Development of high precision estimation method for tree species resource of natural broadleaved trees using next generation laser sensing

2019 Fiscal Year Final Research Report

• Project/Area Number: 17H03827
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Single-year Grants
• Section: 一般
• Research Field: Forest science
• Research Institution: Shinshu University
• Principal Investigator: katoh nasato 信州大学, 学術研究院農学系, 教授 (40345757)
• Project Period (FY): 2017-04-01 – 2020-03-31
• Keywords: リモートセンシング / レーザセンシング / ドローン / スマート林業

Outline of Final Research Achievements

If we can accurately understand the number of trees by species and the contents of forest resources in a wide area forest without conducting a forest survey, not only will forest management be much more efficient, but it will be extremely effective for timber production and resource utilization of renewable energy. The purpose of this study is to develop a technique for calculating the resource amount of tree species in high-precision broad-leaved natural forest, which is the ultimate purpose, as an application of remote sensing technology including laser scanning to the forestry field. We aimed to contribute to effective use. In Nagano Prefecture, which is a research field, we have developed a technology for providing precise broad-leaved resource information in units of single tree level, measured using a drone laser scanning. This method can be used for point cloud data for laser scanning approach of airborne that has a wide range of applications.

Free Research Field

森林科学

Academic Significance and Societal Importance of the Research Achievements

1）上空からのレーザ計測のみで、多大な労力と費用を要している森林調査と資源管理が効率的になり，経費の削減効果が大きい。未利用資源として扱われている広葉樹林の価値の見直し、林産業、バイオマス資源として有効利用できることから、学術的かつ産業的な貢献もでき、大きなインパクトを与えることができる。
2）本研究の森林調査をせずに森林資源情報を把握する方法は、国内では広大な北海道の針広天然林、海外では広葉樹林の多い東南アジア，南アメリカ、アフリカなどの諸外国の森林にも応用可能なことから，日本が先導する国際共同研究に貢献できる。