Estimating Canopy Cover from Standard Forest Inventory Measurements in Western Oregon Public Deposited

http://ir.library.oregonstate.edu/concern/defaults/1j92g805s

To the best of our knowledge, one or more authors of this paper were federal employees when contributing to this work. This is the publisher’s final pdf. The published article is copyrighted by Society of American Foresters and can be found at:  http://www.safnet.org/.

Descriptions

Attribute NameValues
Creator
Abstract or Summary
  • Reliable measures of canopy cover are important in the management of public and private forests. However, direct sampling of canopy cover is both labor- and time-intensive. More efficient methods for estimating percent canopy cover could be empirically derived relationships between more readily measured stand attributes and canopy cover or, alternatively, the use of aerial photos. In this study, we compared field-based measures of percent canopy cover with estimates from aerial photography, with equations of individual tree crown width and crown overlap used in the US Forest Service Forest Vegetation Simulator (FVS) equations and with models we developed from standard stand-level forest mensuration estimates. Standard inventory estimates of cover using 1:40,000 scale aerial photos were poorly correlated with field-measured cover, especially in wet hardwood (r = 0.60) and dry hardwood (r = 0.51) stands. FVS equations underestimated cover by 17% on average at high cover levels (>70%) in wet conifer and wet hardwood stands. We also developed predictive models of canopy cover for three forest groups sampled on 884 plots by the Forest Inventory and Analysis program in western Oregon: wet conifer, wet hardwood, and dry hardwood. Predictions by the models were within 15% of measured cover for >82% of the observations. Compared with previous studies modeling canopy cover, our best predictive models included species-specific stocking equations, whereas species-invariant basal area was not an important predictor for most forest types. Accuracies of these new predictive models may be adequate for some purposes, reducing the need for direct measures of canopy cover in the field.
Resource Type
DOI
Date Available
Date Issued
Citation
  • McIntosh, A., Gray, A., & Garman, S. (2012). Estimating canopy cover from standard forest inventory measurements in western oregon. Forest Science, 58(2), 154-167. doi: 10.5849/forsci.09-127
Academic Affiliation
Series
Keyword
Rights Statement
Publisher
Peer Reviewed
Language
Replaces
Additional Information
  • description.provenance : Approved for entry into archive by Deborah Campbell(deborah.campbell@oregonstate.edu) on 2013-01-16T19:04:49Z (GMT) No. of bitstreams: 1 GarmanStevenLForestEcosystemsSocieetyEstimatingCanopyCover.pdf: 1102242 bytes, checksum: f4c223829e5e8dc9dcc5501de3f6805d (MD5)
  • description.provenance : Submitted by Deborah Campbell (deborah.campbell@oregonstate.edu) on 2013-01-16T18:39:46Z No. of bitstreams: 1 GarmanStevenLForestEcosystemsSocieetyEstimatingCanopyCover.pdf: 1102242 bytes, checksum: f4c223829e5e8dc9dcc5501de3f6805d (MD5)
  • description.provenance : Made available in DSpace on 2013-01-16T19:04:49Z (GMT). No. of bitstreams: 1 GarmanStevenLForestEcosystemsSocieetyEstimatingCanopyCover.pdf: 1102242 bytes, checksum: f4c223829e5e8dc9dcc5501de3f6805d (MD5) Previous issue date: 2012-02-02

Relationships

In Administrative Set:
Last modified: 07/08/2017

Downloadable Content

Download PDF
Citations:

EndNote | Zotero | Mendeley

Items