Object-Oriented Approach and Texture Analysis for Change Detection in Very High Resolution Images

The objective of this paper is to develop an object-based change detection method able to qualify the nature of changes in landscapes from remotely sensed images, in terms of geometry and content. The originality of the approach consists in jointly dealing with the analysis of the object contours and the analysis of texture evolution. The method is applied on grassy strips, which are landscape buffers between crops and hydrologic networks. A geometric change index that quantify the intensity of change and that qualify it according its properties is proposed. We also present a content change index that discriminates partial change from diffuse change that affect the object of interest. It turned out that the geometric changes, most of abrupt content changes and some of subtle changes have been accurately detected. Lastly, our approach is suitable on airborne data with a Very High Resolution data and can be generalized to spaceborne images.