This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1117/12.2560008. This is version 2 of this Preprint.

An open, scalable, and flexible framework for automated aerial measurement of field experiments
Downloads
Supplementary Files
Authors
Abstract
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 emphasize... more
DOI
https://doi.org/10.31223/osf.io/vezn5
Subjects
Agricultural Science, Agriculture, Bioresource and Agricultural Engineering, Ecology and Evolutionary Biology, Engineering, Life Sciences, Plant Breeding and Genetics Life Sciences, Plant Sciences, Research Methods in Life Sciences, Terrestrial and Aquatic Ecology
Keywords
agriculture, automation, data standards, ecosystem ecology, high performance computing, high throughput phenotyping, open source software, unoccupied aerial vehicles, workflows
Dates
Published: 2020-05-25 10:23
There are no comments or no comments have been made public for this article.