Abstract
Signals from global navigation satellite systems (GNSS) can be utilized as signals of opportunity in remote sensing applications. Geophysical properties of the earth surface can be detected and monitored by processing the back-scattered GNSS signals from the ground. In the literature, several airborne GNSS-based passive radar experiments have been successfully demonstrated. With the advancements in small unmanned aerial vehicles (UAVs) and their applications for environmental monitoring, we want to investigate whether GNSS-based passive radar can provide valuable geospatial information from such platforms. Low-cost GNSS reflectometry sensors, developed using commercial of the shelf components, can be mounted onboard UAVs and flown to sense environmental parameters. This paper presents the results of a preliminary study to investigate the feasibility of utilizing data collected by UAV-based GNSS-R sensors to detect surface water for a potential application in supporting flood monitoring operations. The study was conducted in the area surrounding the Avigliana lakes in Northern Italy. The results show the possibility of detecting small water surfaces with few tens of meters resolution, and estimating the area of the lake surface with 92% accuracy. Furthermore, it is proved through simulations that the use of multi-GNSS increases this accuracy to about 99%.
Highlights
Remote sensing has been used in studying floods for more than 40 years [1], where data from air- and space-borne optical, thermal and microwave sensors [2] are exploited to support the different stages of flood risk management [3]
The other two cases relate to smaller and narrower water surfaces, where the performance of the technique is challenged in detecting unexpected water contents on ground and in recognizing narrow river streams
This paper presents the preliminary results of investigating the feasibility of using data from
Summary
Remote sensing has been used in studying floods for more than 40 years [1], where data from air- and space-borne optical, thermal and microwave sensors [2] are exploited to support the different stages of flood risk management [3]. Space-borne data are widely used for flood monitoring providing different spatial and temporal resolutions. Synthetic aperture radar (SAR) techniques on the other hand overcome this weather limitation, and provide day/night visibility [5], but are challenged to detect inundations in urban areas [6] and under vegetation [7]. The latter is overcome with passive microwave sensors in low microwave frequency which have
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