You are here: Home
/ Publication Information
Title: Classification accuracy for stratification with remotely sensed data
Author: Czaplewski, Raymond L. Ph.D.; Patterson, Paul L.;
Source: Forest Science. 49(3): 402-408
Publication Series: Scientific Journal (JRNL)
Description: Tools are developed that help specify the classification accuracy required from remotely sensed data. These tools are applied during the planning stage of a sample survey that will use poststratification, prestratification with proportional allocation, or double sampling for stratification. Accuracy standards are developed in terms of an “error matrix,” which is familiar to remote sensing specialists. In addition, guidance is provided to determine when new remotely sensed classifications are needed to maintain acceptable levels of statistical precision with stratification.
Keywords: forest inventory and monitoring, forest statistics
- 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.
XML: View XML
Czaplewski, Raymond L.; Patterson, Paul L. 2003. Classification accuracy for stratification with remotely sensed data. Forest Science. 49(3): 402-408
Get the latest version of the Adobe Acrobat reader or Acrobat Reader for Windows with Search and Accessibility