Research on adaptation criteria generation based on large data mining

Abstract

This paper performs research on adaptation analysis based on large amount of multi-source remote sensing data. In view of different demands from different task background, the research is firstly focused on how to analyze the data in computer language. To achieve this, the feature parameters of target areas are extracted from different target area geographic data. In combination of ORACLE database engine, data mining technology is used to carry out the target area adaptation assessment, and extract corresponding adaptation criteria. We test the trained adaptation criteria on multi-source geographic information data of different target areas. Experimental results show that the resulting criterion has certain coincidence rate and robustness.