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Ground reference data error and the mis-estimation of the area of land cover change as a function of its abundance

Area estimation is a common application of remote sensing especially in relation to studies of land cover change. The use of an imperfect, nongold-standard, reference is shown to be a source of substantial error in estimates of change area. The relationships between the accuracy of land cover classifications, both real and perceived, together with area of change are explored over the full range of change abundance. The magnitude of mis-estimation varies with the abundance of change and the quality of the data sets used but may be large. For scenarios based on realistic values of data set quality for the common situation in which change is rare, ≤1%, change area was overestimated by up to two orders of magnitude because of reference data error. The results highlight that the ability of remote sensing to provide accurate information on change area is limited by reference data error and is, in part, a function of change abundance.