{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T08:17:21Z","timestamp":1769329041700,"version":"3.49.0"},"reference-count":63,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2015,8,18]],"date-time":"2015-08-18T00:00:00Z","timestamp":1439856000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"IFPCAR","award":["4509-1"],"award-info":[{"award-number":["4509-1"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Light Detection and Ranging (Lidar) is a state of the art technology to assess forest aboveground biomass (AGB). To date, methods developed to relate Lidar metrics with forest parameters were built upon the vertical component of the data. In multi-layered tropical forests, signal penetration might be restricted, limiting the efficiency of these methods. A potential way for improving AGB models in such forests would be to combine traditional approaches by descriptors of the horizontal canopy structure. We assessed the capability and complementarity of three recently proposed methods for assessing AGB at the plot level using point distributional approach (DM), canopy volume profile approach (CVP), 2D canopy grain approach (FOTO), and further evaluated the potential of a topographical complexity index (TCI) to explain part of the variability of AGB with slope. This research has been conducted in a mountainous wet evergreen tropical forest of Western Ghats in India. AGB biomass models were developed using a best subset regression approach, and model performance was assessed through cross-validation. Results demonstrated that the variability in AGB could be efficiently captured when variables describing both the vertical (DM or CVP) and horizontal (FOTO) structure were combined. Integrating FOTO metrics with those of either DM or CVP decreased the root mean squared error of the models by 4.42% and 6.01%, respectively. These results are of high interest for AGB mapping in the tropics and could significantly contribute to the REDD+ program. Model quality could be further enhanced by improving the robustness of field-based biomass models and influence of topography on area-based Lidar descriptors of the forest structure.<\/jats:p>","DOI":"10.3390\/rs70810607","type":"journal-article","created":{"date-parts":[[2015,8,18]],"date-time":"2015-08-18T10:31:11Z","timestamp":1439893871000},"page":"10607-10625","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Aboveground-Biomass Estimation of a Complex Tropical Forest in India Using Lidar"],"prefix":"10.3390","volume":"7","author":[{"given":"C\u00e9dric","family":"V\u00e9ga","sequence":"first","affiliation":[{"name":"Laboratoire de l'Inventaire Forestier, Institut National de l'Information G\u00e9ographique et Foresti\u00e8re, 54000 Nancy, France"},{"name":"Institut Fran\u00e7ais de Pondich\u00e9ry, UMIFRE CNRS-MAEE 21, Pondicherry 605001, India"}]},{"given":"Udayalakshmi","family":"Vepakomma","sequence":"additional","affiliation":[{"name":"FPInnovations, 570 Saint-Jean Boulevard, Pointe-Claire, Montrea, QC H9R 3J9, Canada"}]},{"given":"Jules","family":"Morel","sequence":"additional","affiliation":[{"name":"Institut Fran\u00e7ais de Pondich\u00e9ry, UMIFRE CNRS-MAEE 21, Pondicherry 605001, India"}]},{"given":"Jean-Luc","family":"Bader","sequence":"additional","affiliation":[{"name":"Institut Fran\u00e7ais de Pondich\u00e9ry, UMIFRE CNRS-MAEE 21, Pondicherry 605001, India"}]},{"given":"Gopalakrishnan","family":"Rajashekar","sequence":"additional","affiliation":[{"name":"National Remote Sensing Center, Balanagar, Hyderabad 500037, India"}]},{"given":"Chandra","family":"Jha","sequence":"additional","affiliation":[{"name":"National Remote Sensing Center, Balanagar, Hyderabad 500037, India"}]},{"given":"J\u00e9r\u00f4me","family":"Fer\u00eat","sequence":"additional","affiliation":[{"name":"Institut Fran\u00e7ais de Pondich\u00e9ry, UMIFRE CNRS-MAEE 21, Pondicherry 605001, India"}]},{"given":"Christophe","family":"Proisy","sequence":"additional","affiliation":[{"name":"IRD, UMR AMAP, F-34000 Montpellier, France"}]},{"given":"Rapha\u00ebl","family":"P\u00e9lissier","sequence":"additional","affiliation":[{"name":"Institut Fran\u00e7ais de Pondich\u00e9ry, UMIFRE CNRS-MAEE 21, Pondicherry 605001, India"},{"name":"IRD, UMR AMAP, F-34000 Montpellier, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5084-1367","authenticated-orcid":false,"given":"Vinay","family":"Dadhwal","sequence":"additional","affiliation":[{"name":"National Remote Sensing Center, Balanagar, Hyderabad 500037, India"}]}],"member":"1968","published-online":{"date-parts":[[2015,8,18]]},"reference":[{"key":"ref_1","first-page":"85","article-title":"Above-ground standing biomass and carbon stock dynamics under a varied degree of anthropogenic pressure in tropical rain forests of Uttara Kannada District, Western Ghats, India","volume":"56","author":"Bhat","year":"2011","journal-title":"Taiwania"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1126\/science.1184984","article-title":"Terrestrial gross carbon dioxide uptake: Global distribution and covariation with climate","volume":"329","author":"Beer","year":"2010","journal-title":"Science"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1126\/science.263.5144.185","article-title":"Carbon pools and flux of global forest ecosystems","volume":"263","author":"Dixon","year":"1994","journal-title":"Science"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"235","DOI":"10.5194\/bg-6-235-2009","article-title":"Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling","volume":"6","author":"Morton","year":"2009","journal-title":"Biogeosciences"},{"key":"ref_5","unstructured":"UNFCC Kyoto Protocol Reference Manual on Accounting of Emissions Assigned Amount. 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