Multi-temporal Remotely Sensed Data Processing System

Remote sensing provides huge multi-temporal data for earth surface, which has not been used completely. In the study, based on Visual C++ and Geographic Information System (GIS) platform, a multi-temporal data processing system using Grey Model (GM) is developed. By the interactive system, some functions, such as data input/output, visualization, simulation, prediction, data transformation, comparison, and analysis, are carried out. Specifically, a Generalization GM (GGM), an extension of GM, is applied to process unequal time interval data. The procedure of “line-basic line-line” is also proposed to analyze the raster images, where every row or column of the image is taken as one basic line, a minimal unit of this system. With the help of GIS, the vector data can be processed together with raster data. At last, the system we developed is applied successfully to urban growth prediction by multi-temporal remotely sensed data.