Passive kHz lidar for the quantification of insect activity and dispersal

Abstract

Abstract Background In recent years, our group has developed electro-optical remote sensing methods for the monitoring and classification of aerofauna. These methods include active lidar methods and passive, so-called dark-field methods that measure scattered sunlight. In comparison with satellite- and airborne remote sensing, our methods offer a spatiotemporal resolution several orders of magnitude higher, and unlike radar, they can be employed close to ground. Whereas passive methods are desirable due to lower power consumption and ease of use, they have until now lacked ranging capabilities. Results In this work, we demonstrate how passive ranging of sparse insects transiting the probe volume can be achieved with quadrant sensors. Insects are simulated in a raytracing model of the probe volume, and a ranging equation is devised based on the simulations. The ranging equation is implemented and validated with field data, and system parameters that vary with range are investigated. A model for estimating insect flight headings with modulation spectroscopy is implemented and tested with inconclusive results. Insect fluxes are retrieved through time-lag correlation of quadrant detector segments, showing that insects flew more with than against the wind during the study period. Conclusions The presented method demonstrates how ranging can be achieved with quadrant sensors, and how it can be implemented with or without active illumination. A number of insect flight parameters can be extracted from the data produced by the sensor and correlated with complementary information about weather and topography. The approach has the potential to become a widespread and simple tool for monitoring abundances and fluxes of pests and disease vectors in the atmosphere.

Keywords

• Near-field optics
• Lidar
• Remote sensing
• Aerofauna
• Dark field
• Modulation spectroscopy