Data from: Evaluating the target-tracking performance of scanning avian radars by augmenting data with simulated echoes

1. Small scanning radars have been used for many years to track the movements of insects, birds, and bats. While the ability to track multiple flying animals simultaneously has numerous applications in basic ecology and applied conservation, translating radar tracks into accurate animal densities an...

Full description

Bibliographic Details
Main Authors: Urmy, Samuel, Warren, Joseph
Format: Dataset
Language:unknown
Published: 2020
Subjects:
Online Access:https://zenodo.org/record/4971275
https://doi.org/10.5061/dryad.3n5tb2rd2
id ftzenodo:oai:zenodo.org:4971275
record_format openpolar
spelling ftzenodo:oai:zenodo.org:4971275 2023-05-15T18:27:25+02:00 Data from: Evaluating the target-tracking performance of scanning avian radars by augmenting data with simulated echoes Urmy, Samuel Warren, Joseph 2020-02-03 https://zenodo.org/record/4971275 https://doi.org/10.5061/dryad.3n5tb2rd2 unknown https://zenodo.org/communities/dryad https://zenodo.org/record/4971275 https://doi.org/10.5061/dryad.3n5tb2rd2 oai:zenodo.org:4971275 info:eu-repo/semantics/openAccess https://creativecommons.org/publicdomain/zero/1.0/legalcode info:eu-repo/semantics/other dataset 2020 ftzenodo https://doi.org/10.5061/dryad.3n5tb2rd2 2023-03-10T21:36:27Z 1. Small scanning radars have been used for many years to track the movements of insects, birds, and bats. While the ability to track multiple flying animals simultaneously has numerous applications in basic ecology and applied conservation, translating radar tracks into accurate animal densities and fluxes requires estimates of detection and tracking probabilities. These can be challenging to determine, especially in environments with variable background clutter. 2. In order to assess radar tracking probabilities, we added echoes from simulated bird tracks to sequences of scans collected with an X-band marine radar at a colony of common and roseate terns (Sterna hirundo and S. dougallii) on Great Gull Island, New York, USA in the summers of 2014 and 2015. Automated detection, classification, and tracking algorithms were used to extract the trajectories of terns from the radar data. The proportion of simulated tracks recovered by these procedures could then be used to estimate the tracking probabilities for real birds. Stationary telescope transects provided visual ground-truth. 3. The radar could track individual birds up to 3 km away, performing best between 0.5-1.2 km, where 38% of simulated birds were correctly detected and tracked in each scan. Overall, 94% of all simulated birds were tracked over at least part of their trajectories. Tracking performance was limited by weak bird echoes, backscatter from the sea surface, and the inherent challenges of multi-target tracking. 4. This simulation-based method provides a low-cost, flexible approach for estimating radar tracking probabilities in complex, cluttered environments. Knowledge of these probabilities in turn allows the animal densities and fluxes to be corrected for imperfect detection. Despite their limitations, small scanning radars can track hundreds of birds simultaneously over 10s of km2, giving a view of animal movement unavailable with other techniques. Funding provided by: American Museum of Natural HistoryCrossref Funder Registry ID: ... Dataset Sterna hirundo Zenodo Gull Island ENVELOPE(-55.315,-55.315,49.533,49.533)
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language unknown
description 1. Small scanning radars have been used for many years to track the movements of insects, birds, and bats. While the ability to track multiple flying animals simultaneously has numerous applications in basic ecology and applied conservation, translating radar tracks into accurate animal densities and fluxes requires estimates of detection and tracking probabilities. These can be challenging to determine, especially in environments with variable background clutter. 2. In order to assess radar tracking probabilities, we added echoes from simulated bird tracks to sequences of scans collected with an X-band marine radar at a colony of common and roseate terns (Sterna hirundo and S. dougallii) on Great Gull Island, New York, USA in the summers of 2014 and 2015. Automated detection, classification, and tracking algorithms were used to extract the trajectories of terns from the radar data. The proportion of simulated tracks recovered by these procedures could then be used to estimate the tracking probabilities for real birds. Stationary telescope transects provided visual ground-truth. 3. The radar could track individual birds up to 3 km away, performing best between 0.5-1.2 km, where 38% of simulated birds were correctly detected and tracked in each scan. Overall, 94% of all simulated birds were tracked over at least part of their trajectories. Tracking performance was limited by weak bird echoes, backscatter from the sea surface, and the inherent challenges of multi-target tracking. 4. This simulation-based method provides a low-cost, flexible approach for estimating radar tracking probabilities in complex, cluttered environments. Knowledge of these probabilities in turn allows the animal densities and fluxes to be corrected for imperfect detection. Despite their limitations, small scanning radars can track hundreds of birds simultaneously over 10s of km2, giving a view of animal movement unavailable with other techniques. Funding provided by: American Museum of Natural HistoryCrossref Funder Registry ID: ...
format Dataset
author Urmy, Samuel
Warren, Joseph
spellingShingle Urmy, Samuel
Warren, Joseph
Data from: Evaluating the target-tracking performance of scanning avian radars by augmenting data with simulated echoes
author_facet Urmy, Samuel
Warren, Joseph
author_sort Urmy, Samuel
title Data from: Evaluating the target-tracking performance of scanning avian radars by augmenting data with simulated echoes
title_short Data from: Evaluating the target-tracking performance of scanning avian radars by augmenting data with simulated echoes
title_full Data from: Evaluating the target-tracking performance of scanning avian radars by augmenting data with simulated echoes
title_fullStr Data from: Evaluating the target-tracking performance of scanning avian radars by augmenting data with simulated echoes
title_full_unstemmed Data from: Evaluating the target-tracking performance of scanning avian radars by augmenting data with simulated echoes
title_sort data from: evaluating the target-tracking performance of scanning avian radars by augmenting data with simulated echoes
publishDate 2020
url https://zenodo.org/record/4971275
https://doi.org/10.5061/dryad.3n5tb2rd2
long_lat ENVELOPE(-55.315,-55.315,49.533,49.533)
geographic Gull Island
geographic_facet Gull Island
genre Sterna hirundo
genre_facet Sterna hirundo
op_relation https://zenodo.org/communities/dryad
https://zenodo.org/record/4971275
https://doi.org/10.5061/dryad.3n5tb2rd2
oai:zenodo.org:4971275
op_rights info:eu-repo/semantics/openAccess
https://creativecommons.org/publicdomain/zero/1.0/legalcode
op_doi https://doi.org/10.5061/dryad.3n5tb2rd2
_version_ 1766209511155040256