OpenDroneMap (ODM) aims to allow humanitarian users to process UAV imagery and push those products to other platforms and projects for crowdsourcing.
Effective disaster preparedness, monitoring, relief coordination, as well as damage assessments are predicated on reliable, uptodate geographic information that marries well with on ground knowledge. The highly detailed imagery available from unmanned aerial vehicles well fits this predicate due to high level of spatial detail, flexibility in requisition, and image quality.
The detailed, cloud-free view that unmanned aerial vehicles (UAVs) provide is useful for disaster preparedness because it has great potential for field tactics (eg determining the best possible route for a convoy), and is useful for allocation of resources for relief coordination (eg damage assessment and determining most affected areas).
Additionally, processed UAV imagery can result in a unique additional product—three dimensional (3D) point clouds, digital surface models, and digital elevation models—required for natural disaster preparedness planning and societal and infrastructure vulnerability assessments.
The outcomes that we seek with OpenDroneMap are faster and more informed decisions for humanitarian relief efforts. We expect that better, more detailed, more relevant, and more flexible mapping efforts as provided by UAVs will aid in those faster and better informed decisions.
OpenDroneMap will be a platform to produce software and required documentation capable of end-to-end UAV imagery processing (from data to map) suitable for use by humanitarian organisations during disaster planning and relief efforts.
By shortening and simplifying UAV imagery delivery and analysis, OpenDroneMap will support the scalability of crisis mapping and will have the capacity to augment preparedness projects, like MissingMaps, with high resolution imagery.
The aim of this project is to advance the state of the art with respect to the use of OpenDroneMap in the humanitarian context in 4 areas: improve usability, improve and validate data quality, integrate with existing humanitarian tools, and improve the scalability of OpenDroneMap.View
In addition to improved dense point cloud generation, improved mesh generation, and orthophotos; ShadowView have worked toward improved texturing and the integration of an external library to aid in user image classification.View
WebODM is under rapid development, recently additional allowance has been created for advanced interaction with the 3D point clouds and meshes that OpenDroneMap produces, allowing for measurements to be taken directly on the models.View
The OpenDroneMap team introduce us to some use cases of drone image processingView
ShadowView have created a split merge feature for their OpenDroneMap, which processes subsets of data that are geographically aligned and produces a single aerial mapsView
The OpenDroneMap team look back on their recently ended project, and share how they have developed their software over the last two yearsView
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