GEOBIA in the Era of Big EO Data

Dear colleagues,

Object Based Image Analysis (OBIA) – in the domain of remote sensing and Earth sciences often referred to GeOBIA, denoting the focus on Earth related data analysis – has meanwhile established as an elaborated methodology for the analysis of remote sensing data. In this context, GeOBIA is sometimes even seen as a paradigm of image analysis due to its way of knowledge incorporation in the image analysis process. The emergence, success and evolution of GeOBIA was strongly coupled with the increase of spatial, spectral and radiometric resolution of remote sensing data. New imaging technologies such as Very High Resolution (VHR) satellite images as well as UAV based imagery were contributing to the proliferation of GeOBIA in the RS community. Simultaneously, the amount of Earth related data gathered, and in particular the amount of EO data being captured and stored has increased exponentially and is still increasing, which makes a meaningful data handling and analysis of all these imaging data a challenging task. Likewise, the term Big Data Big data was originally associated with three key concepts often named as the three Vs: volume, variety, and velocity. That is, the sheer amount of data to be handled an analyzed cannot be handled with conventional methods and software of data storage, management and analysis. Often further Vs such as veracity were added to characterize Big Data. Thus, new technologies such as cloud computing and methods having their origin in Artificial Intelligence (AI) evolved in order to manage and analyze these huge data sets in a meaningful way. Despite the challenges Big EO data poses, its opportunities especially for monitoring, change detection and general multi-temporal image analysis are tremendous: they span a wide range starting from a better understanding of Earth related processes and ending with the improvement of early warning systems of hazards. Nevertheless, in order to draw full advantage of recent EO data in terms of information extraction, GeOBIA methods will certainly play a central role in the near future while simultaneously the Vs of Big EO Data will still remain a challenge for it.

At this background submissions of manuscripts are appreciated which cover not exclusively the following topics:

• Big Data management and GeOBIA
• Image (pre-) processing and Big EO data in the context of GeOBIA
• Application of GeOBIA algorithms and rule sets in Big EO data contexts
• Monitoring and change detection
• Image and data fusion
• Image segmentation
• Multi-scale image and data analysis
• AI methods in and for GeOBIA
• Cloud computing and GeOBIA
• Services and service management based on Big EO data and GeOBIA

Dr. Peter Hofmann
Prof. Dr. Wolfgang Dorner
Guest Editors

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