University of New Hampshire Scholars Repository (University of New Hampshire at Manchester) · 1993 · 197 citations · 0 references
ComputingGeographyGeoinformaticsGeographic Information ScienceGeographic Information SystemsRemote SensingLand Cover ClassificationRemote Sensing For Forest InventoryClassification Accuracy AssessmentCommission ErrorsForest Cover ClassificationGeographic Information System DataRemote Sensing-based AssessmentSpatial Accuracy AssessmentSpatial Data Quality AssessmentUncertainty Analysis In Gis
The need for assessing the accuracy of spatial data derived from remote sensing techniques and used in geographic information system (GIS) analyses has been recognized as a critical component of many projects. The results of this assessment are typically represented by an error matrix presenting the overall accuracy, the accuracies of each category, and the omission and commission errors. This paper presents a discussion of the various sources of confusion that are represented within an error matrix. Ideally, the matrix is representative of only classification error. However, other factors can be significant and substantially lower the accuracy as represented by the matrix. An example is presented from mapping old growth forests on the Rogue River National Forest in Oregon.