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http://dx.doi.org/10.7780/kjrs.2020.36.5.1.1

Estimating the Stand Level Vegetation Structure Map Using Drone Optical Imageries and LiDAR Data based on an Artificial Neural Networks (ANNs)  

Cha, Sungeun (Department of Environmental Science and Ecological Engineering, Korea University)
Jo, Hyun-Woo (Department of Environmental Science and Ecological Engineering, Korea University)
Lim, Chul-Hee (Institute of Life Science and Natural Resources, Korea University)
Song, Cholho (OJEong Resilience Institute (OJERI), Korea University)
Lee, Sle-Gee (OJEong Resilience Institute (OJERI), Korea University)
Kim, Jiwon (Department of Environmental Science and Ecological Engineering, Korea University)
Park, Chiyoung (Geomatics Research Institute, Saehan Aero Survey Co., Ltd.)
Jeon, Seong-Woo (Department of Environmental Science and Ecological Engineering, Korea University)
Lee, Woo-Kyun (Department of Environmental Science and Ecological Engineering, Korea University)
Publication Information
Korean Journal of Remote Sensing / v.36, no.5_1, 2020 , pp. 653-666 More about this Journal
Abstract
Understanding the vegetation structure is important to manage forest resources for sustainable forest development. With the recent development of technology, it is possible to apply new technologies such as drones and deep learning to forests and use it to estimate the vegetation structure. In this study, the vegetation structure of Gongju, Samchuk, and Seoguipo area was identified by fusion of drone-optical images and LiDAR data using Artificial Neural Networks(ANNs) with the accuracy of 92.62% (Kappa value: 0.59), 91.57% (Kappa value: 0.53), and 86.00% (Kappa value: 0.63), respectively. The vegetation structure analysis technology using deep learning is expected to increase the performance of the model as the amount of information in the optical and LiDAR increases. In the future, if the model is developed with a high-complexity that can reflect various characteristics of vegetation and sufficient sampling, it would be a material that can be used as a reference data to Korea's policies and regulations by constructing a country-level vegetation structure map.
Keywords
Vegetation structure; Drone image; Artificial Neural Networks(ANNs); Sustainable forest development;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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