Evaluation of the Efficiency of Object-Based Classification in the Identification of Geological Structures Case Study: Extraction of the Morphology of the Normal Faults

摘要

Object-based classification is a promising methodology. Unlike pixel-based techniques which only use the layer pixel values, the object-based techniques can also use shape and context information of a scene texture. These degrees of freedom provided by the objects will aid the identification of geological structures. In this article, we present an evaluation of object-based classification in the context of extracting morphology of geological faults. An automatic classification procedure is prepared to extract the faults. The DEM and radar images of an area near Lake Magadi, Kenya, are processed separately to identify which of them is a better candidate for mapping faults. Further, after classifying the faults, it is interesting to see how the notion of an object helps in determining the statistics of the faults populations.