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Aboveground biomass estimation in tropical forests at single tree level with ALS data

Dalponte, M; Jucker, T; Burslem, DFRP; Lewis, SL; Nilus, R; Phillips, O; Qie, L; (2016) Aboveground biomass estimation in tropical forests at single tree level with ALS data. In: Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). (pp. pp. 5334-5337). IEEE: Beijing, China. Green open access

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Abstract

In this paper we present a study on the estimation of the aboveground biomass in tropical forests at single tree level using airborne laser scanning (ALS) data. Individual tree crowns (ITCs) are firstly detected using a method based on an adaptive window that change its size according to tree height. The diameter at breast height (DBH) and the aboveground biomass (AGB) of each ITC then are predicted using standard allometric models. Lastly, the AGB values are aggregated at plot level, and compared with field measured values. The results show that it is possible to accurately predict the aboveground biomass of tropical forests at single tree level using ALS data.

Type: Proceedings paper
Title: Aboveground biomass estimation in tropical forests at single tree level with ALS data
Event: 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
ISBN-13: 9781509033324
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/IGARSS.2016.7730390
Publisher version: https://doi.org/10.1109/IGARSS.2016.7730390
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Vegetation, Carbon, Soil, Biomass, Estimation, Electronic mail, Laser modes, aboveground biomass, LiDAR, ALS, tropical forest
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Geography
URI: https://discovery.ucl.ac.uk/id/eprint/10071789
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