Computer Vision Techniques in Forest Inventory Assessment: Improving Accuracy of Tree Diameter Measurement Using Smartphone Camera and Photogrammetry

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초록

The forest industry is facing many challenges, including lack of labor and low operational efficiency. In South Korea, the small-scale forest industry has hindered the development of advanced-level forest industry due to high cost of machines and sensors. To overcome these challenges, the application of ICT technologies can be considered a means of rehabilitating the Korean forest industry. As one approach, we investigated the possibility of using smartphone-integrated computer vision in forest inventory assessment. Individual tree diameters were estimated using four different circular fitting algorithms: least-squares circle (C), minimum enclosing circle (MEC), convex hull (CH), and least-squares ellipse (E). We found that C and MEC were the most accurate algorithms for estimating the tree diameter in Pinus densiflora (PD) and Pinus koraiensis (PK) forest stands. The results of this research indicate the possibility of using smartphones to investigate the forest structure efficiently.

키워드

computer vision; photogrammetry; tree diameter; forest inventory; image processing; STEM VOLUME; ABOVEGROUND BIOMASS; INDIVIDUAL TREES; TERRESTRIAL; LIDAR; DBH; HEIGHT; ATTRIBUTES
제목
Computer Vision Techniques in Forest Inventory Assessment: Improving Accuracy of Tree Diameter Measurement Using Smartphone Camera and Photogrammetry
저자
Woo, Heesung; Kim, Ikhyun; Choi, Byoungkoo
DOI
10.18494/SAM.2021.3605
발행일
2021
유형
Article
저널명
Sensors and Materials
권
33
호
11
페이지
3835 ~ 3845