Multi-feature Space-based Remote Sensing Thematic Information Automatic Extraction Of Research

Remotely sensed imagery is the most immediate and abundant carrier of integrated information for ground target, and extracting terrain and thematic information from it automatically is an impending and complicated problem for remote sensing and GIS. Along with the quick development of remotely sensed obtaining technology in outer space, which provides more and more data, study personnel can get little effective information synchronously yet. Automatic extraction of thematic information from remotely sensed data has become bottleneck in Remotely sensed information production flow. Extraction method based on spectral character and single target figure character has been developed many years, but interpretation impact is short of anticipation desire despite of getting some evolution.This paper studied Remotely sensed information expression of object manifold recognition characters, analyzed allude relation between Remotely sensed imagery and target multi-characters space, put forward the study method of automatic Remotely sensed thematic information extraction based on multi-characters space. According to the evaluation for corn thematic information supervised classification result, with the analysis of influencing factors to corn spatial distributing, this paper brought forward automatic extraction model of corn thematic information based on multi-characters space, built the relevant expert knowledge storeroom and finished automatic classification of TM imagery thematic information using it. Comparing this classification result with the manpower visual interpretation, it was found that the former could improve efficiency of thematic information extraction, at the same time, this method was significant theoretically and also an innovation in automatic interpretation of remotely sensed imagery.This paper was divided into four chapters as follows: The first chapter summarized the present study and development direction about automatic interpretation of remote sensed imagery, and then explained the main study content, significance, aim and study method in this paper. The second chapter expatiated expression of manifold Remotely sensed information about ground targets, brought forward a method of thematic information extraction based on multi-characters space and constructed automatic extraction model of Remotely sensed thematic information based on multi-characters space. The third chapter took corn infield as researchobject, carried out thematic information extraction automatically by setting up corn extraction model, compared it with the extraction result of corn supervised classification, generalized the characters of automatic extraction method. The fourth chapter summarized study content of this paper, its innovation and stated the conclusion of this paper.