UAV-Based GNSS-R for Water Detection as a Support to Flood Monitoring Operations: A Feasibility Study

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%.

Integration of Smartphones Into Small Unmanned Aircraft Systems to Sense Water in Soil by Using Reflected GPS Signals

“…The qualitative analysis of the high jump in the reflected signal power over both ponds and spatial variations over land indicates that the fluctuations over land carry information in addition to noise and they are due to the change in crop types, roughness, and moisture in the soil. These results are consistent with resent experimental results [14]- [16] and support the assertion that reflected signals collected by smartphones are highly sensitive to water content on the surface, with similar dynamic range observed by regular custom-built GNSS-R instruments. However, it is necessary to have detailed insitu data in conjunction with experimental data in order to quantitatively verify the results.…”

“…Two identical smartphones attached to ground plates (located on the top and bottom of the drone) are used to separate direct and reflected Global Positioning System (GPS) signals. Consistent with the results obtained by other recent airborne observations [14]- [16], a much stronger reflected signal has been observed over ponds and there has been appreciable spatial variations over lands. However, it has also been shown that the received signal power levels can be significantly modified by the orientation of smartphones due to the poor quality of the smartphone GNSS antenna, which can make the analysis of received signals challenging for remote sensing applications.…”

“…This technique has been gaining attention in the remote sensing community since it only requires the development of small Size Weight and Power -Cost (SWaP-C) passive receivers, an analysis algorithm, and no on-board transmitter [3]. Over the past two decades, various methods have been developed to estimate the geophysical parameters such as ocean surface winds [4], snowpack, and sea ice [5], soil moisture [6]- [10], vegetation [11]- [13] as well as wetland and flooding monitoring [14]- [16]. In particular, application and validation of the GNSS-M. Kurum R technique over land surfaces have been accelerated as a potential microwave remote sensing alternative with the launch of new spaceborne missions [17]- [19] in recent years.…”

“…In particular, application and validation of the GNSS-M. Kurum R technique over land surfaces have been accelerated as a potential microwave remote sensing alternative with the launch of new spaceborne missions [17]- [19] in recent years. The number of studies have used geodetic or specially designed GNSS receivers from airborne [6], [8], [10], [13]- [16] and tower-based platforms [7], [9], [11]. They have experimentally demonstrated that reflected GNSS signals from land are highly sensitive to water content in the soil and vegetation type and amount over ground.…”

Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces

“…Furthermore, an increasing number of combinations and the linking of different sensors and RS platforms have been used to monitor flood events, e.g., web cameras with airborne LiDAR RS data [217]. Due to a high degree of flexibility with comparatively low costs, an increasing number of different RS sensors are being used on UAV platforms for monitoring floods [218,219].…”