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Authors: Hemang Narendra Vithlani 1 ; Marcel Dogotari 1 ; Olee Hoi Ying Lam 1 ; Moritz Prüm 1 ; Bethany Melville 2 ; Frank Zimmer 1 and Rolf Becker 1

Affiliations: 1 Faculty of Communication and Environment, Rhine-Waal University of Applied Sciences, 47475 Kamp-Lintfort, Germany ; 2 Astron Environmental Services, 129 Royal Street, East Perth Western Australia, 6004, Australia

ISBN: 978-989-758-425-1

Keyword(s): Drone Imagery, Opendronemap, Photogrammetry, Open-source, Kubernetes, Cloud Computing.

Abstract: Aerial images acquired using drone-based imaging sensors can be processed by photogrammetry toolkits to create geometrically corrected 2D orthophoto and/or 3D models. This is a crucial step for many of the ever-evolving civil applications of drones such as precision agriculture and surveying. Nevertheless, limited computational resources become bottleneck in providing these results quickly. Cloud computing helps in such scenarios because of its value-added features, namely virtualization, elasticity, high performance and distributed computing for the web-based image processing. The containerization approach plays a vital role in cloud computing by providing operational efficiency. Container orchestration engine, Kubernetes, not only provides template-based or GUI-based service deployment but also better monitoring, log querying and auto-scaling. The present work displays a scalable photogrammetry service, deployed on a Kubernetes-orchestrated on-premise cluster. This reference impleme ntation on Kubernetes enables the parallel processing of large datasets in less time than a single computer using the free and open-source toolkit OpenDroneMap. (More)

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Paper citation in several formats:
Vithlani, H.; Dogotari, M.; Lam, O.; Prüm, M.; Melville, B.; Zimmer, F. and Becker, R. (2020). Scale Drone Mapping on K8S: Auto-scale Drone Imagery Processing on Kubernetes-orchestrated On-premise Cloud-computing Platform.In Proceedings of the 6th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM, ISBN 978-989-758-425-1, pages 318-325. DOI: 10.5220/0009816003180325

@conference{gistam20,
author={Hemang Narendra Vithlani. and Marcel Dogotari. and Olee Hoi Ying Lam. and Moritz Prüm. and Bethany Melville. and Frank Zimmer. and Rolf Becker.},
title={Scale Drone Mapping on K8S: Auto-scale Drone Imagery Processing on Kubernetes-orchestrated On-premise Cloud-computing Platform},
booktitle={Proceedings of the 6th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,},
year={2020},
pages={318-325},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009816003180325},
isbn={978-989-758-425-1},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,
TI - Scale Drone Mapping on K8S: Auto-scale Drone Imagery Processing on Kubernetes-orchestrated On-premise Cloud-computing Platform
SN - 978-989-758-425-1
AU - Vithlani, H.
AU - Dogotari, M.
AU - Lam, O.
AU - Prüm, M.
AU - Melville, B.
AU - Zimmer, F.
AU - Becker, R.
PY - 2020
SP - 318
EP - 325
DO - 10.5220/0009816003180325

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