Accuracy assessment of mixed land cover using a GIS-designed sampling scheme

Land cover maps, based on remotely sensed data, are widely developed and used for studying global ecosystems and land use/land cover change. However, accuracy assessment of mixed land cover classes, including varying dominance of invasive species, is complicated by uncertainty about where to define a threshold of presence/absence. Geographic Information Science (GIS) can be used to target sampling locations that encompass a range of mixed pixels, but are also easily accessible for an efficient accuracy assessment. Here, an accuracy assessment of a Landsat-derived map of the invasive species cheatgrass (Bromus tectorum) in the state of Nevada, USA is presented. The stratified random design used GIS to increase efficiency by limiting the target area while still sampling the distribution of mixed pixels present in the larger study area, and a receiver operating characteristic (ROC) curve was used to assess overall map accuracy with different thresholds of cheatgrass presence/absence. This approach is useful for validating map accuracy in the presence of mixed pixels.