EGU21-14670
https://doi.org/10.5194/egusphere-egu21-14670
EGU General Assembly 2021
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Understory biomass estimation based on Structure from Motion data by Multi-layered forest drone survey

Yupan Zhang1, Yuichi Onda1, Hiroaki Kato1, Xinchao Sun2, and Takashi Gomi3
Yupan Zhang et al.
  • 1Center for Research in Isotopes and Environmental Dynamics, University of Tsukuba, Tsukuba, Ibaraki 305-8572, Japan
  • 2Institute of Surface-Earth System Science, Tianjin University, 92 Weijin Road, Nankai District, Tianjin 300072, PR China
  • 3Department of International Environmental and Agricultural Science, Tokyo University of Agriculture and Technology, Fuchu, Tokyo 183-8509, Japan

Understory vegetation is an important part of evapotranspiration from forest floor. Forest management changes the forest structure and then affects the understory vegetation biomass (UVB). Quantitative measurement and estimation of  UVB is a step cannot be ignored in the study of forest ecology and forest evapotranspiration. However, large-scale biomass measurement and estimation is challenging. In this study, Structure from Motion (SfM) was adopted simultaneously at two different layers in a plantation forest made by Japanese cedar and Japanese cypress to reconstruct forest structure from understory to above canopy: i) understory drone survey in a 1.1h sub-catchment to generate canopy height model (CHM) based on dense point clouds data derived from a manual low-flying drone under the canopy; ii) Above-canopy drone survey in whole catchment (33.2 ha) to compute canopy openness data based on point clouds of canopy derived from an autonomous flying drone above the canopy. Combined with actual biomass data from field harvesting to develop regression models between the CHM and UVB, which was then used to map spatial distribution of  UVB in sub-catchment. The relationship between UVB and canopy openness data was then developed by overlap analysis. This approach yielded high resolution understory over catchment scale with a point cloud density of more than 20 points/cm2. Strong coefficients of determination (R-squared = 0.75) of the cubic model supported prediction of UVB from CHM, the average UVB was 0.82kg/m2 and dominated by low ferns. The corresponding forest canopy openness in this area was 42.48% on average. Overlap analysis show no significant interactions between them in a cubic model with weak predictive power (R-squared < 0.46). Overall, we reconstructed the multi-layered structure of the forest and provided models of UVB. Understory survey has high accuracy for biomass measurement, but it’s inherently difficult to estimate UVB only based on canopy openness result.

How to cite: Zhang, Y., Onda, Y., Kato, H., Sun, X., and Gomi, T.: Understory biomass estimation based on Structure from Motion data by Multi-layered forest drone survey, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14670, https://doi.org/10.5194/egusphere-egu21-14670, 2021.