A Spectral and Textural Knowledge-Based Approach for Automated Extraction of Topographical Factors from Remotely Sensed Images

摘要

A prototype expert system is developed to demonstrate the feasibility of classifying multispectral remotely sensed data on the basis of spectral and textural knowledge. In this paper, the spectral and textural properties of settlement place, vegetation, water area, soil, etc. are discussed and a production algorithm of texture image is studied. According to the relationships of hand-to-hand and category-to-texture, a knowledge base represented by rules and weights is established. The method presented in this paper is of fast computation speed and high classification accuracy.