The impact of imperfect ground reference data on the accuracy of land cover change estimation

Error in the ground reference data set used in studies of land cover change can be a source of bias in the estimation of land cover change and of change detection accuracy. The magnitude of the bias introduced may be very large even if the ground reference data set is of a high accuracy. Sometimes the bias is of a predictable systematic nature and so may be reduced or even removed. The impacts of ground reference data error on the accuracy of estimates of the extent of change and on change detection accuracy were explored with simulated data. In one scenario illustrated, the producer's accuracy of change detection was estimated to be 61% when in reality it was 80%, the substantial underestimation of accuracy arising through the use of a ground reference data set with an accuracy of 90%. In the same scenario, the extent of change was also substantially overestimated at 26%, when in reality a change of only 20% had occurred. Reducing the effect of error in ground reference data will enable more accurate estimation of land cover change and a more realistic appraisal of the quality of remote sensing as a source of data on land cover change.