Deriving Tree Size Distributions of Tropical Forests from Lidar

Autor(en): Taubert, Franziska
Fischer, Rico
Knapp, Nikolai
Huth, Andreas 
Stichwörter: AREA; Barro Colorado Island; BIOMASS; CANOPY; Environmental Sciences; Environmental Sciences & Ecology; forest structure; Geology; Geosciences, Multidisciplinary; HEIGHT; Imaging Science & Photographic Technology; leaf area distribution; lidar; lidar profile; MODEL; PREDICTIONS; PROFILES; Remote Sensing; SATELLITE; stem diameter distribution; TANDEM-X; tropical forests; WAVE-FORMS
Erscheinungsdatum: 2021
Herausgeber: MDPI
Journal: REMOTE SENSING
Volumen: 13
Ausgabe: 1
Zusammenfassung: 
Remote sensing is an important tool to monitor forests to rapidly detect changes due to global change and other threats. Here, we present a novel methodology to infer the tree size distribution from light detection and ranging (lidar) measurements. Our approach is based on a theoretical leaf-tree matrix derived from allometric relations of trees. Using the leaf-tree matrix, we compute the tree size distribution that fit to the observed leaf area density profile via lidar. To validate our approach, we analyzed the stem diameter distribution of a tropical forest in Panama and compared lidar-derived data with data from forest inventories at different spatial scales (0.04 ha to 50 ha). Our estimates had a high accuracy at scales above 1 ha (1 ha: root mean square error (RMSE) 67.6 trees ha(-1)/normalized RMSE 18.8%/R-2 0.76; 50 ha: 22.8 trees ha(-1)/6.2%/0.89). Estimates for smaller scales (1-ha to 0.04-ha) were reliably for forests with low height, dense canopy or low tree height heterogeneity. Estimates for the basal area were accurate at the 1-ha scale (RMSE 4.7 tree ha(-1), bias 0.8 m(2) ha(-1)) but less accurate at smaller scales. Our methodology, further tested at additional sites, provides a useful approach to determine the tree size distribution of forests by integrating information on tree allometries.
DOI: 10.3390/rs13010131

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