Landscape-scale parameterization of a tree-level forest growth model: a k-nearest neighbor imputation approach incorporating LiDAR data

Journal article

Peer reviewed

Michael J Falkowski, Andrew Thomas Hudak, Nicholas L Crookston, Paul E Gessler, Edward H Uebler and Alistair M S Smith

Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere, Vol.40(2), pp.184-199

2010

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http://dx.doi.org/10.1139/X09-183View

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Title: Landscape-scale parameterization of a tree-level forest growth model: a k-nearest neighbor imputation approach incorporating LiDAR data
Creators: Michael J Falkowski - Michigan Technological University
Andrew Thomas Hudak - Rocky Mountain Research Station
Nicholas L Crookston - Michigan Technological University
Paul E Gessler - University of Idaho
Edward H Uebler
Alistair M S Smith - University of Idaho
Publication Details: Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere, Vol.40(2), pp.184-199
Identifiers: 996631738501851
Academic Unit: Idaho Experimental Partnership to Stimulate Competitive Research; Earth and Spatial Sciences; Institute for Health in the Human Ecosystem; Forest, Rangeland, and Fire Sciences; Institute for Modeling Collaboration and Innovation; Idaho Fire Institute for Research and Education
Language: English
Resource Type: Journal article