Forest plot volume estimation using national forest inventory, forest type map and airborne LiDAR data

Taejin Park, Woo Kyun Lee, Jong Yeol Lee, Woo Hyuk Byun, Doo Ahn Kwak, Guishan Cui, Moon Il Kim, Raesun Jung, Eko Pujiono, Suhyun Oh, Jungyeon Byun, Kijun Nam, Hyun Kook Cho, Jung Su Lee, Dong Jun Chung, Sung Ho Kim

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


The importance of estimating forest volume has been emphasized by increasing interest on carbon sequestration and storage which can be converted from volume estimates. With importance of forest volume, there are growing needs for developing efficient and unbiased estimation methods for forest volume using reliable data sources such as the National Forest Inventory (NFI) and supplementary information. Therefore, this study aimed to develop a forest plot volume model using selected explanatory variables from each data type (only Forest Type Map (FTM), only airborne LiDAR and both datasets), and verify the developed models with forest plot volumes in 60 test plots with the help of the NFI dataset. In linear regression modeling, three variables (LiDAR height sum, age, and crown density class) except diameter class were selected as explanatory independent variables. These variables generated the four forest plot volume models by combining the variables of each data type. To select an optimal forest plot volume model, a statistical comparing process was performed between four models. In verification, Model no. 3 constructed by both FTM and airborne LiDAR was selected as an optimal forest plot volume model through comparing root mean square error (RMSE) and coefficient of determination (R2). The selected best performance model can predict the plot volume derived from NFI with RMSE and R2 at 50.41 (m3) and 0.48, respectively.

Original languageEnglish
Pages (from-to)89-98
Number of pages10
JournalForest Science and Technology
Issue number2
Publication statusPublished - 2012

Bibliographical note

Funding Information:
This study was carried out with the support of ‘‘Forest Science and Technology Projects (Project No. S120911L010130)’’ provided by the Korea Forest Service and ‘‘A3 Foresight Program (Grant No A307-K005)’’ provided by the National Research Foundation of Korea.


  • Airborne LiDAR
  • Forest Type Map
  • Forest plot volume
  • Linear regression analysis
  • National Forest Inventory

ASJC Scopus subject areas

  • Forestry
  • Management, Monitoring, Policy and Law


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