Multi-objective processing of ASTER image for urban environmental analysis

A framework of multi-objective processing and analysis of ASTER data for urban environmental analysis was proposed at first, and related key techniques were discussed. Five levels of multi-objective information processing were discussed. The first level is visualization-level combination, in which the simple combination of results of different objectives is used for visualization or better representation. The second level is coefficient-level combination, and it aims to derive some new parameters by the combination of results for different objectives. The third level is collaboration-level combination, in which the output from one process is feed into the other processes and to improve the performance. The fourth level is association-level combination with the aim of finding those association rules among the results of different processes by statistics and data mining. The fifth level is collaboration decision-level integration, and this level aims to monitor, analyze, manage and protect urban environment by integrating above data, rules, parameter and models. The multi-objective processing and analysis of ASTER data will bring more benefits for urban environment Remote Sensing applications than ever, and this framework and related information processing methods could be used to other fields further.