Insect target classes discerned from entomological radar data

Zhenhua Hao, V. Alistair Drake, John R. Taylor, Eric Warrant

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Entomological radars employing the 'ZLC' (zenith-pointing linear-polarized narrow-angle conical scan) configuration detect individual insects flying overhead and can retrieve information about a target's trajectory (its direction and speed), the insect's body alignment and four parameters that characterize the target itself: its radar cross section, two shape parameters and its wingbeat frequency. Criteria have previously been developed to distinguish Australian Plague Locusts Chortoicetes terminifera, large moths, medium moths and small insects using the target-character parameters. Combinations of target characters that occur frequently, known as target 'classes', have also been identified previously both through qualitative analyses and more objectively with a 4D peak-finding algorithm applied to a dataset spanning a single flight season. In this study, fourteen years of radar observations from Bourke, NSW (30.0392°S, 145.952°E, 107 m above MSL) have been used to test this approach and potentially improve its utility. We found that the previous criteria for assigning targets to classes require some modification, that classes identified in the previous studies were frequently present in other years and that two additional classes could be recognized. Additionally, by incorporating air-temperature information from a meteorological model, we have shown that different classes fly in different temperature ranges. By drawing on knowledge concerning migrant species found in the regional areas around the radar site, together with morphological measurements and radar cross-section data for proxy species, we have made tentative identifications of the insect taxa likely to be contributing to each class.

Original languageEnglish
Article number673
JournalRemote Sensing
Issue number4
Publication statusPublished - 2020 Feb 18

Bibliographical note

This work was funded by the European Union (EU) and the Horizon 2020 program: European Research Council (ERC) Advanced Grant MagneticMoth (grant no. 741298)

Subject classification (UKÄ)

  • Ecology


  • Grasshopper
  • Insect RCS
  • Insects
  • Migration
  • Moth
  • Radar cross-section
  • Radar entomology
  • Target classes


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