Automatic Change Detection of Remote Sensing Image Integrated with Process Optimization

At present, the method for extract change spot with remote imagery, in the law enforcement of land use, is mainly making full use of the operators' visual interpretation of the two high-resolution remote sensing imageries, to get the spatial position of the land use change. Therefore, whether the spots are right or not, it is easy to generate errors, depends by the experience of the interpreters. With general detection process, there is a good result for the particular remote sensing data. But handling the city's remote sensing image on a large scale, with various characteristics, and higher resolution, this detection method seems to be limited and hard to be applied. This paper presents a remote sensing imagechange detection process which includes two main parts:remote sensing image human-computer interactive change detection and batch automatic detection. The system has integrated thought of process optimization and the existing remote sensing image change detection methods, and used a large number of high-precision GIS data accumulated during the development of digital city, which is fully combined with the features' shape index and people's working experience. It has been applied to the extraction of land use change spot in law enforcement inspection of satellite land image in Shenzhen, improved the level of automation, and reduced the time and labor costs effectively, which is helpful for the related government to find andprevent the occurrence of illegal land use in time.