AM-106 - Error-based Uncertainty

The largest contributing factor to spatial data uncertainty is error. Error is defined as the departure of a measure from its true value. Uncertainty results from: (1) a lack of knowledge of the extent and of the expression of errors and (2) their propagation through analyses. Understanding error and its sources is key to addressing error-based uncertainty in geospatial practice. This entry presents a sample of issues related to error and error based uncertainty in spatial data. These consist of (1) types of error in spatial data, (2) the special case of scale and its relationship to error and (3) approaches to quantifying error in spatial data.
DC-19 - Ground Verification and Accuracy Assessment
Spatial products such as maps of land cover, soil type, wildfire, glaciers, and surface water have become increasingly available and used in science and policy decisions. These maps are not without error, and it is critical that a description of quality accompany each product. In the case of a thematic map, one aspect of quality is obtained by conducting a spatially explicit accuracy assessment in which the map class and reference class are compared on a per spatial unit basis (e.g., per 30m x 30m pixel). The outcome of an accuracy assessment is a description of quality of the end-product map, in contrast to conducting an evaluation of map quality as part of the map production process. The accuracy results can be used to decide if the map is of adequate quality for an intended application, as input to uncertainty analyses, and as information to improve future map products.