Information measurement of classification maps and scale effects

For a particular application, data of appropriate scale need to be selected. And the quality of a thematic map is closely related with the classification accuracy of a primary classification map and the amount of information contained in it. Starting from the information theory, this paper has studied the methods for measuring the information in a classification map and the relationship between scale and information amount of a classification map. It has analyzed the law of how the information amount of a classification map changes with the image scales. After analysis, the following conclusion has been reached: whatever classification map, whether the total information amount or the average information amount, with the increase of the resampling scale, the amount of information will reduce. This paper can provide useful reference for information measurement of a map and for how to choose right map scale.