Using Spatial Autocorrelation Analysis to Explore the Errors in Maps Generated from Remotely Sensed Data
Three data sets of varying spatial complexity, including an agricultural area, a range area, and a forest area, were chosen for investigation in this study. A difference image was generated for each data set by comparing a Landsat classification with an assumed correct reference classification and noting the agreement and disagreement. Visual inspection and spatial autocorrelation analysis were used to identify and quantify the patterns of error within each difference image. This information is very important when land cover maps generated from remotely sensed data are sampled for accuracy assessment.
Natural Resources and the Environment
Photogrammetric Engineering and Remote Sensing
American Society for Photogrammetry and Remote Sensing and Remote Sensing
Congalton, R. 1988. Using spatial autocorrelation analysis to explore errors in maps generated from remotely sensed data. Photogrammetric Engineering and Remote Sensing. Vol. 54, No. 5, pp. 587-592.
©1988 American Society for Photogrammetry and Remote Sensing