{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T08:41:04Z","timestamp":1768725664595,"version":"3.49.0"},"reference-count":47,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2021,2,17]],"date-time":"2021-02-17T00:00:00Z","timestamp":1613520000000},"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":"<jats:p>Dense time series of stripmap RADARSAT-2 data acquired in the Multilook Fine mode were used for detecting and mapping the extent of selective logging operations in the tropical forest area in the northern part of the Republic of the Congo. Due to limited radiometric sensitivity to forest biomass variation at C-band, basic multitemporal change detection approach was supplemented by spatial texture analysis to separate disturbed forest from intact. The developed technique primarily uses multi-temporal aggregation of orthorectified synthetic aperture radar (SAR) imagery that are acquired before and after the logging operations. The actual change analysis is based on textural features of the log-ratio image calculated using two SAR temporal composites compiled of SAR scenes acquired before and after the logging operations. Multitemporal aggregation and filtering of SAR scenes decreased speckle and made the extracted textural features more prominent. The overall detection accuracy was around 80%, with some underestimation of the area of forest disturbance compared to reference based on optical data. The user\u2019s accuracy for disturbed forest varied from 76.7% to 94.9% depending on the accuracy assessment approach. We conclude that change detection utilizing RADARSAT-2 time series represents a useful instrument to locate areas of selective logging in tropical forests.<\/jats:p>","DOI":"10.3390\/rs13040740","type":"journal-article","created":{"date-parts":[[2021,2,17]],"date-time":"2021-02-17T21:35:42Z","timestamp":1613597742000},"page":"740","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Mapping Forest Disturbance Due to Selective Logging in the Congo Basin with RADARSAT-2 Time Series"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8576-404X","authenticated-orcid":false,"given":"Oleg","family":"Antropov","sequence":"first","affiliation":[{"name":"VTT Technical Research Centre of Finland, P.O. Box 1000, 00076 Espoo, Finland"}]},{"given":"Yrj\u00f6","family":"Rauste","sequence":"additional","affiliation":[{"name":"VTT Technical Research Centre of Finland, P.O. Box 1000, 00076 Espoo, Finland"}]},{"given":"Jaan","family":"Praks","sequence":"additional","affiliation":[{"name":"Department of Electronics and Nanoengineering, Aalto University, P.O. Box 11000, 00076 Aalto, Finland"}]},{"given":"Frank Martin","family":"Seifert","sequence":"additional","affiliation":[{"name":"European Space Agency, ESA-ESRIN, Largo Galileo Galilei 1, 00044 Frascati, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1446-010X","authenticated-orcid":false,"given":"Tuomas","family":"H\u00e4me","sequence":"additional","affiliation":[{"name":"VTT Technical Research Centre of Finland, P.O. Box 1000, 00076 Espoo, Finland"}]}],"member":"1968","published-online":{"date-parts":[[2021,2,17]]},"reference":[{"key":"ref_1","unstructured":"Lund, H.G. (2007). What is a Degraded Forest?, Forest Information Services. White paper on forest degradation definitions prepared for FAO."},{"key":"ref_2","unstructured":"Simula, M. (2009). 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