{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T19:12:30Z","timestamp":1769281950054,"version":"3.49.0"},"reference-count":52,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2019,12,13]],"date-time":"2019-12-13T00:00:00Z","timestamp":1576195200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000844","name":"European Space Agency","doi-asserted-by":"publisher","award":["4000116151\/15\/I-NB"],"award-info":[{"award-number":["4000116151\/15\/I-NB"]}],"id":[{"id":"10.13039\/501100000844","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The European Space Agency\u2019s (ESA) \u201cSAR for REDD\u201d project aims to support complementing optical remote sensing capacities in Africa with synthetic aperture radar (SAR) for Reducing Emissions from Deforestation and Forest Degradation (REDD). The aim of this study is to assess and compare Sentinel-1 C-band, ALOS-2 PALSAR-2 L-band and combined C\/L-band SAR-based land cover mapping over a large tropical area in the Democratic Republic of Congo (DRC). The overall approach is to benefit from multi-temporal observations acquired from 2015 to 2017 to extract statistical parameters and seasonality of backscatters to improve forest land cover (FLC) classification. We investigate whether and to what extent the denser time series of C- band SAR can compensate for the L-band\u2019s deeper vegetation penetration depth and known better FLC mapping performance. The supervised classification differentiates into forest, inundated forest, woody savannah, dry and wet grassland, and river swamps. Several feature combinations of statistical parameters from both, single and multi-frequency observations in a multivariate maximum-likelihood classification are compared. The FLC maps are reclassified into forest, savannah, and grassland (FSG) and validated with a systematic sampling grid of manual interpretations of very-high-resolution optical satellite data. Using the temporal variability of the dual-polarized backscatters, in the form of either wet\/dry seasonal averages or using the statistical variance, in addition to the average backscatter, increased the classification accuracies by 4\u20135 percent points and 1\u20132 percent points for C- and L-band, respectively. For the FSG validation overall accuracies of 84.4%, 89.1%, and 90.0% were achieved for single frequency C- and L-band, and C\/L-band combined, respectively. The resulting forest\/non-forest (FNF) maps with accuracies of 90.3%, 92.2%, and 93.3%, respectively, are then compared to the Landsat-based Global Forest Change program\u2019s and JAXA\u2019s ALOS-1\/2 based global FNF maps.<\/jats:p>","DOI":"10.3390\/rs11242999","type":"journal-article","created":{"date-parts":[[2019,12,13]],"date-time":"2019-12-13T11:27:22Z","timestamp":1576236442000},"page":"2999","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Multi-Temporal and Multi-Frequency SAR Analysis for Forest Land Cover Mapping of the Mai-Ndombe District (Democratic Republic of Congo)"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9681-9269","authenticated-orcid":false,"given":"J\u00f6rg","family":"Haarpaintner","sequence":"first","affiliation":[{"name":"NORCE\u2014Norwegian Research Centre AS, NORCE Climate, P.O. Box 6434, N-9294 Troms\u00f8, Norway"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4336-6294","authenticated-orcid":false,"given":"Heidi","family":"Hindberg","sequence":"additional","affiliation":[{"name":"NORCE\u2014Norwegian Research Centre AS, NORCE Technology, P.O. Box 6434, N-9294 Troms\u00f8, Norway"}]}],"member":"1968","published-online":{"date-parts":[[2019,12,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1038\/ngeo671","article-title":"CO2 emissions from forest loss","volume":"2","author":"Morton","year":"2009","journal-title":"Nat. Geosci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"985","DOI":"10.1126\/science.1136163","article-title":"Tropical Forests and Climate Policy","volume":"316","author":"Gullison","year":"2007","journal-title":"Science"},{"key":"ref_3","unstructured":"The United Nations Framework Convention on Climate Change (UNFCCC) (2019, September 27). 2015 Paris Agreement English. 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