Development of high-precision classification technology for standing trees by integrating next-generation airborne and ground based laser scanning

2022 Fiscal Year Final Research Report

• Project/Area Number: 20H03025
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Single-year Grants
• Section: 一般
• Review Section: Basic Section 40010:Forest science-related
• Research Institution: Shinshu University
• Principal Investigator: Katoh Masato 信州大学, 学術研究院農学系, 教授 (40345757)
• Co-Investigator(Kenkyū-buntansha): トウ ソウキュウ 信州大学, 先鋭領域融合研究群山岳科学研究所, 研究員 (00772477)
• Project Period (FY): 2020-04-01 – 2023-03-31
• Keywords: レーザセンシング / ドローン / スマート林業 / リモートセンシング

Outline of Final Research Achievements

About 70% of Japan's land area is forest. However, the current situation in Japan is that forest resources are not fully utilized. The Forestry Agency, local governments, and forestry business entities are highly demanding information on the value of both the amount of resources and product categories for wide-area forests. The existing forest survey methods are sample survey that rely on manual labor due to variations in accuracy among surveyors and oversight of trees, the amount of information and accuracy obtained relative to the survey cost is low, and the amount of resources cannot be accurately evaluated. is considered a problem.
In this research, by integrating next-generation laser scanning from drone and ground mobile, we will promote the development of technology that enables highly accurate product classification from 3D information on tree crowns and trunks. Calculating the amount and value of resources will be a breakthrough for turning forestry into a growth industry.

Free Research Field

森林科学

Academic Significance and Societal Importance of the Research Achievements

本技術は、レーザ計測から高精度な樹冠と幹の樹幹抽出から、単木区分と幹の細り（任意の直径、曲がり）を算出して、価値の高い建築用構造材（Ａ材丸太）
の丸太の立木品等区分が可能になった。極めて有効な自動分類技術であると共に 、国際的にオリジナルな研究開発であり、特許出願を予定している。