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 (299 KB)

Title: Moderate-resolution data and gradient nearest neighbor imputation for regional-national risk assessment

Author: Pierce, Kenneth B. Jr.; Brewer, C. Kenneth; Ohmann, Janet L.;

Date: 2010

Source: In: Pye, John M.; Rauscher, H. Michael; Sands, Yasmeen; Lee, Danny C.; Beatty, Jerome S., tech. eds. 2010. Advances in threat assessment and their application to forest and rangeland management. Gen. Tech. Rep. PNW-GTR-802. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest and Southern Research Stations: 111-121

Publication Series: General Technical Report (GTR)

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

Description: This study was designed to test the feasibility of combining a method designed to populate pixels with inventory plot data at the 30-m scale with a new national predictor data set. The new national predictor data set was developed by the USDA Forest Service Remote Sensing Applications Center (hereafter RSAC) at the 250-m scale. Gradient Nearest Neighbor (GNN) imputation was designed by the USDA Forest Service Pacific Northwest Research Station (hereafter PNW) to assign a plot identifier, and, therefore, a link to associated plot data, to each pixel within a target raster. Gradient Nearest Neighbor was implemented at 30-m resolution in three separate multimillion-hectare regions of the Western United States. Concurrently, RSAC developed a set of spatial predictor surfaces at 250-m resolution for use in producing nationally consistent data products. These data have been used for modeling forest types and forest biomass for the conterminous United States and Alaska. These predictor data have also been used for large regional applications. In this study, we substituted the 250-m predictor data for the 30-m predictor data used thus far in GNN. Our objective was to quantify the difference in performance using the lower spatial resolution predictors. We remodeled the same three regions that were mapped at 30 m with the 250-m data set and compared the error structure of the two modeling efforts. For species presence/absence models in the two areas with large environmental gradients, the Sierra Nevada and northeastern Washington, the species models performed substantially the same at the two resolutions. For the region with reduced environmental heterogeneity and moderate environmental gradients, coastal Oregon, species models did not work well with either the 30-m or 250-m studies. Models geared towards mapping forest structure did not perform as well as the 30-m models and may be insufficient for risk-assessment use.

Keywords: Gradient Nearest Neighbor, imputation, regional analysis, species distributions, vegetation mapping.

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 pnw_pnwpubs@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:


Pierce, Kenneth B. Jr.; Brewer, C. Kenneth; Ohmann, Janet L. 2010. Moderate-resolution data and gradient nearest neighbor imputation for regional-national risk assessment. In: Pye, John M.; Rauscher, H. Michael; Sands, Yasmeen; Lee, Danny C.; Beatty, Jerome S., tech. eds. 2010. Advances in threat assessment and their application to forest and rangeland management. Gen. Tech. Rep. PNW-GTR-802. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest and Southern Research Stations: 111-121.

 


 [ 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.