Extended biomass allometric equations for large mangrove trees from terrestrial LiDAR data

Abstract

International audienceAccurately determining biomass of large trees is crucial for reliable biomass analyses in most tropical forests, but most allometric models calibration are deficient in large trees data. This issue is a major concern for high-biomass mangrove forests, especially when their role in the ecosystem carbon storage is considered. As an alternative to the fastidious cutting and weighing measurement approach, we explored a non-destructive terrestrial laser scanning approach to estimate the aboveground biomass of large mangroves (diameters reaching up to 125 cm). Because of buttresses in large trees, we propose a pixel-based analysis of the composite 2D flattened images, obtained from the successive thin segments of stem point-cloud data to estimate wood volume. Branches were considered as successive best-fitted primitive of conical frustums. The product of wood volume and height-decreasing wood density yielded biomass estimates. This approach was tested on 36 A. germinans trees in French Guiana, considering available biomass models from the same region as references. Our biomass estimates reached ca. 90% accuracy and a correlation of 0.99 with reference biomass values. Based on the results, new tree biomass model, which had R² of 0.99 and RSE of 87.6 kg of dry matter. This terrestrial LiDAR-based approach allows the estimates of large tree biomass to be tractable, and opens new opportunities to improve biomass estimates of tall mangroves. The method could also be tested and applied to other tree species

Using terrestrial laser scanning data to estimate large tropical trees biomass and calibrate allometric models: A comparison with traditional destructive approach

“…The use of TLS technology to estimate tree volume and AGB is beginning to be well documented in temperate forests, but its application to large tropical trees of contrasted architecture and often buttresses or fluted stems is a big step further. Direct use of raw simpletree QSMs to estimate tree volume highlighted the (expected) difficulties of the cylinder‐based, automated approach to describe large tree stumps and crowns, requiring manual edits and the separate modelling of buttressed parts with a mesh model (Cushman, Muller‐Landau, Condit, & Hubbell, ; Nogueira, Fearnside, Nelson, Barbosa, & Keizer, ; Nölke et al., ; Olagoke et al., ; Picard & Saint‐andré, ). While reconstruction algorithms are rapidly evolving (Raumonen et al., , ; Stovall et al., ; Tao et al., ; Trochta et al., ) in the hope to upscale studies to entire forest stands, the semi‐automated procedure proposed here is already fully operational even in very dense tropical forests at the leaf‐on stage, allowing to improve validation R ² for tree volumes from .75 to .98, and to reduce from 29% to 12%.…”

“…The use of TLS technology to estimate tree volume and AGB is beginning to be well documented in temperate forests, but its application to large tropical trees of contrasted architecture and often buttresses or fluted stems is a big step further. Direct use of raw simpletree QSMs to estimate tree volume highlighted the (expected) difficulties of the cylinder-based, automated approach to describe large tree stumps and crowns, requiring manual edits and the separate modelling of buttressed parts with a mesh model (Cushman, Muller-Landau, Condit, & Hubbell, 2014;Nogueira, Fearnside, Nelson, Barbosa, & Keizer, 2008;Nölke et al, 2015;Olagoke et al, 2016;Picard & Saint-andré, 2012).…”

Segmentation of unbalanced and in-homogeneous point clouds and its application to 3D scanned trees

“…Indeed, TLS enables 3D forest geometric information to be acquired at high speed [12], with applications ranging from ecology to forestry (forest monitoring, sustainable development) and industry (harvest planning, sawmill optimization). In the field of forestry, TLS data have, for instance, been successfully used to enhance allometric theory [37]. This theory consists of a set of general relations derived from a large compilation of forest measurements.…”

Estimating and Mapping Mangrove Biomass Dynamic Change Using WorldView-2 Images and Digital Surface Models

“…Producing accurate biomass models requires further key input parameters that can be obtained from images, such as species type and tree height, to identify variations of a mangrove forest structure [21]. Species type can be mapped by supervised classification [22], [23], and tree height can be obtained by canopy height models (CHM) using LiDAR (e.g., satellite LiDAR [24], terrestrial LiDAR [25], airborne LiDAR [26]), InSAR [26]- [29], or aerial photographs [30]- [33], which can be successfully applied to estimate forest biomass.…”

“…It is also an adequate low-cost alternative to obtain tree height compared with LiDAR or InSAR methods [37]. Previous studies demonstrated the utility of CHM derived from SfM [25], [38], [39], which has also been applied to estimate AGB [30]- [33].…”