Skip to page content
USDA Forest Service

Research & Development Treesearch

Treesearch Home
About Treesearch
Contact Us
Research & Development
Forest Products Lab
International Institute of Tropical Forestry
Pacific Northwest
Pacific Southwest
Rocky Mountain
Southern Research Station
Help - We Participate  Government Made Easy

Global Forest Information Service

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

(202) 205-8333

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

Publication Information

View PDF (525 KB)

Title: A framework for simulating map error in ecosystem models

Author: Healey, Sean P.; Urbanski, Shawn P.; Patterson, Paul L.; Garrard, Chris;

Date: 2014

Source: Remote Sensing of Environment. 150: 207-217.

Publication Series: Scientific Journal (JRNL)

Description: The temporal depth and spatial breadth of observations from platforms such as Landsat provide unique perspective on ecosystem dynamics, but the integration of these observations into formal decision support will rely upon improved uncertainty accounting. Monte Carlo (MC) simulations offer a practical, empirical method of accounting for potential map errors in broader ecosystem assessments. However, unless steps are taken across simulations to vary the probability density functions (PDFs) that control simulated map error, the large number of map units to which those PDFs are applied may cause convergence of mean simulated conditions and an artificial reduction of MC estimates of uncertainty. For MC simulation of errors in categorical maps, we introduce a technique we call "PDF weaving" which both: 1) allows variation of PDFs across simulations; and, 2) explicitly aligns the resulting range of simulated populations with estimates and uncertainties identified by traditional monitoring methods such as design-based inventories. This approach is based on solving systems of linear equations and inequalities for each simulation. Each system incorporates linear constraints related to the unchanging distribution of area among classes in the original map (akin to the fixed longitudinal "warp" on a loom)with variable linear constraints related to the class distribution to be simulated in any one iteration (analogous to the perpendicular, variable fibers of the "weft"). Additional constraints specify how many map units to treat as "correct" based on validation exercises at the map unit level. Solution of these systems provides PDFs which will simulate error at both the map unit level and the population level in a way that is consistent with validation exercises and available population-level estimates. We illustrated this approach in an assessment of the effects of wildfire and harvest on carbon storage over 20 years on a forested landscape in the western United States (US). This assessment utilized the Forest Carbon Management Framework (ForCaMF) approach, which is being implemented by the US National Forest System (NFS). Results showed that simulating map error through the use of dynamic PDFs can contribute significant, realistic uncertainty in a Monte Carlo analysis, but that impacts of fire and harvest on carbon storage may nevertheless be clearly identified and differentiated using remotely sensed maps of vegetation and disturbance.

Keywords: Monte Carlo, Landsat, change detection, carbon

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.



Healey, Sean P.; Urbanski, Shawn P.; Patterson, Paul L.; Garrard, Chris. 2014. A framework for simulating map error in ecosystem models. Remote Sensing of Environment. 150: 207-217.


 [ 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.