A fully software Global Navigation Satellite System reflectometry (GNSS-R) receiver for soil monitoring

Pei, Yuekun; Notarpietro, Riccardo; Savi, Patrizia; Cucca, Manuela; Dovis, Fabio

doi:10.1080/01431161.2014.894662

Cited by 19 publications

(11 citation statements)

References 45 publications

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“…[13][14][15][16][17]. It was then tested over continental surfaces, where it revealed its strong potential for the monitoring of various surface parameters such as the water content of the soil or vegetation biomass [18][19][20][21][22][23][24][25]. Following various recent in situ and airborne campaigns collecting GNSS-R measurements [22,26,27], several studies have illustrated their potential for the development of GNSS-R based applications [28][29][30][31][32][33][34][35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Desert Roughness Retrieval Using CYGNSS GNSS-R Data

et al. 2020

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The aim of this paper is to assess the potential use of data recorded by the Global Navigation Satellite System Reflectometry (GNSS-R) Cyclone Global Navigation Satellite System (CYGNSS) constellation to characterize desert surface roughness. The study is applied over the Sahara, the largest non-polar desert in the world. This is based on a spatio-temporal analysis of variations in Cyclone Global Navigation Satellite System (CYGNSS) data, expressed as changes in reflectivity (Γ). In general, the reflectivity of each type of land surface (reliefs, dunes, etc.) encountered at the studied site is found to have a high temporal stability. A grid of CYGNSS Γ measurements has been developed, at the relatively fine resolution of 0.03° × 0.03°, and the resulting map of average reflectivity, computed over a 2.5-year period, illustrates the potential of CYGNSS data for the characterization of the main types of desert land surface (dunes, reliefs, etc.). A discussion of the relationship between aerodynamic or geometric roughness and CYGNSS reflectivity is proposed. A high correlation is observed between these roughness parameters and reflectivity. The behaviors of the GNSS-R reflectivity and the Advanced Land Observing Satellite-2 (ALOS-2) Synthetic Aperture Radar (SAR) backscattering coefficient are compared and found to be strongly correlated. An aerodynamic roughness (Z0) map of the Sahara is proposed, using four distinct classes of terrain roughness.

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Section: Introductionmentioning

confidence: 99%

Desert Roughness Retrieval Using CYGNSS GNSS-R Data

et al. 2020

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“…A wide range of applications has been reported in the literature for GNSS-R including: water basins detection (e.g., [18,19]), river level monitoring (e.g., [20]), estimation of the surface roughness and wind retrieval (e.g., [21,22]), measurement of the soil moisture (e.g., [23][24][25][26][27]), altimetry (e.g., [28,29]), monitoring the presence of vegetation (e.g., [30,31]), and estimation of snow/ice thickness (e.g., [32]).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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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%.

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“…Although this technique was first developed for the measurement of sea surface parameters such as height [ 6 ] and roughness [ 7 ], other more recent studies have focused on the monitoring of land surface characteristics such as soil moisture [ 8 , 9 ], fraction of vegetation cover [ 10 , 11 ], forest biomass [ 12 , 13 ], the mapping of flooded areas [ 14 ], and the detection of snow or ice [ 15 , 16 ]. Experimental campaigns from both fixed [ 17 , 18 , 19 ], airborne [ 13 , 20 , 21 , 22 ], balloon [ 23 ] and more recently from Low Earth Orbit [ 24 ] platforms have confirmed the sensitivity of GNSS receivers to soil and biomass characteristics. In parallel to these experimental developments, progress has been made with electromagnetic bistatic models [ 25 , 26 , 27 , 28 , 29 ], improving scientific understanding of the scattering effects taking place in GNSS reflectometry.…”

Section: Introductionmentioning

confidence: 99%

GLORI: A GNSS-R Dual Polarization Airborne Instrument for Land Surface Monitoring

Motte

Zribi

Fanise

et al. 2016

Sensors

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Global Navigation Satellite System-Reflectometry (GNSS-R) has emerged as a remote sensing tool, which is complementary to traditional monostatic radars, for the retrieval of geophysical parameters related to surface properties. In the present paper, we describe a new polarimetric GNSS-R system, referred to as the GLObal navigation satellite system Reflectometry Instrument (GLORI), dedicated to the study of land surfaces (soil moisture, vegetation water content, forest biomass) and inland water bodies. This system was installed as a permanent payload on a French ATR42 research aircraft, from which simultaneous measurements can be carried out using other instruments, when required. Following initial laboratory qualifications, two airborne campaigns involving nine flights were performed in 2014 and 2015 in the Southwest of France, over various types of land cover, including agricultural fields and forests. Some of these flights were made concurrently with in situ ground truth campaigns. Various preliminary applications for the characterisation of agricultural and forest areas are presented. Initial analysis of the data shows that the performance of the GLORI instrument is well within specifications, with a cross-polarization isolation better than −15 dB at all elevations above 45°, a relative polarimetric calibration accuracy better than 0.5 dB, and an apparent reflectivity sensitivity better than −30 dB, thus demonstrating its strong potential for the retrieval of land surface characteristics.

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A fully software Global Navigation Satellite System reflectometry (GNSS-R) receiver for soil monitoring

Cited by 19 publications

References 45 publications

Desert Roughness Retrieval Using CYGNSS GNSS-R Data

Desert Roughness Retrieval Using CYGNSS GNSS-R Data

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

GLORI: A GNSS-R Dual Polarization Airborne Instrument for Land Surface Monitoring

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