Reproducibility and Practical Adoption of GEOBIA with Open-Source Software in Docker Containers

Abstract

Geographic Object-Based Image Analysis (GEOBIA) mostly uses proprietary software, but the interest in Free and Open-Source Software (FOSS) for GEOBIA is growing. This interest stems not only from cost savings, but also from benefits concerning reproducibility and collaboration. Technical challenges hamper practical reproducibility, especially when multiple software packages are required to conduct an analysis. In this study, we use containerization to package a GEOBIA workflow in a well-defined FOSS environment. We explore the approach using two software stacks to perform an exemplary analysis detecting destruction of buildings in bi-temporal images of a conflict area. The analysis combines feature extraction techniques with segmentation and object-based analysis to detect changes using automatically-defined local reference values and to distinguish disappeared buildings from non-target structures. The resulting workflow is published as FOSS comprising both the model and data in a ready to use Docker image and a user interface for interaction with the containerized workflow. The presented solution advances GEOBIA in the following aspects: higher transparency of methodology; easier reuse and adaption of workflows; better transferability between operating systems; complete description of the software environment; and easy application of workflows by image analysis experts and non-experts. As a result, it promotes not only the reproducibility of GEOBIA, but also its practical adoption.

DOI: 10.3390/rs9030290

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Cite this paper

@article{Knoth2017ReproducibilityAP, title={Reproducibility and Practical Adoption of GEOBIA with Open-Source Software in Docker Containers}, author={Christian Knoth and Daniel N{\"{u}st}, journal={Remote Sensing}, year={2017}, volume={9}, pages={290} }