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.
Highlights
The purpose of this research is to develop an end-to-end process that enables the connection of the three processes seamlessly by combining digital images acquired by Unmanned Aerial Vehicle (UAV) and limited data from ground surveys: (1) The detection of individual trees via 3D
The orthographic images and 3D point cloud data were created via UAV-Structure from (SfM) using Photoscan by inputting an aerial image taken by the UAV are shown in Figure 1c,d and Figure 4
This study developed an end-to-end process to simulate the future state of stand volume, carbon stock in the forest ecosystem, and forest attributes by coupling the current forest conditions derived by UAV with an individual-based gap model
Summary
The Paris agreement adopted in 2015 decided to limit the temperature increase to 2 degrees. Celsius above pre-industrial levels as the long-term target [1]. The special report in 2018 demonstrated the possibility of 1.5 ◦ C temperature increases of by 2030, which suggests that extreme measures are required to reduce the greenhouse gas produced globally [2]. Forests 2019, 10, 680 as critical issues in achieving the targets for reduction. Sustainable forest management is a global issue [1]. Reduced Emissions from Deforestation and forest Degradation (REDD+)
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