Enabling reproducible obia with open-source software in docker containers

Knoth, Christian; Nüst, Daniel

doi:10.3990/2.456

Cited by 3 publications

(2 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The most well-known approach to software containers is Docker [23]. This does not only allow running application on different environments, but also supports archiving strategies that can ensure reproducibility and replicability [24].…”

Section: B Improving Reproducibilitymentioning

confidence: 99%

Reproducibility and Replicability in SAR Remote Sensing

Balz

Rocca

2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

Modern science is built on systematic experimentation and observation. Today's form of communicating scientific results with written articles is the foundation we build our work on. The reproducibility and replicability of the experiments and observations are central to this process of validation. However, reproducibility and replicability are not always guaranteed, sometimes referred to as 'crisis of reproducibility'. We believe that remote sensing in general suffers from this crisis. To analyze the extent of the crisis, we conducted a survey on the state of reproducibility in remote sensing. Based on this survey we map the problem of reproducibility with a focus on SAR remote sensing, as this is our area of research. We also give advice on how to improve reproducibility in remote sensing.

show abstract

Section: B Improving Reproducibilitymentioning

confidence: 99%

Reproducibility and Replicability in SAR Remote Sensing

Balz

Rocca

2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Finally, we discuss the solution and the challenges (Section 4), and conclude with a summary and outlook in Section 5. This paper is an extended version of our contribution to the GEOBIA 2016 conference [44].…”

Section: Contribution and Overviewmentioning

confidence: 99%

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

Knoth

Nüst

2017

Remote Sensing

Self Cite

View full text Add to dashboard Cite

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.

show abstract