{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T05:04:04Z","timestamp":1787029444720,"version":"3.56.0"},"reference-count":66,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2022,1,16]],"date-time":"2022-01-16T00:00:00Z","timestamp":1642291200000},"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>Soil moisture effects limit radar-based aboveground biomass carbon (AGBC) prediction accuracy as well as lead to stripes between adjacent paths in regional mosaics due to varying soil moisture conditions on different acquisition dates. In this study, we utilised the semi-empirical water cloud model (WCM) to account for backscattering from soil moisture in AGBC retrieval from L-band radar imagery in central Mozambique, where woodland ecosystems dominate. Cross-validation results suggest that (1) the standard WCM effectively accounts for soil moisture effects, especially for areas with AGBC \u2264 20 tC\/ha, and (2) the standard WCM significantly improved the quality of regional AGBC mosaics by reducing the stripes between adjacent paths caused by the difference in soil moisture conditions between different acquisition dates. By applying the standard WCM, the difference in mean predicted AGBC for the tested path with the largest soil moisture difference was reduced by 18.6%. The WCM is a valuable tool for AGBC mapping by reducing prediction uncertainties and striping effects in regional mosaics, especially in low-biomass areas including African woodlands and other woodland and savanna regions. It is repeatable for recent L-band data including ALOS-2 PALSAR-2, and upcoming SAOCOM and NISAR data.<\/jats:p>","DOI":"10.3390\/rs14020404","type":"journal-article","created":{"date-parts":[[2022,1,16]],"date-time":"2022-01-16T20:45:21Z","timestamp":1642365921000},"page":"404","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Large Area Aboveground Biomass and Carbon Stock Mapping in Woodlands in Mozambique with L-Band Radar: Improving Accuracy by Accounting for Soil Moisture Effects Using the Water Cloud Model"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5766-0956","authenticated-orcid":false,"given":"Yaqing","family":"Gou","sequence":"first","affiliation":[{"name":"Laboratory of Geo-Information Science and Remote Sensing, Wageningen University & Research, Droevendaalsesteeg 3, 6708 PB Wageningen, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1802-0128","authenticated-orcid":false,"given":"Casey M.","family":"Ryan","sequence":"additional","affiliation":[{"name":"School of GeoSciences, University of Edinburgh, Crew Building, The King\u2019s Buildings, Alexander Crum Brown Road, Edinburgh EH9 3FF, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4327-4349","authenticated-orcid":false,"given":"Johannes","family":"Reiche","sequence":"additional","affiliation":[{"name":"Laboratory of Geo-Information Science and Remote Sensing, Wageningen University & Research, Droevendaalsesteeg 3, 6708 PB Wageningen, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"757","DOI":"10.1007\/s10712-019-09510-6","article-title":"The role and need for space-based forest biomass-related measurements in environmental management and policy","volume":"40","author":"Herold","year":"2019","journal-title":"Surv. 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