Analysis of Unmanned Aerial System (UAS) Sensor Data for Natural Resource Applications: A Review

Benjamin T. Fraser, Christine L. Bunyon, Sarah Reny, Isabelle Sophia Lopez and Russell G. Congalton
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Benjamin T. Fraser: Department of Natural Resources and the Environment, University of New Hampshire, 56 College Road, Durham, NH 03824, USA
Christine L. Bunyon: Department of Natural Resources and the Environment, University of New Hampshire, 56 College Road, Durham, NH 03824, USA
Sarah Reny: Department of Natural Resources and the Environment, University of New Hampshire, 56 College Road, Durham, NH 03824, USA
Isabelle Sophia Lopez: Department of Natural Resources and the Environment, University of New Hampshire, 56 College Road, Durham, NH 03824, USA
Russell G. Congalton: Department of Natural Resources and the Environment, University of New Hampshire, 56 College Road, Durham, NH 03824, USA

Geographies, 2022, vol. 2, issue 2, 1-38

Abstract: Unmanned Aerial Systems (UAS, UAV, or drones) have become an effective tool for applications in natural resources since the start of the 21st century. With their associated hardware and software technologies, UAS sensor data have provided high resolution and high accuracy results in a range of disciplines. Despite these achievements, only minimal progress has been made in (1) establishing standard operating practices and (2) communicating both the limitations and necessary next steps for future research. In this review of literature published between 2016 and 2022, UAS applications in forestry, freshwater ecosystems, grasslands and shrublands, and agriculture were synthesized to discuss the status and trends in UAS sensor data collection and processing. Two distinct conclusions were summarized from the over 120 UAS applications reviewed for this research. First, while each discipline exhibited similarities among their data collection and processing methods, best practices were not referenced in most instances. Second, there is still a considerable variability in the UAS sensor data methods described in UAS applications in natural resources, with fewer than half of the publications including an incomplete level of detail to replicate the study. If UAS are to increasingly provide data for important or complex challenges, they must be effectively utilized.

Keywords: unmanned aerial systems; UAS; UAV; natural resources; forestry; freshwater; grasslands; shrublands; agriculture; photogrammetry (search for similar items in EconPapers)
JEL-codes: Q1 Q15 Q5 Q53 Q54 Q56 Q57 (search for similar items in EconPapers)
Date: 2022
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