Applying LiDAR Individual Tree Detection to Management of Structurally Diverse Forest Landscapes-Reference-Cited by-同舟云学术

Applying LiDAR Individual Tree Detection to Management of Structurally Diverse Forest Landscapes

Published:2018-06-29 Issue:4 Volume:116 Page:336-346
ISSN:0022-1201
Container-title:Journal of Forestry
language:en
Short-container-title:

Author:

Jeronimo Sean M A¹^ORCID,Kane Van R¹,Churchill Derek J²,McGaughey Robert J³^ORCID,Franklin Jerry F¹

Affiliation:

1. School of Environmental and Forest Sciences, College of the Environment, University of Washington, Seattle, WA, USA

2. Washington State Department of Natural Resources, Wildfire Division, Olympia, WA, USA

3. USDA Forest Service, Pacific Northwest Research Station, University of Washington, Seattle, WA, USA

Funder

USDA Forest Service Pacific Southwest Research

National Park Service

Publisher

Oxford University Press (OUP)

Subject

Plant Science,Forestry

Link

http://academic.oup.com/jof/article-pdf/116/4/336/25106382/fvy023.pdf

Reference72 articles.

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2. Curvature analysis of LiDAR data for single tree species classification in alpine latitude forests. Laser scanning 2009;Barilotti;ISPRS J. Photogramm,2009

3. Seeing Central African forests through their largest trees;Bastin;Sci. Rep,2015

4. Estimating forest biomass using small footprint LiDAR data: An individual tree-based approach that incorporates training data;Bortolot;ISPRS J. Photogramm,2005

5. Prediction of species specific forest inventory attributes using a nonparametric semi-individual tree crown approach based on fused airborne laser scanning and multispectral data;Breidenbach;Remote Sens. Environ,2010

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