Document Detail


Accurate estimation of forest carbon stocks by 3-D remote sensing of individual trees.
MedLine Citation:
PMID:  12680675     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Forests are one of the most important carbon sinks on Earth. However, owing to the complex structure, variable geography, and large area of forests, accurate estimation of forest carbon stocks is still a challenge for both site surveying and remote sensing. For these reasons, the Kyoto Protocol requires the establishment of methodologies for estimating the carbon stocks of forests (Kyoto Protocol, Article 5). A possible solution to this challenge is to remotely measure the carbon stocks of every tree in an entire forest. Here, we present a methodology for estimating carbon stocks of a Japanese cedar forest by using a high-resolution, helicopter-borne 3-dimensional (3-D) scanning lidar system that measures the 3-D canopy structure of every tree in a forest. Results show that a digital image (10-cm mesh) of woody canopy can be acquired. The treetop can be detected automatically with a reasonable accuracy. The absolute error ranges for tree height measurements are within 42 cm. Allometric relationships of height to carbon stocks then permit estimation of total carbon storage by measurement of carbon stocks of every tree. Thus, we suggest that our methodology can be used to accurately estimate the carbon stocks of Japanese cedar forests at a stand scale. Periodic measurements will reveal changes in forest carbon stocks.
Authors:
Kenji Omasa; Guo Yu Qiu; Kenichi Watanuki; Kenji Yoshimi; Yukihide Akiyama
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Environmental science & technology     Volume:  37     ISSN:  0013-936X     ISO Abbreviation:  Environ. Sci. Technol.     Publication Date:  2003 Mar 
Date Detail:
Created Date:  2003-04-08     Completed Date:  2003-06-18     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0213155     Medline TA:  Environ Sci Technol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1198-201     Citation Subset:  IM    
Affiliation:
Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo, Tokyo 113-8657, Japan. aomasa@mail.ecc.u-tokyo.ac.jp
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MeSH Terms
Descriptor/Qualifier:
Automation
Carbon / analysis*
Cedrus
Environmental Monitoring / methods*
Light
Sensitivity and Specificity
Trees*
Chemical
Reg. No./Substance:
7440-44-0/Carbon

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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