To maximize resilience and productivity, researchers, farmers and natural resource managers need to know how plants and animals—and landscapes as a whole—are affected by changing environmental conditions and other stressors. Remote sensing with drones offers a promising way to characterize landscapes, individual plants and animals, and their various stressors. However, a number of barriers have kept drones from being widely used for agriculture and natural resources.
Since 2016, Land-grant University researchers and educators in 20 states have worked to increase the adoption of drones for remote sensing and precise management of agriculture and natural resources through a multistate project. With diverse expertise and members in multiple states, this team can test drones in a wide variety of real-world agriculture situations. In contrast, most prior research focused on drone use in a single field or a specific crop or stressor. Coordination spreads the workload, reduces duplication, and lowers some costs. Sharing information, equipment and other resources helps overcome the limited capacity of a single institution.
As part of this ongoing project, scientists have evaluated and identified the most reliable, cost-effective and user-friendly drone platforms and sensors for monitoring and managing stressors in agriculture and natural resources. To maximize the accuracy of the data collected, project members developed hardware, software and detailed protocols for calibrating and using drones as well as new tools to help drone users manage the data they collect, including a digital logbook.
Expanding Drone Use Opportunities
This project has expanded drone use opportunities by creating new drone systems that:
- Scout pests and diseases in fruit, nut and row crops and apply targeted treatment. These industries face major pest issues that are intensified by limited labor availability and increasing consumer demand for produce with fewer chemical inputs (Clemson University, University of Georgia, Purdue University, Washington State University).
- Monitor plant water stress to help farmers target irrigation resources where most needed (Clemson University).
- Enable faster plant screening and new types of measurements and biological discoveries (Montana State University, Texas A&M, Virginia Tech, Washington State University).
- Detect stray livestock herds, create 3D renderings of animals to calculate market value and assess forage quality (University of Kentucky, Mississippi State University).
- Monitor water quality on a large scale (Mississippi State University, North Carolina State University, Virginia Tech).
- Provide higher resolution data for flood risk models and water resource management (Auburn University, Mississippi State University, North Carolina State University, Virginia Tech).
Over the past five years, project members have shared their knowledge with farmers, producers and natural resource managers in diverse ways, including:
- Fact sheets to help stakeholders understand the regulations and licensing required for drone use
- Workshops on risk management for current and potential drone users (University of Arkansas, Clemson University, Texas A&M)
- Trainings to help forest land managers use drones for less labor-intensive estimates of timber value (Auburn University, University of Florida)
- Extension workshops, programs, and materials (University of Arkansas, Clemson University, The Ohio State University, Purdue University, Washington State University)
- Digital resources like websites, videos, and datasets
- Peer-reviewed publications
This group’s multistate, multidisciplinary research and outreach have helped overcome barriers and accelerate broader use of drones in agriculture and natural resources. By efficiently collecting large amounts of data, drones can help guide better decision making, greater advances in plant and animal breeding, and more profitable and sustainable management.
The team won the 2022 National Excellence in Multistate Research Award for their outstanding collaboration and impacts. The award is presented each year by the Experiment Station Section, a unit of the Association of Public and Land-grant Universities Board on Agriculture Assembly.