Integration of Multi-Sensor Data to Estimate Plot-Level Stem Volume Using Machine Learning Algorithms–Case Study of Evergreen Conifer Planted Forests in Japan

Integration of Multi-Sensor Data to Estimate Plot-Level Stem Volume Using Machine Learning Algorithms–Case Study of Evergreen Conifer Planted Forests in Japan

The development of new methods for estimating precise forest structure parameters is essential for the quantitative evaluation of forest resources. Conventional use of satellite image data, increasing use of terrestrial laser scanning (TLS), and emerging trends in the use of unmanned aerial systems...

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Bibliographic Details
Main Authors: Kotaro Iizuka, Yuichi S. Hayakawa, Takuro Ogura, Yasutaka Nakata, Yoshiko Kosugi, Taichiro Yonehara
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Remote Sensing
Subjects:
UAS
stem volume
TLS
SAR
random forest
support vector
Online Access:https://www.mdpi.com/2072-4292/12/10/1649

Internet

https://www.mdpi.com/2072-4292/12/10/1649

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