Systematic validation of 3D ground-based radars for tracking birds and bats
Abstract
Ground-based radar (GBR) is increasingly used to quantify bird and bat movement in support of ecological studies, environmental monitoring, and collision risk assessment, yet few studies have systematically validated radar-derived tracks against targets with known positions. We evaluated the performance of two commercially available 3D GBRs using controlled drone flights that were designed to simulate biologically relevant movement patterns ranging from straight-line transiting to highly dynamic chasing behavior. Target detection rate, positional deviation, mean absolute positional deviation, and root mean square deviation were computed for radar-derived positions compared to drone positions across horizontal and vertical dimensions. Both radars successfully detected moving targets and produced georeferenced tracks generally consistent with drone positions within tens of meters. Detection performance varied with radar power, flight trajectory relative to radar orientation, and flight track continuity. Flights near the limits of the radar viewshed and behaviors with dynamic maneuvering produced greater tracking variability. Positional discrepancies were primarily driven by georeferencing uncertainty, and track continuity and smoothness. Drone-radar positional discrepancies in the vertical dimension were generally within estimated drone position uncertainties, supporting the use of 3D GBRs to characterize flight height distributions relevant to collision risk modeling. These findings demonstrate that GBR can provide accurate, quantitative bird and bat movement data at spatial and temporal scales difficult to achieve with visual or optical methods alone, while underscoring the importance of careful siting, georeferencing, and conservative interpretation of tracks near radar viewshed limits or during highly dynamic flight behavior. As infrastructure development continues to expand globally, validated GBR systems can strengthen ecological monitoring and support more defensible decisions that balance infrastructure needs with wildlife conservation.
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BibTeX
@misc{chang2026systematic,
title = {{Systematic validation of 3D ground-based radars for tracking birds and bats}},
author = {Grace Chang and Jennifer Pettis Schallert and Stephanie Schneider and Rachael Young and Sharon H. Kramer and Lizette Crooks and Jesse Lewis and Frank Spada},
howpublished = {EarthArXiv},
year = {2026},
month = sep,
doi = {10.31223/x5kj7v},
url = {https://eartharxiv.org/repository/view/15176/},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Systematic validation of 3D ground-based radars for tracking birds and bats
AU - Grace Chang
AU - Jennifer Pettis Schallert
AU - Stephanie Schneider
AU - Rachael Young
AU - Sharon H. Kramer
AU - Lizette Crooks
AU - Jesse Lewis
AU - Frank Spada
PY - 2026
DA - 2026/09/23
PB - EarthArXiv
DO - 10.31223/x5kj7v
UR - https://eartharxiv.org/repository/view/15176/
AB - Ground-based radar (GBR) is increasingly used to quantify bird and bat movement in support of ecological studies, environmental monitoring, and collision risk assessment, yet few studies have systematically validated radar-derived tracks against targets with known positions. We evaluated the performance of two commercially available 3D GBRs using controlled drone flights that were designed to simulate biologically relevant movement patterns ranging from straight-line transiting to highly dynamic chasing behavior. Target detection rate, positional deviation, mean absolute positional deviation, and root mean square deviation were computed for radar-derived positions compared to drone positions across horizontal and vertical dimensions. Both radars successfully detected moving targets and produced georeferenced tracks generally consistent with drone positions within tens of meters. Detection performance varied with radar power, flight trajectory relative to radar orientation, and flight track continuity. Flights near the limits of the radar viewshed and behaviors with dynamic maneuvering produced greater tracking variability. Positional discrepancies were primarily driven by georeferencing uncertainty, and track continuity and smoothness. Drone-radar positional discrepancies in the vertical dimension were generally within estimated drone position uncertainties, supporting the use of 3D GBRs to characterize flight height distributions relevant to collision risk modeling. These findings demonstrate that GBR can provide accurate, quantitative bird and bat movement data at spatial and temporal scales difficult to achieve with visual or optical methods alone, while underscoring the importance of careful siting, georeferencing, and conservative interpretation of tracks near radar viewshed limits or during highly dynamic flight behavior. As infrastructure development continues to expand globally, validated GBR systems can strengthen ecological monitoring and support more defensible decisions that balance infrastructure needs with wildlife conservation.
ER -