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An End to End Process Development for UAV-SfM Based Forest Monitoring: Individual Tree Detection, Species Classification and Carbon Dynamics Simulation

1
Graduate School of Engineering, Osaka University, Yamadaoka 2-1, Suita, Osaka, 565-0871, Japan
2
Institute of Materials and Systems for Sustainability, Nagoya University, Furo-cho, Chikusa, Aichi, Nagoya 464-8601, Japan
3
International Digital Earth Applied Science Research Center, Matsumoto-cho 1200, Kasugai, Aichi 487-8501, Japan
4
Department of Civil Engineering, Nagoya University, Furo-cho, Chikusa, Aichi, Nagoya 464-8601, Japan
*
Author to whom correspondence should be addressed.
Forests 2019, 10(8), 680; https://doi.org/10.3390/f10080680
Received: 26 June 2019 / Revised: 7 August 2019 / Accepted: 8 August 2019 / Published: 11 August 2019
(This article belongs to the Section Forest Inventory, Quantitative Methods and Remote Sensing)
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Abstract

To promote Bio-Energy with Carbon dioxide Capture and Storage (BECCS), which aims to replace fossil fuels with bio energy and store carbon underground, and Reducing Emissions from Deforestation and forest Degradation (REDD+), which aims to reduce the carbon emissions produced by forest degradation, it is important to build forest management plans based on the scientific prediction of forest dynamics. For Measurement, Reporting and Verification (MRV) at an individual tree level, it is expected that techniques will be developed to support forest management via the effective monitoring of changes to individual trees. In this study, an end-to-end process was developed: (1) detecting individual trees from Unmanned Aerial Vehicle (UAV) derived digital images; (2) estimating the stand structure from crown images; (3) visualizing future carbon dynamics using a forest ecosystem process model. This process could detect 93.4% of individual trees, successfully classified two species using Convolutional Neural Network (CNN) with 83.6% accuracy and evaluated future ecosystem carbon dynamics and the source-sink balance using individual based model FORMIND. Further ideas for improving the sub-process of the end to end process were discussed. This process is expected to contribute to activities concerned with carbon management such as designing smart utilization for biomass resources and projecting scenarios for the sustainable use of ecosystem services.
Keywords: tree top detection; crown segmentation; species classification; carbon simulation tree top detection; crown segmentation; species classification; carbon simulation
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Fujimoto, A.; Haga, C.; Matsui, T.; Machimura, T.; Hayashi, K.; Sugita, S.; Takagi, H. An End to End Process Development for UAV-SfM Based Forest Monitoring: Individual Tree Detection, Species Classification and Carbon Dynamics Simulation. Forests 2019, 10, 680.

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