A simulation method to infer tree allometry and forest structure from airborne laser scanning and forest inventories

REMOTE SENSING OF ENVIRONMENT

卷:251

Article

Fischer, Fabian Jorg¹  Labriere, Nicolas¹  Vincent, Gregoire²  Herault, Bruno^3,4  Alonso, Alfonso⁵  Memiaghe, Herve⁶  Bissiengou, Pulcherie⁷  Kenfack, David⁸  Saatchi, Sassan⁹  Chave, Jerome¹ 

[1] UMR 5174 CNRS IRD UPS, Lab Evolut & Diversite Biol, 118 Route Narbonne, F-31062 Toulouse 9, France

[2] Univ Montpellier, AMAP, IRD, CIRAD,CNRS,INRAE, Montpellier, France

[3] Univ Montpellier, Cirad, UR Forests & Soc, F-34000 Montpellier, France

[4] Inst Natl Polytech Felix Houphouet Boigny, INPHB, Yamoussoukro, Cote Ivoire

[5] Smithsonian Conservat Biol Inst, Ctr Conservat & Sustainabil, 1100 Jefferson Dr SW,Suite 3123, Washington, DC 20560 USA

[6] Ctr Natl Rech Sci & Technol CENAREST, Inst Rech Ecol Trop IRET, BP 13354, Libreville, Gabon

[7] Ctr Natl Rech Sci & Technol CENAREST, Herbier Natl Gabon, Inst Pharmacopee & Med Tradit IPHAMETRA, BP 1165, Libreville, Gabon

[8] Smithsonian Trop Res Inst, Ctr Trop Forest Sci, Forest Global Earth Observ, 10th & Constitut Ave NW, Washington, DC 20560 USA

[9] CALTECH, Jet Prop Lab, 4800 Oak Grove Dr, Pasadena, CA 91109 USA

关键词: Vegetation structure;    Tropical forest;    Individual-based modeling;    Airborne lidar;    Approximate Bayesian Computation;    Allometry;    Biomass;    Canopy space filling;   

DOI  :  10.1016/j.rse.2020.112056

来源: Elsevier

【 摘 要 】

Tropical forests are characterized by large carbon stocks and high biodiversity, but they are increasingly threatened by human activities. Since structure strongly influences the functioning and resilience of forest communities and ecosystems, it is important to quantify it at fine spatial scales. Here, we propose a new simulation-based approach, the Canopy Constructor, with which we quantified forest structure and biomass at two tropical forest sites, one in French Guiana, the other in Gabon. In a first step, the Canopy Constructor combines field inventories and airborne lidar scans to create virtual 3D representations of forest canopies that best fit the data. From those, it infers the forests' structure, including crown packing densities and allometric scaling relationships between tree dimensions. In a second step, the results of the first step are extrapolated to create virtual tree inventories over the whole lidar-scanned area. Across the French Guiana and Gabon plots, we reconstructed empirical canopies with a mean absolute error of 3.98 m [95% credibility interval: 3.02, 4.98], or 14.4%, and a small upwards bias of 0.66 m [-0.41, 1.8], or 2.7%. Height-stem diameter allometries were inferred with more precision than crown-stem diameter allometries, with generally larger heights at the Amazonian than the African site, but similar crown-stem diameter allometries. Plot-based aboveground biomass was inferred to be larger in French Guiana with 400.8 t ha(-1) [366.2-437.9], compared to 302.2 t ha(-1) in Gabon [267.8-336.8] and decreased to 299.8 t ha(-1) [275.9-333.9] and 251.8 t ha(-1) [206.7-291.7] at the landscape scale, respectively. Predictive accuracy of the extrapolation procedure had an RMSE of 53.7 t ha(-1) (14.9%) at the 1 ha scale and 87.6 t ha(-1) (24.2%) at the 0.25 ha scale, with a bias of -17.1 t ha(-1) (-4.7%). This accuracy was similar to regression-based approaches, but the Canopy Constructor improved the representation of natural heterogeneity considerably, with its range of biomass estimates larger by 54% than regression-based estimates. The Canopy Constructor is a comprehensive inference procedure that provides fine-scale and individual-based reconstructions even in dense tropical forests. It may thus prove vital in the assessment and monitoring of those forests, and has the potential for a wider applicability, for example in the exploration of ecological and physiological relationships in space or the initialisation and calibration of forest growth models.

【 授权许可】

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