scholarly journals Desert Roughness Retrieval Using CYGNSS GNSS-R Data

2020 ◽  
Vol 12 (4) ◽  
pp. 743 ◽  
Author(s):  
Donato Stilla ◽  
Mehrez Zribi ◽  
Nazzareno Pierdicca ◽  
Nicolas Baghdadi ◽  
Mireille Huc
Keyword(s):  
Global Navigation Satellite System ◽  
Land Surface ◽  
Temporal Stability ◽  
Temporal Analysis ◽  
Satellite System ◽  
Navigation Satellite ◽  
Global Navigation ◽  
Spatio Temporal ◽  
Aerodynamic Roughness ◽  
Global Navigation Satellite

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.

scholarly journals Evaluation of the Land GNSS-Reflected DDM Coherence on Soil Moisture Estimation from CYGNSS Data

2021 ◽  
Vol 13 (4) ◽  
pp. 570
Author(s):  
Zhounan Dong ◽  
Shuanggen Jin
Keyword(s):  
Soil Moisture ◽  
Global Navigation Satellite System ◽  
Land Surface ◽  
Satellite System ◽  
Navigation Satellite ◽  
Global Navigation ◽  
Incoherent Component ◽  
Global Navigation Satellite ◽  
The Impact ◽  
Moisture Estimation

With the development of spaceborne global navigation satellite system-reflectometry (GNSS-R), it can be used for terrestrial applications as a promising remote sensing tool, such as soil moisture (SM) retrieval. The reflected L-band GNSS signal from the land surface can simultaneously generate coherent and incoherent scattering, depending on surface roughness. However, the contribution of the incoherent component was directly ignored in previous GNSS-R land soil moisture content retrieval due to the hypothesis of its relatively small proportion. In this paper, a detection method is proposed to distinguish the coherence of land GNSS-R delay-Doppler map (DDM) from the cyclone global navigation satellite system (CYGNSS) mission in terms of DDM power-spreading features, which are characterized by different classification estimators. The results show that the trailing edge slope of normalized integrated time-delay waveform presents a better performance to recognize coherent and incoherent dominated observations, indicating that 89.6% of CYGNSS land observations are dominated by the coherent component. Furthermore, the impact of the land GNSS-Reflected DDM coherence on soil moisture retrieval is evaluated from 19-month CYGNSS data. The experiment results show that the influence of incoherent component and incoherent observations is marginal for CYGNSS soil moisture retrieval, and the RMSE of GNSS-R derived soil moisture reaches 0.04 cm3/cm3.

scholarly journals A pilot study into the use of global navigation satellite system technology to quantify the behavioural responses of sheep during simulated dog predation events

2014 ◽  
Vol 54 (10) ◽  
pp. 1676 ◽  
Author(s):  
Jaime K. Manning ◽  
Eloise S. Fogarty ◽  
Mark G. Trotter ◽  
Derek A. Schneider ◽  
Peter C. Thomson ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Global Navigation Satellite System ◽  
Satellite System ◽  
Navigation Satellite ◽  
Temporal Data ◽  
Behavioural Responses ◽  
Predation Event ◽  
Global Navigation ◽  
Spatio Temporal ◽  
Global Navigation Satellite

The predation of sheep (Ovis aries) by wild and domestic dogs (Canis lupis) is a major issue in Australia, causing serious welfare issues to inflicted animals. The estimated cost of sheep and cattle production losses caused by wild dogs when combined with an extensive range of control measures, costs the Australian economy AU$66 million annually. Spatio-temporal data derived from global navigation satellite system (GNSS) devices were used to quantify the behavioural responses of two flocks of 15 Merino ewes ranging from 2 to 8 years old (average 4.5 years) during simulated dog predation events. Each sheep was fitted with a GNSS collar, and the behavioural responses of the sheep were video recorded during six trials (three per flock). The behavioural data collated from video recordings were then compared with the movement metrics derived from the GNSS collars. Derived metrics include the spatial distribution of flock members, speed of animal movement and specific behavioural changes including centripetal rotation (circling behaviour of the flock, with individual sheep seeking the centre). While the spatial distribution data did not appear to be specific enough to enable identification of a predation event, the velocity of sheep was higher (P < 0.001) during compared with before and after a simulated dog predation event. Centripetal rotation occurred in 80% of the simulated predation events during this study, and may provide a means for identifying predation. The spatio-temporal data from GNSS devices have potential as a research tool to assist in understanding sheep movement patterns during a dog attack. While further research and mathematical modelling of predation events is clearly required, the application of remote sensing technology has the potential to improve future livestock monitoring.

scholarly journals OutFin, a multi-device and multi-modal dataset for outdoor localization based on the fingerprinting approach

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Fahad Alhomayani ◽  
Mohammad H. Mahoor
Keyword(s):  
Global Navigation Satellite System ◽  
Urban Areas ◽  
Satellite System ◽  
Reference Points ◽  
Navigation Satellite ◽  
Data Types ◽  
Entry Barrier ◽  
Promising Alternative ◽  
Global Navigation ◽  
Global Navigation Satellite

AbstractIn recent years, fingerprint-based positioning has gained researchers’ attention since it is a promising alternative to the Global Navigation Satellite System and cellular network-based localization in urban areas. Despite this, the lack of publicly available datasets that researchers can use to develop, evaluate, and compare fingerprint-based positioning solutions constitutes a high entry barrier for studies. As an effort to overcome this barrier and foster new research efforts, this paper presents OutFin, a novel dataset of outdoor location fingerprints that were collected using two different smartphones. OutFin is comprised of diverse data types such as WiFi, Bluetooth, and cellular signal strengths, in addition to measurements from various sensors including the magnetometer, accelerometer, gyroscope, barometer, and ambient light sensor. The collection area spanned four dispersed sites with a total of 122 reference points. Each site is different in terms of its visibility to the Global Navigation Satellite System and reference points’ number, arrangement, and spacing. Before OutFin was made available to the public, several experiments were conducted to validate its technical quality.

Implementation of a Dual-Frequency GLONASS and GPS L1 C/A Software Receiver

2010 ◽  
Vol 63 (2) ◽  
pp. 269-287 ◽  
Author(s):  
S. Abbasian Nik ◽  
M. G. Petovello
Keyword(s):  
Global Navigation Satellite System ◽  
Critical Role ◽  
Satellite System ◽  
Navigation Satellite ◽  
Dual Frequency ◽  
Software Receiver ◽  
The Public ◽  
Global Navigation ◽  
Global Navigation Satellite

These days, Global Navigation Satellite System (GNSS) technology plays a critical role in positioning and navigation applications. Use of GNSS is becoming more of a need to the public. Therefore, much effort is needed to make the civilian part of the system more accurate, reliable and available, especially for the safety-of-life purposes. With the recent revitalization of Russian Global Navigation Satellite System (GLONASS), with a constellation of 20 satellites in August 2009 and the promise of 24 satellites by 2010, it is worthwhile concentrating on the GLONASS system as a method of GPS augmentation to achieve more reliable and accurate navigation solutions.

scholarly journals Computation Approach for Quantitative Dielectric Constant from Time Sequential Data Observed by CYGNSS Satellites

2021 ◽  
Vol 13 (11) ◽  
pp. 2032
Author(s):  
Junchan Lee ◽  
Sunil Bisnath ◽  
Regina S.K. Lee ◽  
Narin Gavili Kilane
Keyword(s):  
Dielectric Constant ◽  
Soil Moisture ◽  
Global Navigation Satellite System ◽  
Measurement Data ◽  
Satellite System ◽  
Computation Method ◽  
Navigation Satellite ◽  
Local Soil ◽  
Global Navigation ◽  
Global Navigation Satellite

This paper describes a computation method for obtaining dielectric constant using Global Navigation Satellite System reflectometry (GNSS-R) products. Dielectric constant is a crucial component in the soil moisture retrieval process using reflected GNSS signals. The reflectivity for circular polarized signals is combined with the dielectric constant equation that is used for radiometer observations. Data from the Cyclone Global Navigation Satellite System (CYGNSS) mission, an eight-nanosatellite constellation for GNSS-R, are used for computing dielectric constant. Data from the Soil Moisture Active Passive (SMAP) mission are used to measure the soil moisture through its radiometer, and they are considered as a reference to confirm the accuracy of the new dielectric constant calculation method. The analyzed locations have been chosen that correspond to sites used for the calibration and validation of the SMAP soil moisture product using in-situ measurement data. The retrieved results, especially in the case of a specular point around Yanco, Australia, show that the estimated results track closely to the soil moisture results, and the Root Mean Square Error (RMSE) in the estimated dielectric constant is approximately 5.73. Similar results can be obtained when the specular point is located near the Texas Soil Moisture Network (TxSON), USA. These results indicate that the analysis procedure is well-defined, and it lays the foundation for obtaining quantitative soil moisture content using the GNSS reflectometry results. Future work will include applying the computation product to determine the characteristics that will allow for the separation of coherent and incoherent signals in delay Doppler maps, as well as to develop local soil moisture models.

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