":"additional","affiliation":[{"name":"Department of Geology, Geography and Environment, University of Alcal\u00e1, Calle Colegios 2, 28801 Alcal\u00e1 de Henares, Spain"},{"name":"Department of Forest Monitoring, Romanian National Institute for Research and Development in Forestry, INCDS \u201cMarin Dr\u0103cea\u201d, Bulevardul Eroilor 128, 077190 Voluntari, Romania"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,27]]},"reference":[{"key":"ref_1","unstructured":"Food and Agriculture Organization Forest Resources Assessment (2000). 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