ORCID
Schultz: https://orcid.org/0000-0001-5254-2598; Neary: https://orcid.org/0000-0001-6198-5470; Jones: https://orcid.org/0000-0003-1814-6115; Evans: https://orcid.org/0000-0001-6815-2383; Iglay: https://orcid.org/0000-0001-7300-7244
MSU Affiliations
College of Forest Resources; Department of Wildlife, Fisheries and Aquaculture; Mississippi Agricultural and Forestry Experiment Station; Forest and Wildlife Research Center
Item Type
Research Data
Abstract
The following dataset pertains to Python scripts of an agent-based model simulating various drone survey design and quantifying potential count bias of stationary animals in fixed landscapes as part of an accepted manuscript in Ecosphere. Simulated animals were distributed among five animal densities (n = 4, 9, 25, 49, 100 animals/survey area) and three distribution patterns (random, uniform, aggregated). Eight drone flight patterns surveyed a 4.16-km2 landscape within constraints of real-world battery and line-of-sight limitations. The simplified landscape also provided 100% animal classification (i.e., all animals within image frame observed and identified).
Publication Date
Winter 2-11-2026
Recommended Citation
Schultz, Emma A.; Ellison-Neary, Natasha; Jones, Landon R.; Evans, Kristine O.; and Iglay, Raymond B., "Agent-based Model Details for Quantifying Error in Drone-based Animal Surveys: Animal Density, Distribution and Flight Patterns" (2026). Research Data. 11.
https://scholarsjunction.msstate.edu/research-data/11
