Insect Monitoring Radar: Maximizing Performance and Utility

Drake, V. A.; Hatty, Shane; Symons, Colin; Wang, Haikou

doi:10.3390/rs12040596

Cited by 18 publications

(18 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recent works continue to fill research gaps in equipment [ 96 , 97 , 98 ], reflectivity, and insects’ geometrical characteristics [ 99 , 100 , 101 , 102 ]. As shown earlier, radar applications focus on either biodiversity/conservation [ 103 , 104 , 105 , 106 , 107 ] or agriculture (economically important insects [ 108 , 109 , 110 ] and pest management [ 21 , 111 , 112 , 113 , 114 , 115 , 116 ]).…”

Section: Insect Radarmentioning

confidence: 99%

A Review of Insect Monitoring Approaches with Special Reference to Radar Techniques

Noskov

Bendix

Frieß

2021

Sensors

View full text Add to dashboard Cite

Drastic declines in insect populations are a vital concern worldwide. Despite widespread insect monitoring, the significant gaps in the literature must be addressed. Future monitoring techniques must be systematic and global. Advanced technologies and computer solutions are needed. We provide here a review of relevant works to show the high potential for solving the aforementioned problems. Major historical and modern methods of insect monitoring are considered. All major radar solutions are carefully reviewed. Insect monitoring with radar is a well established technique, but it is still a fast-growing topic. The paper provides an updated classification of insect radar sets. Three main groups of insect radar solutions are distinguished: scanning, vertical-looking, and harmonic. Pulsed radar sets are utilized for all three groups, while frequency-modulated continuous-wave (FMCW) systems are applied only for vertical-looking and harmonic insect radar solutions. This work proves the high potential of radar entomology based on the growing research interest, along with the emerging novel setups, compact devices, and data processing approaches. The review exposes promising insect monitoring solutions using compact radar instruments. The proposed compact and resource-effective setups can be very beneficial for systematic insect monitoring.

show abstract

Section: Insect Radarmentioning

confidence: 99%

A Review of Insect Monitoring Approaches with Special Reference to Radar Techniques

Noskov

Bendix

Frieß

2021

Sensors

View full text Add to dashboard Cite

show abstract

“…The R scripts use standard summary files produced by the IMR processing system as input. A variant that analyses data from a newer, upgraded radar (Drake et al 2020) has also been developed.…”

Section: Methodsmentioning

confidence: 99%

“…This is the case both for the vertical-beam systems developed specifically for insect observation, e.g. of the type known variously as Vertical-Looking Radars (VLR) and Insect Monitoring Radars (IMR) (Chapman, Reynolds, and Smith 2003;Drake et al 2020), and radars in which the beam is scanned (e.g. Schaefer 1976).…”

Section: Introductionmentioning

confidence: 99%

Heading variations resolve the heading-direction ambiguity in vertical-beam radar observations of insect migration

Drake

Hao

Warrant

2021

International Journal of Remote Sensing

Self Cite

View full text Add to dashboard Cite

Vertical-beam entomological radars provide precise measurements of the body alignment of individual overflying insects but are unable to distinguish which of the two axial directions the insect is heading towards. Insects migrating at altitude typically show common alignment, although with a broad spread. We show here that when observations from multiple individual insects are available, and the insects have airspeeds of about 2 ms-1 or greater, the spread in heading directions allows the heading ambiguity to be resolved (though at the sample rather than the individual level). A vector analysis of radar-measured track direction, track speed, and heading will provide consistent results for all the insects in a sample only when the heading direction is chosen correctly. With the heading then resolved, the analysis can continue to estimation of representative values for the airspeed of the insects in the sample and for the speed and direction of the wind they were flying in. This general approach can be implemented in two different ways, which we term the 'cluster' and 'projection' methods. When applied to an intense migration of large insects, probably moths, these methods produced highly consistent results from hour to hour and from one 150 m height interval to the next. Simulations show that the methods are not liable to directional bias and reveal when they are rendered ineffective by small sample sizes or low insect airspeeds; they also indicate that the cluster method handles small sample sizes better than the projection method, and its use is therefore recommended. A comparison with two previously proposed methods that use meteorological data to resolve the ambiguity shows that the new methods are more reliable. Use of this objective means of resolving the heading ambiguity will increase confidence in radar-based studies of the orientation behaviour of insect migrants and their responses to cues like sky illumination patterns, the Earth's magnetic field, and wind.

show abstract

“…The method to identify insects and hydrometeors presented herein builds on prior work using polarimetric diversity and Doppler velocity power spectra variability (e.g., Martner and Moran, 2001;Bauer-Pfundstein and Görsdorf, 2007;Luke et al, 2008;Görsdorf et a., 2015). One unique feature of the proposed algorithms is that insect and hydrometeor scattering are identified before identifying significant peaks in the Doppler velocity spectra.…”

Section: Introductionmentioning

confidence: 99%

Identifying insects, clouds, and precipitation using vertically pointing polarimetric radar Doppler velocity spectra

et al. 2021

View full text Add to dashboard Cite

Abstract. This study presents a method to identify and distinguish insects, clouds, and precipitation in 35 GHz (Ka-band) vertically pointing polarimetric radar Doppler velocity power spectra and then produce masks indicating the occurrence of hydrometeors (i.e., clouds or precipitation) and insects at each range gate. The polarimetric radar used in this study transmits a linear polarized wave and receives signals in collinear (CoPol) and cross-linear (XPol) polarized channels. The measured CoPol and XPol Doppler velocity spectra are used to calculate linear depolarization ratio (LDR) spectra. The insect–hydrometeor discrimination method uses CoPol and XPol spectral information in two separate algorithms with their spectral results merged and then filtered into single value products at each range gate. The first algorithm discriminates between insects and clouds in the CoPol Doppler velocity power spectra based on the spectra texture, or spectra roughness, which varies due to the scattering characteristics of insects vs. cloud particles. The second algorithm distinguishes insects from raindrops and ice particles by exploiting the larger Doppler velocity spectra LDR produced by asymmetric insects. Since XPol power return is always less than CoPol power return for the same target (i.e., insect or hydrometeor), fewer insects and hydrometeors are detected in the LDR algorithm than the CoPol algorithm, which drives the need for a CoPol based algorithm. After performing both CoPol and LDR detection algorithms, regions of insect and hydrometeor scattering from both algorithms are combined in the Doppler velocity spectra domain and then filtered to produce a binary hydrometeor mask indicating the occurrence of cloud, raindrops, or ice particles at each range gate. Forty-seven summertime days were processed with the insect–hydrometeor discrimination method using US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Ka-band zenith pointing radar observations in northern Oklahoma, USA. For these 47 d, over 70 % of the hydrometeor mask column bottoms were within ±100 m of simultaneous ceilometer cloud base heights. All datasets and images are available to the public on the DOE ARM repository.

show abstract

Insect Monitoring Radar: Maximizing Performance and Utility

Cited by 18 publications

References 19 publications

A Review of Insect Monitoring Approaches with Special Reference to Radar Techniques

A Review of Insect Monitoring Approaches with Special Reference to Radar Techniques

Heading variations resolve the heading-direction ambiguity in vertical-beam radar observations of insect migration

Identifying insects, clouds, and precipitation using vertically pointing polarimetric radar Doppler velocity spectra

Contact Info

Product

Resources

About