Thermal Infrared UAV Applications for Spatially Explicit Wildlife Occupancy Modeling

Eve Bohnett (), Babu Ram Lamichanne, Surendra Chaudhary, Kapil Pokhrel, Giavanna Dorman, Axel Flores, Rebecca Lewison, Fang Qiu, Doug Stow and Li An
Additional contact information
Eve Bohnett: Department of Landscape Architecture, University of Florida, Gainesville, FL 89101, USA
Babu Ram Lamichanne: National Trust for Nature Conservation, Chitwan 44204, Nepal
Surendra Chaudhary: National Trust for Nature Conservation, Chitwan 44204, Nepal
Kapil Pokhrel: National Trust for Nature Conservation, Chitwan 44204, Nepal
Giavanna Dorman: Department of Geography, San Diego State University, San Diego, CA 92182, USA
Axel Flores: Department of Geography, San Diego State University, San Diego, CA 92182, USA
Rebecca Lewison: Department of Biology, San Diego State University, San Diego, CA 92182, USA
Fang Qiu: Department of Geospatial Information Science, University of Texas, Dallas, TX 75080, USA
Doug Stow: Department of Geography, San Diego State University, San Diego, CA 92182, USA
Li An: The Complex Human-Environment Systems Lab, College of Forestry, Wildlife and Environment, Auburn University, Auburn, AL 36849, USA

Land, 2025, vol. 14, issue 7, 1-27

Abstract: Assessing the impact of community-based conservation programs on wildlife biodiversity remains a significant challenge. This pilot study was designed to develop and demonstrate a scalable, spatially explicit workflow using thermal infrared (TIR) imagery and unmanned aerial vehicles (UAVs) for non-invasive biodiversity monitoring. Conducted in a 2-hectare grassland area in Chitwan, Nepal, the study applied TIR-based grid sampling and multi-species occupancy models with thin-plate splines to evaluate how species detection and richness might vary between (1) morning and evening UAV flights, and (2) the Chitwan National Park and Kumroj Community Forest. While the small sample area inherently limits ecological inference, the aim was to test and demonstrate data collection and modeling protocols that could be scaled to larger landscapes with sufficient replication, and not to produce generalizable ecological findings from a small dataset. The pilot study results revealed higher species detection during morning flights, which allowed us to refine our data collection. Additionally, models accounting for spatial autocorrelation using thin plate splines suggested that community-based conservation programs effectively balanced ecosystem service extraction with biodiversity conservation, maintaining richness levels comparable to the national park. Models without splines indicated significantly higher species richness within the national park. This study demonstrates the potential for spatially explicit methods for monitoring grassland mammals using TIR UAV as indicators of anthropogenic impacts and conservation effectiveness. Further data collection over larger spatial and temporal scales is essential to capture the occupancy more generally for species with larger home ranges, as well as any effects of rainfall, flooding, and seasonal variability on biodiversity in alluvial grasslands.

Keywords: thermal infrared UAV; spatially explicit occupancy; thin-plate spline; community-based conservation (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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