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Fusing Satellite and Drone Data with GIS to Create New Analytical Decision Support Tools for Varying Farm Types

PI Kevin Adkins

PI Nickolas Macchiarella

The synergy between moderate resolution satellite imagery and fine resolution drone imagery, LiDAR data, and meteorological data, along with generally available GIS data, must be identified and optimized. These data will be integrated to produce a variety of products that help identify what tools, inputs, and management strategies most effectively contribute to an increase in the productivity and resilience of an important agricultural system to a major weather or climate related disturbance.

Satellite imagery has been used in agriculture for some time and the increasing implementation of drones into agriculture and agriculture science holds unique promise. However, the synergy between moderate resolution satellite imagery, fine resolution drone imagery, fine resolution LiDAR (Light Detection And Ranging) data, fine-resolution meteorological data, and generally available GIS (Geographic Information Systems) data must be identified and optimized. To be most useful, this fusion of data should help provide estimates in the health and yield of agriculture systems as well as insight into the microclimate and ecosystem variation within a farm site. These data will be integrated to produce a variety of fine-resolution maps that can be analyzed to identify what tools, inputs, and management strategies most effectively contribute to an increase in productivity, agroecological system health, and resiliency or restoration (typically in response to weather or climatic disturbance) of a given farming operation and site. This research will apply these data science methods and tools to varying farm types in Puerto Rico. We expect new insight into how the fusing of a multitude of data can be effectively integrated into an agriculture operation and, subsequently, determine which outputs are most valuable to the varied farm types, practices, and locations. This investigation will also provide critical information on the resistance and resilience of an important agricultural system to major weather or climate-related disturbances and, subsequently, inform management decisions related to climate change adaptation.

Research Dates

07/19/2019 to 06/19/2023

Researchers

  • Kevin A Adkins
    Department
    Aeronautical Science Department
    Degrees
    Ph.D., Mississippi State University
    M.Eng., B.S., University of Michigan-Ann Arbor
  • Nickolas Macchiarella
    Department
    Aeronautical Science Department
    Degrees
    Ph.D., Nova Southeastern University
    M.Ed., University of Louisville
    B.S., University of Central Florida
  • Ronny Schroeder
    Department
    Applied Aviation Sciences Department
    Degrees
    Ph.D., Universit??t Hohenheim
    M.A., B.A., Friedrich Schiller Universit??t Jena

Tags: nmanned aircraft systems uas drones agriculture farm management climate resiliency

Categories: Faculty-Staff