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http://dx.doi.org/10.14578/jkfs.2022.111.3.435

Review of Remote Sensing Technology for Forest Canopy Height Estimation and Suggestions for the Advancement of Korea's Nationwide Canopy Height Map  

Lee, Boknam (Human Resources Development Center for Big Data-based Glocal Forest Science 4.0 Professionals, Kyungpook National University)
Jung, Geonhwi (Department of Forestry, College of Agriculture and Life Science, Kyungpook National University)
Ryu, Jiyeon (Department of Forestry, College of Agriculture and Life Science, Kyungpook National University)
Kwon, Gyeongwon (Department of Forestry, College of Agriculture and Life Science, Kyungpook National University)
Yim, Jong Su (Forest ICT Research Center, National Institute of Forest Science)
Park, Joowon (School of Forest Sciences and Landscape Architecture, Kyungpook National University)
Publication Information
Journal of Korean Society of Forest Science / v.111, no.3, 2022 , pp. 435-449 More about this Journal
Abstract
Forest canopy height is an indispensable vertical structure parameter that can be used for understanding forest biomass and carbon storage as well as for managing a sustainable forest ecosystem. Plot-based field surveys, such as the national forest inventory, have been conducted to provide estimates of the forest canopy height. However, the comprehensive nationwide field monitoring of forest canopy height has been limited by its cost, lack of spatial coverage, and the inaccessibility of some forested areas. These issues can be addressed by remote sensing technology, which has gained popularity as a means to obtain detailed 2- and 3-dimensional measurements of the structure of the canopy at multiple scales. Here, we reviewed both international and domestic studies that have used remote sensing technology approaches to estimate the forest canopy height. We categorized and examined previous approaches as: 1) LiDAR approach, 2) Stereo or SAR image-based point clouds approach, and 3) combination approach of remote sensing data. We also reviewed upscaling approaches of utilizing remote sensing data to generate a continuous map of canopy height across large areas. Finally, we provided suggestions for further advancement of the Korean forest canopy height estimation system through the use of various remote sensing technologies.
Keywords
forest canopy height; remote sensing; LiDAR; Stereo/SAR image-based point clouds; upscaling;
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