{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T12:28:26Z","timestamp":1777724906504,"version":"3.51.4"},"reference-count":81,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2018,4,20]],"date-time":"2018-04-20T00:00:00Z","timestamp":1524182400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002322","name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","doi-asserted-by":"publisher","award":["Process BEX 9861\/14-9"],"award-info":[{"award-number":["Process BEX 9861\/14-9"]}],"id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Remote sensing techniques offer useful tools for estimating forest biomass to large extent, thereby contributing to the monitoring of land use and landcover dynamics and the effectiveness of environmental policies. The main goal of this study was to investigate the potential use of discrete return light detection and ranging (lidar) data to produce accurate aboveground biomass (AGB) maps of mangrove forests. AGB was estimated in 34 small plots scatted over a 50 km2 mangrove forest in Rio de Janeiro, Brazil. Plot AGB was computed using either species-specific or non-species-specific allometric models. A total of 26 descriptive lidar metrics were extracted from the normalized height of the lidar point cloud data, and various model forms (random forest and partial least squares regression with backward selection of predictors (Auto-PLS)) were tested to predict the recorded AGB. The models developed using species-specific allometric models were distinctly more accurate (R2(calibration) = 0.89, R2(validation) = 0.80, root-mean-square error (RMSE, calibration) = 11.20 t\u00b7ha\u22121, and RMSE(validation) = 14.80 t\u00b7ha\u22121). The use of non-species-specific allometric models yielded large errors on a landscape scale (+14% or \u221218% bias depending on the allometry considered), indicating that using poor quality training data not only results in low precision but inaccuracy at all scales. It was concluded that under suitable sampling pattern and provided that accurate field data are used, discrete return lidar can accurately estimate and map the AGB in mangrove forests. Conversely this study underlines the potential bias affecting the estimates of AGB in other forested landscapes where only non-species-specific allometric equations are available.<\/jats:p>","DOI":"10.3390\/rs10040637","type":"journal-article","created":{"date-parts":[[2018,4,23]],"date-time":"2018-04-23T04:29:17Z","timestamp":1524457757000},"page":"637","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Reducing Uncertainty in Mapping of Mangrove Aboveground Biomass Using Airborne Discrete Return Lidar Data"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1319-7717","authenticated-orcid":false,"given":"Francisca","family":"Rocha de Souza Pereira","sequence":"first","affiliation":[{"name":"National Institute for Space Research, Remote Sensing Division, Av. dos Astronautas 1758, S\u00e3o Jose dos Campos 12227-010, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0011-2083","authenticated-orcid":false,"given":"Milton","family":"Kampel","sequence":"additional","affiliation":[{"name":"National Institute for Space Research, Remote Sensing Division, Av. dos Astronautas 1758, S\u00e3o Jose dos Campos 12227-010, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3312-7257","authenticated-orcid":false,"given":"M\u00e1rio Luiz","family":"Gomes Soares","sequence":"additional","affiliation":[{"name":"N\u00facleo de Estudos em Manguezais, Rio de Janeiro State University, Rua S\u00e3o Francisco Xavier 524, Sala 4023E, Rio de Janeiro 20550-900, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gustavo Calderucio Duque","family":"Estrada","sequence":"additional","affiliation":[{"name":"Golder Associates, Via Antonio Banfo, 43, 10155 Turin, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0232-6912","authenticated-orcid":false,"given":"Cristina","family":"Bentz","sequence":"additional","affiliation":[{"name":"PETROBRAS R&amp;D Center, Rio de Janeiro 20550-900, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9443-021X","authenticated-orcid":false,"given":"Gregoire","family":"Vincent","sequence":"additional","affiliation":[{"name":"AMAP, IRD, CNRS, CIRAD, INRA, Univ Montpellier, F-34000 Montpellier, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,4,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1038\/ngeo1123","article-title":"Mangroves among the most carbon-rich forests in the tropics","volume":"4","author":"Donato","year":"2011","journal-title":"Nat. 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