Geographic Object-based Image Analysis (GEOBIA): Emerging trends and future opportunities
Gang Chen a, Qihao Weng b, Geoffrey J. Hay c, Yinan He a
a Laboratory for Remote Sensing and Environmental Change (LRSEC), Department of Geography and Earth Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
b Center for Urban and Environmental Change, Department of Earth and Environmental Systems, Indiana State University, Terre Haute, IN 47809, USA
c Department of Geography, University of Calgary, Calgary, AB T2N 1N4, Canada
Abstract:
Over the last two decades (since circa 2000), Geographic Object-Based Image Analysis (GEOBIA) has emerged as a new paradigm to analyzing high-spatial resolution remote sensing imagery. During this time, research interests have demonstrated a shift from the development of GEOBIA theoretical foundations to advanced geo-object-based models and their implementation in a wide variety of real-world applications. We suggest that such a rapid GEOBIA evolution warrants the need for a systematic review that defines the recent developments in this field. Therefore, the main objective of this paper is to elucidate the emerging trends in GEOBIA, and discuss potential opportunities for future development. The emerging trends were found in multiple sub-fields of GEOBIA, including data sources, image segmentation, object-based feature extraction, and geo-object-based modeling frameworks. It is our view that understanding the state-of-the-art in GEOBIA will further facilitate and support the study of geographic entities and phenomena at multiple scales with effective incorporation of semantics, informing high-quality project design, and improving geo-object-based model performance and results.