DEDAL documentation
Distributed Ecosystem for Drone Analytics in Life-sciences: what it does, how it works, and how to use it.
What DEDAL is
DEDAL is the John Innes Centre's platform for processing and phenotyping drone imagery, for UK crop-genetics researchers and farmers. Upload a flight's images and DEDAL produces orthomosaics, a surface model and vegetation indices; for DJI Mavic 3M multispectral flights it first calibrates the images to reflectance, and it extracts per-plot values for field trials. Flights can be taken further in DEDAL-Lab (RStudio) or opened in QGIS as ready-made projects.
Getting startedStep by step, with screenshots: account, processing, calibration, plot extraction, DEDAL-Lab, QGIS.
Calibration methodThe algorithm, quality checks, validation and text for your methods section.
Processing and productsInputs, photogrammetry settings, outputs and formats, plot extraction, QGIS projects, DEDAL-Lab.
ReferencePanel files, thresholds, extraction columns, plot sheets and layouts, QGIS project files, limits.
TroubleshootingCommon problems and what to do.
Software and citationComponents, versions, licences, source code and how to cite DEDAL.
How it fits together
- Built on (third-party, open source): OpenDroneMap (photogrammetry: ODM, WebODM, NodeODM, ClusterODM), QGIS (desktop GIS, for the downloaded projects), RStudio Server and FIELDimageR.Extra (in DEDAL-Lab).
- Developed for DEDAL: the reflectance calibration of DJI Mavic 3M images and its quality checks (dedal-calibration), the WebODM plugins (panel calibration, plot extraction, DEDAL-Lab, QGIS projects), the delivery of the camera's factory lens to the processing nodes, the website and account system, DEDAL-Lab's on-demand sessions, and the cluster pipeline that processes whole seasons with the same settings.
DEDAL is not officially associated with OpenDroneMap or its products.