An open, scalable, and flexible framework for automated aerial measurement of field experiments
| Autor: | David Shaner LeBauer, Christophe Schnaufer, Julian Pistorius |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
EarthArXiv|Life Sciences|Plant Sciences|Plant Breeding and Genetics Life Sciences
Computer science bepress|Engineering Interoperability EarthArXiv|Engineering bepress|Life Sciences|Ecology and Evolutionary Biology EarthArXiv|Life Sciences|Ecology and Evolutionary Biology EarthArXiv|Life Sciences|Plant Sciences|Agricultural Science Bottleneck Software bepress|Life Sciences EarthArXiv|Engineering|Bioresource and Agricultural Engineering bepress|Life Sciences|Plant Sciences|Plant Breeding and Genetics Life Sciences EarthArXiv|Life Sciences EarthArXiv|Life Sciences|Ecology and Evolutionary Biology|Terrestrial and Aquatic Ecology bepress|Life Sciences|Research Methods in Life Sciences bepress|Engineering|Bioresource and Agricultural Engineering bepress|Life Sciences|Ecology and Evolutionary Biology|Terrestrial and Aquatic Ecology business.industry bepress|Life Sciences|Plant Sciences|Agricultural Science EarthArXiv|Life Sciences|Agriculture Automation Pipeline (software) Drone bepress|Life Sciences|Agriculture Workflow EarthArXiv|Life Sciences|Plant Sciences Scalability EarthArXiv|Life Sciences|Research Methods in Life Sciences bepress|Life Sciences|Plant Sciences Software engineering business |
| Popis: | Unoccupied areal vehicles (UAVs or drones) are increasingly used in field research. Drones capable of routinely and consistently capturing high quality imagery of experimental fields have become relatively inexpensive. However, converting these images into scientifically useable data has become a bottleneck. A number of tools exist to support this workflow, but there is no framework for making these tools interopreable, sharable, and scalable. Here we present an initial draft of the Drone Processing Pipeline (DPP), a framework for processing agricultural research imagery that supports best practices and interoperability. DPP emphasizes open software and data that can be shared among and used in whole or part by the research community. We are building the DPP as a distributed, scalable, and flexible pipeline for converting drone imagery into orthomosaics, point clouds, and plot level statistics. Our intent is not to replace, but to integrate components from the emerging ecosystem of utilities with a focus on end-to-end automation and scalability. The initial focus of DPP is the measurements of experimental plots in field research. In the future we expect that standardization will enable new scientific discovery by facilitating collaboration and sharing of software and data. Our vision is to create a processing pipeline that is open, flexible, extensible, portable, and automated. With modern tools, deploying a pipeline on a laptop or HPC should only take a single command. Running a pipeline and publishing data should require only input data and a defined workflow. |
| Databáze: | OpenAIRE |
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