A Hierarchical Approach to Three-Dimensional Segmentation of LiDAR Data at Single-Tree Level in a Multilayered Forest

Paris, Claudia; Valduga, Davide; Bruzzone, Lorenzo

doi:10.1109/tgrs.2016.2538203

Cited by 71 publications

(38 citation statements)

References 38 publications

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“…Finally, it is well known that the success of individual tree crown approaches highly depends on many factors, such as the lidar processing method, the forest characteristics and the lidar acquisition parameters [25,29,[39][40][41]. Furthermore, they have been validated over limited areas, and more effort must be put into the development and validation of robust individual tree extraction methods able to apply to different forest ecosystems.…”

Section: Discussionmentioning

confidence: 99%

Airborne Lidar Estimation of Aboveground Forest Biomass in the Absence of Field Inventory

et al. 2016

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Abstract:The scientific community involved in the UN-REDD program is still reporting large uncertainties about the amount and spatial variability of CO 2 stored in forests. The main limitation has been the lack of field samplings over space and time needed to calibrate and convert remote sensing measurements into aboveground biomass (AGB). As an alternative to costly field inventories, we examine the reliability of state-of-the-art lidar methods to provide direct retrieval of many forest metrics that are commonly collected through field sampling techniques (e.g., tree density, individual tree height, crown cover). AGB is estimated using existing allometric equations that are fed by lidar-derived metrics at either the individual tree-or forest layer-level (for the overstory or underneath layers, respectively). Results over 40 plots of a multilayered forest located in northwest Portugal show that the lidar method provides AGB estimates with a relatively small random error (RMSE = of 17.1%) and bias (of 4.6%). It provides local AGB baselines that meet the requirements in terms of accuracy to calibrate satellite remote sensing measurements (e.g., the upcoming lidar GEDI (Global Ecosystem Dynamics Investigation), and the Synthetic Aperture Radar (SAR) missions NISAR (National Aeronautics and Space Administration and Indian Space Research Organization SAR) and BIOMASS from the European Space Agency, ESA) for AGB mapping purposes. The development of similar techniques over a variety of forest types would be a significant improvement in quantifying CO 2 stocks and changes to comply with the UN-REDD policies.

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Section: Discussionmentioning

confidence: 99%

Airborne Lidar Estimation of Aboveground Forest Biomass in the Absence of Field Inventory

et al. 2016

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“…The vertical distribution of laser returns was then analyzed to find the next vegetation layer by identifying a local minimum in each segment and excluding the ALS data above the local minima from the point cloud that was used to produce a new CHM using only the lower layer. The process continued until no further CHM from lower vegetation layers could be created [25,26].…”

Section: Surface Model Methodsmentioning

confidence: 99%

Individual Tree Crown Methods for 3D Data from Remote Sensing

Lindberg

Holmgren

2017

Curr Forestry Rep

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Purpose of Review The rapid development of remote sensing technology has made dense 3D data available from airborne laser scanning and recently also photogrammetric point clouds. This paper reviews methods for extraction of individual trees from 3D data and their applications in forestry and ecology. Recent Findings Methods for analysis of 3D data at tree level have been developed since the turn of the century. The first algorithms were based on 2D surface models of the upper contours of tree crowns. These methods are robust and provide information about the trees in the top-most canopy. There are also methods that use the complete 3D data. However, development of these 3D methods is still needed to include use of geometric properties. To detect a large fraction of the tallest trees, a surface model method generally gives the best results, but detection of smaller trees below the top-most canopy requires methods utilizing the whole point cloud. Several new sensors are now available with capability to describe the upper part of the canopy, which can be used to frequently update vegetation maps. Highly sensitive laser photo detectors have become available for civilian applications, which will enable acquisition of high-resolution 3D laser data for large areas to much lower costs. Summary Methods for ITC delineation from 3D data provide information about a large fraction of the trees, but there is still a challenge to make optimal use of the information from the whole point cloud. Newly developed sensors might make ITC methods cheaper and feasible for large areas.

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“…However, these methods do not enable crown area estimates for subcanopy trees (but see e.g. Paris et al, 2016;Shendryk et al, 2016), which differ systematically in their crown allometries.…”

Section: Conclusion and Directions For Future Researchmentioning

confidence: 99%

Interspecific variation in tropical tree height and crown allometries in relation to life history traits

Cano

Muller‐Landau

Wright

et al. 2018

Biogeosciences Discuss.

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<p><strong>Abstract.</strong> Tree allometric relationships are widely employed to estimate forest biomass and production, and are basic building blocks of dynamic vegetation models. In tropical forests, allometric relationships are often modeled by fitting scale-invariant power functions to pooled data from multiple species, an approach that fails to reflect finite size effects at the smallest and largest sizes, and that ignores interspecific differences in allometry. Here, we analyzed allometric relationships of tree height (9884 individuals) and crown area (2425) with trunk diameter using species-specific morphological and life history data of 162 species from Barro Colorado Island, Panamá. We fit nonlinear, hierarchical models informed by species traits and assessed the performance of three alternative functional forms: the scale-invariant power function, and the saturating Weibull and generalized Michaelis-Menten (gMM) functions. The relationship of tree height with trunk diameter was best fit by a saturating gMM model in which variation in allometric parameters was related to interspecific differences in sapling growth rates, a measure of regeneration light demand. Light-demanding species attained taller heights at comparatively smaller diameters as juveniles and had shorter asymptotic heights at larger diameters as adults. The relationship of crown area with trunk diameter was best fit by a power function model incorporating a weak positive relationship between crown area and species-specific wood density. The use of saturating functional forms and the incorporation of functional traits in tree allometric models is a promising approach to improve estimates of forest biomass and productivity. Our results provide an improved basis for parameterizing tropical tree functional types in vegetation models.</p>

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A Hierarchical Approach to Three-Dimensional Segmentation of LiDAR Data at Single-Tree Level in a Multilayered Forest

Cited by 71 publications

References 38 publications

Airborne Lidar Estimation of Aboveground Forest Biomass in the Absence of Field Inventory

Airborne Lidar Estimation of Aboveground Forest Biomass in the Absence of Field Inventory

Individual Tree Crown Methods for 3D Data from Remote Sensing

Interspecific variation in tropical tree height and crown allometries in relation to life history traits

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