Estimating deforestation and forest degradation from an unmanned aerial vehicle in seasonal tropical forest

• Project/Area Number: 16K18721
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Forest science
• Research Institution: Kyushu University
• Principal Investigator: Ota Tetsuji 九州大学, 持続可能な社会のための決断科学センター, 助教 (10753717)
• Project Period (FY): 2016-04-01 – 2019-03-31
• Project Status: Completed (Fiscal Year 2018)
• Budget Amount: ¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000); Fiscal Year 2018: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000); Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000); Fiscal Year 2016: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
• Keywords: UAV（ドローン） / 択伐 / リモートセンシング / 地上バイオマス量 / UAV / ドローン / SfM / 森林 / 熱帯林

Outline of Final Research Achievements

This study investigated the utility of the low cost UAV (unmanned aerial vehicle) for estimating deforestation and forest degradation in seasonal tropical forest. We at first, evaluated the importance of ground control point (GCP) for reducing location error and the accuracy of forest structure estimation using digital aerial photographs acquired from the UAV. The result showed that we should put 10 GCP to reduce the location error if possible. The results also revealed that we can estimate forest structure estimation at stand level with UAV. We then evaluate the accuracy of aboveground biomass change estimation using repeatedly acquired digital aerial photographs from the UAV in tropical forests in Myanmar. The result showed that repeatedly acquired digital aerial photographs from the UAV can quantify the aboveground biomass change due to selective logging in tropical forests.

Academic Significance and Societal Importance of the Research Achievements

森林の減少・劣化は地球規模の問題として以前より重要視されており，これらを効率的にモニタリングする手法が求められている。本研究課題では，UAV（ドローン）を用いた森林減少・劣化のモニタリング手法の開発を目的に，1)UAVが取得した空中写真の位置精度の検証および林分構造推定モデルの開発，および2)AVを用いた森林減少・劣化量の推定技術の開発を実施した。
その結果，適切な手法を用いることで，UAVから林分レベルで森林の構造を推定できること，伐採前後にUAVから撮影した写真から森林の伐採量を林分レベルで推定できることが明らかとなった。

Research Products

• [Journal Article] Estimating selective logging in tropical forests using repeated digital aerial photography from an unmanned aerial vehicle (2019)
  • Author(s): Ota, T., Ahmed, O.S., Minn, S.T., Khai, T.C., Mizoue, N. and Yoshida, S.
  • Journal Title: Forest Ecology and Management Volume: 433 Pages: 162-169
  • DOI: 10.1016/j.foreco.2018.10.058
  • Peer Reviewed
• [Journal Article] Forest Structure Estimation from a UAV-Based Photogrammetric Point Cloud in Managed Temperate Coniferous Forests (2017)
  • Author(s): Ota Tetsuji、Ogawa Miyuki、Mizoue Nobuya、Fukumoto Keiko、Yoshida Shigejiro
  • Journal Title: forests Volume: 8 Issue: 9 Pages: 343-343
  • DOI: 10.3390/f8090343
• [Presentation] ２時期UAV画像による択伐量の検出 (2018)
  • Author(s): 太田徹志、Sie Thu Minn、Tual Cin Khai、溝上展也、吉田茂二郎
  • Organizer: 第74回九州森林学会
• [Presentation] UAV由来の空中写真データを用いた熱帯林の森林変化量の把握 (2018)
  • Author(s): 太田徹志, Tual Cin Khai, Sie Thu Minn, 溝上展也 , 吉田茂二郎
  • Organizer: 日本森林学会
• [Presentation] UAVを用いた林分構造推定 (2017)
  • Author(s): 太田徹志・小川みゆき・溝上展也・吉田茂二郎
  • Organizer: 日本森林学会
  • Place of Presentation: 鹿児島大学
  • Year and Date: 2017-03-26
• [Presentation] Forest structure estimation using structure from motion approach with UAV in a managed coniferous forest (2017)
  • Author(s): Ota Tetsuji, Ogawa Miyuki, Mizoue Nobuya, Yoshida Shigejiro
  • Organizer: IUFRO 125th Anniversary Congress
  • Int'l Joint Research