{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T08:04:14Z","timestamp":1776326654291,"version":"3.50.1"},"reference-count":107,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2019,1,3]],"date-time":"2019-01-03T00:00:00Z","timestamp":1546473600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Fonds Fran\u00e7ais pour l\u2019Environnement Mondial (FFEM)","award":["Livelihoods (Carbon) Fund"],"award-info":[{"award-number":["Livelihoods (Carbon) Fund"]}]},{"DOI":"10.13039\/501100004837","name":"Ministerio de Ciencia e Innovaci\u00f3n","doi-asserted-by":"publisher","award":["National Programme for the Promotion of Talent and Its Employability (Torres-Quevedo program)"],"award-info":[{"award-number":["National Programme for the Promotion of Talent and Its Employability (Torres-Quevedo program)"]}],"id":[{"id":"10.13039\/501100004837","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Due to the increasing importance of mangroves in climate change mitigation projects, more accurate and cost-effective aboveground biomass (AGB) monitoring methods are required. However, field measurements of AGB may be a challenge because of their remote location and the difficulty to walk in these areas. This study is based on the Livelihoods Fund Oceanium project that monitors 10,000 ha of mangrove plantations. In a first step, the possibility of replacing traditional field measurements of sample plots in a young mangrove plantation by a semiautomatic processing of UAV-based photogrammetric point clouds was assessed. In a second step, Sentinel-1 radar and Sentinel-2 optical imagery were used as auxiliary information to estimate AGB and its variance for the entire study area under a model-assisted framework. AGB was measured using UAV imagery in a total of 95 sample plots. UAV plot data was used in combination with non-parametric support vector regression (SVR) models for the estimation of the study area AGB using model-assisted estimators. Purely UAV-based AGB estimates and their associated standard error (SE) were compared with model-assisted estimates using (1) Sentinel-1, (2) Sentinel-2, and (3) a combination of Sentinel-1 and Sentinel-2 data as auxiliary information. The validation of the UAV-based individual tree height and crown diameter measurements showed a root mean square error (RMSE) of 0.21 m and 0.32 m, respectively. Relative efficiency of the three model-assisted scenarios ranged between 1.61 and 2.15. Although all SVR models improved the efficiency of the monitoring over UAV-based estimates, the best results were achieved when a combination of Sentinel-1 and Sentinel-2 data was used. Results indicated that the methodology used in this research can provide accurate and cost-effective estimates of AGB in young mangrove plantations.<\/jats:p>","DOI":"10.3390\/rs11010077","type":"journal-article","created":{"date-parts":[[2019,1,3]],"date-time":"2019-01-03T11:11:56Z","timestamp":1546513916000},"page":"77","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":157,"title":["Integration of UAV, Sentinel-1, and Sentinel-2 Data for Mangrove Plantation Aboveground Biomass Monitoring in Senegal"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8994-3085","authenticated-orcid":false,"given":"Jos\u00e9 Antonio","family":"Navarro","sequence":"first","affiliation":[{"name":"Agresta Soc. Coop., 28012 Madrid, Spain"},{"name":"MONTES (School of Forest Engineering and Natural Environment), Universidad Polit\u00e9cnica de Madrid, 28040 Madrid, Spain"}]},{"given":"Nur","family":"Algeet","sequence":"additional","affiliation":[{"name":"Agresta Soc. Coop., 28012 Madrid, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4725-8044","authenticated-orcid":false,"given":"Alfredo","family":"Fern\u00e1ndez-Landa","sequence":"additional","affiliation":[{"name":"Agresta Soc. Coop., 28012 Madrid, Spain"}]},{"given":"Jessica","family":"Esteban","sequence":"additional","affiliation":[{"name":"Departamento de Topograf\u00eda y Geom\u00e1tica, ETSI Caminos, Canales y Puertos, Universidad Polit\u00e9cnica de Madrid, 28040 Madrid, Spain"}]},{"given":"Pablo","family":"Rodr\u00edguez-Noriega","sequence":"additional","affiliation":[{"name":"Agresta Soc. Coop., 28012 Madrid, Spain"}]},{"given":"Mar\u00eda Luz","family":"Guill\u00e9n-Climent","sequence":"additional","affiliation":[{"name":"Agresta Soc. Coop., 28012 Madrid, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2019,1,3]]},"reference":[{"key":"ref_1","unstructured":"Murdiyarso, D., Donato, D., Kauffman, J.B., Kurnianto, S., Stidham, M., and Kanninen, M. (2009). Carbon Storage in Mangrove and Peatland Ecosystems. A Preliminary Account from Plots in Indonesia, Center for International Forestry Research."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Donato, D.C., Kauffman, J.B., Murdiyarso, D., Kurnianto, S., Stidham, M., and Kanninen, M. (2011). Mangroves among the most carbon-rich forests in the tropics. Nat. 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