A quantitative investigation of the uncertainty associated with mapping scale in the production of land-cover/land-use data

Mapping scale is an essential issue in land use and land cover (LULC) data production, which always involves the minimum mapping unit (MMU) that stipulated in the product specification. Since the application of MMUs will inevitably cause some inappropriate classification problems, a technique is needed to evaluate the impact on the data outputs. In this study, a novel method is proposed to investigate the classification uncertainty brought by MMUs on LULC data. The omission errors are predicted based on an assumption of the skewed frequency distribution of the LULC patch size, and the commission errors are subsequently computed through the conversion possibilities among different land classes, which can be deduced from the generalization rule. A test is conducted on real data to verify the underlying assumption on the patch size distribution, and the accuracy of the prediction of omission errors is evaluated through a simulation experiment. A case study is also presented to demonstrate the efficiency and feasibility of the proposed method. At the end of this article, the advantages and notes of this method are discussed for further study and application.