Skip to page content
USDA Forest Service
  
Treesearch

Research & Development Treesearch

 
Treesearch Home
About Treesearch
Contact Us
Research & Development
Forest Products Lab
International Institute of Tropical Forestry
Northern
Pacific Northwest
Pacific Southwest
Rocky Mountain
Southern Research Station
Help
 

Science.gov - We Participate


USA.gov  Government Made Easy


Global Forest Information Service

US Forest Service
P.O. Box 96090
Washington, D.C.
20090-6090

(202) 205-8333

You are here: Home / Search / Publication Information
Bookmark and Share

Publication Information

View PDF (599 KB)

Title: A comparison of forest height prediction from FIA field measurement and LiDAR data via spatial models

Author: Li, Yuzhen;

Date: 2009

Source: In: McWilliams, Will; Moisen, Gretchen; Czaplewski, Ray, comps. Forest Inventory and Analysis (FIA) Symposium 2008; October 21-23, 2008; Park City, UT. Proc. RMRS-P-56CD. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 14 p.

Publication Series: Proceedings (P)

   Note: This article is part of a larger document. View the larger document

Description: Previous studies have shown a high correspondence between tree height measurements acquired from airborne LiDAR and that those measured using conventional field techniques. Though these results are very promising, most of the studies were conducted over small experimental areas and tree height was measured carefully or using expensive instruments in the field, which is not feasible in a practical forest inventory context. In this study, 105 plots located west of the Kenai Mountains, Kenai Peninsula, Alaska were measured and LiDAR data over the same set of field plots were acquired. Plot tree height, stand height, LiDAR mean height and LiDAR 90th percentile height were computed. Using the Matern covariance model for constant mean Gaussian spatial process, ordinary kriging was implemented and contour maps of predicted plot-level height from field height measurements and from LiDAR data were produced over the entire region along with maps of estimated standard error. Results indicate that at 300m by 300m pixel resolution, the spatial trends of predicted plot-level height are similar between field measurements and LiDAR measurements. The distribution of predicted stand height is very similar to the distribution of predicted LiDAR mean height with mean difference of only 0.28m. The mean of predicted plot tree height is comparable to the mean of predicted LiDAR 90th percentile height, but the distribution of predicted LiDAR 90th percentile height has much heavier tails.

Keywords: LiDAR, plot-level height, gaussian process, ordinary kriging

Publication Notes:

  • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
  • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
  • You may send email to rmrspubrequest@fs.fed.us to request a hard copy of this publication. (Please specify exactly which publication you are requesting and your mailing address.)

XML: View XML

Citation:


Li, Yuzhen. 2009. A comparison of forest height prediction from FIA field measurement and LiDAR data via spatial models. In: McWilliams, Will; Moisen, Gretchen; Czaplewski, Ray, comps. Forest Inventory and Analysis (FIA) Symposium 2008; October 21-23, 2008; Park City, UT. Proc. RMRS-P-56CD. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 14 p.

 


 [ Get Acrobat ]  Get the latest version of the Adobe Acrobat reader or Acrobat Reader for Windows with Search and Accessibility

USDA logo which links to the department's national site. Forest Service logo which links to the agency's national site.