Remote Sensing Detection of Object Dynamic Change Based on Image Characteristic of Structural Functional Unit (SFU)

In high-resolution remote sensing image, the change of object structural functional unit (SFU) is an important indicative feature to measure the overall dynamic change of object. The research of the chronological phase characteristics of typical object SFU, provides information services for object identification and early warning in the field of intelligence analysis. Facing different types of object SFU, the spectral data of multi-temporal high-resolution remote sensing image were extracted as the sample data set, with the analytical method of Euclidean distance. This method detects the level of object type, SFU and chronological phase. The experimental results show that, by studying the spectral data of multi-temporal object SFU, the chronological phase can be detected reliably, as the type of the overall object can be identified in the medium term of construction. The analytical method of Euclidean distance can effectively detect the SFU of the whole object and effectively shorten the time to identify the object based on diagnostic SFU providing reference basis for the early identification of unknown object types and its construction phase.