Remote sensing of environment and disaster laboratory

Institute of Industrial Science, The University of Tokyo, Japan

Estimation of optimal canopy shape on atropical broadleaf forest

photoTakumi Fujiwara and Wataru Takeuchi
IIS, The University of Tokyo
Abstract: The shadow fraction is an important factor in the light use efficiency of forests, but satellite-based methods can only estimate the fraction at the observation time.
Thus, if we create a virtual forest using globally available physical products of the forest, it is expected to calculate the shadow fraction at any given solar position. In thisstudy, we aimed to estimate the best combination for shadow fraction estimation by reflectance simulation, focusing on canopy shape and canopy coverage (CC). First, TreeHight (TH) and CC for the virtual forest were obtained from the products, respectively. Second, virtual forests were created, and the reflectance and shadow fraction weresimulated. The canopy shape used were cylinder, ellipsoid, half ellipsoid, and inverted half ellipsoid. Thirdly, the simulated reflectance was compared with Sentinel-2reflectance. Finally, the simulated shadow fraction was evaluated by that calculated from a voxel. The minimum RMSE for Sentinel-2 BOA reflectance was 0.025, and thecombination of canopy shape and CC was ellipsoid and 20%, respectively. RMSE for the mean daily shadow fraction was 0.149.
Keyword: Light use efficiency; Virtual forest; Structural parameter of a forest; Shadow; Satellite image

BACKGROUND: Satellite-based GPP estimation uses LUE. However, even thoughshadow is a major determinant of leaf surface conductance, satellite-based GPP only
provides shadow at the observation time. (The mean daily shadow fraction should be used.)Some of the forest structure parameters are globally available. If we can recreate various
forests based on those parameters, it is expected that the mean daily shadow fraction canbe calculated. However, there are no products on canopy shape.
to estimate the optimal canopy shape throughObjective 1,reflectancesimulations
2, to investigate whether these parameters can beused to estimate the shadow fraction of the forest.

Methodology

Fig 1. Research flowResults• Referring to the product,
CC was increased from
10% to 60% in 10%increments.
• A total of 24 virtual forest
patterns were created dueto the four types of tree
canopy shapes. For eachpattern, 40 forests arecreated.
Fig 4. An example of a virtual forest using a cylinderand a half-ellipsoid as crown shapes. CC is 60%
Fig 5. Variation of reflectance to CC and canopy shape

Allometric equation

Fig 2. Canopy shapes used for thevirtual forest.

Fig 3. Target forest

combination of canopy shape and CC with theConclusion • The
smallest RMSE for Sentinel-2 reflectance did notmatch that with the smallest error for mean daily
shadow fraction.
• The reason was inferred to be that only one scene
image was used.

CONCLUSION AND FUTURE TASK

• Reanalyze using multi-temporal images or multi-directional observation data• Use of asymmetrical canopy shapes.

For further details, contact: Takumi Fujiwara, Bw-601, 6-1, Komaba 4-chome, Meguro, Tokyo 153-8505 JAPAN (URL: http://wtlab.iis.u-tokyo.ac.jp/ E-mail: ftakumi@iis.u-tokyo.ac.jp)