This chapter explores the need for automation processes in information extraction from remote sensing images. This exploration is further extended by developing an ontological framework for geographic object-based image analysis (GEOBIA). GEOBIA provides a method to identify real-world geographic objects from remote sensing imagery. It uses the same technique as a human does to perceive different geo-objects and to distinguish them. Thus, human involvement in the form of expert knowledge will be required during image object identification. This need for human intervention is addressed by employing a knowledge representation language such as ontology to formalize human expert knowledge. After formalization, necessary rule sets for image interpretation are developed. Using rule-based classification, no human assistance is required at the time of image object identification, which transforms GEOBIA into an automated process. The proposed framework is applied to an urban case study on land use/land cover (LULC) from Hobart, Tasmania, Australia.