SAVERS: A Simulator of GNSS Reflections From Bare and Vegetated Soils

Pierdicca, Nazzareno; Guerriero, L.; Giusto, R.; Brogioni, Marco; Egido, Alejandro

doi:10.1109/tgrs.2013.2297572

Cited by 99 publications

(56 citation statements)

References 20 publications

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“…Several theoretical studies have shown that the elevation angle has an influence on the bistatic signal penetration down to the soil and the retrieval of vegetation parameters [33,34]. For this reason, our statistical analysis of the GNSS-R measurements makes use of two elevation intervals (50-70 • and 70-90 • ).…”

Section: Discussionmentioning

confidence: 99%

Potential Applications of GNSS-R Observations over Agricultural Areas: Results from the GLORI Airborne Campaign

et al. 2018

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Abstract:The aim of this study is to analyze the sensitivity of airborne Global Navigation Satellite System Reflectometry (GNSS-R) on soil surface and vegetation cover characteristics in agricultural areas. Airborne polarimetric GNSS-R data were acquired in the context of the GLORI'2015 campaign over two study sites in Southwest France in June and July of 2015. Ground measurements of soil surface parameters (moisture content) and vegetation characteristics (leaf area index (LAI), and vegetation height) were recorded for different types of crops (corn, sunflower, wheat, soybean, vegetable) simultaneously with the airborne GNSS-R measurements. Three GNSS-R observables (apparent reflectivity, the reflected signal-to-noise-ratio (SNR), and the polarimetric ratio (PR)) were found to be well correlated with soil moisture and a major vegetation characteristic (LAI). A tau-omega model was used to explain the dependence of the GNSS-R reflectivity on both the soil moisture and vegetation parameters.

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Section: Discussionmentioning

confidence: 99%

Potential Applications of GNSS-R Observations over Agricultural Areas: Results from the GLORI Airborne Campaign

et al. 2018

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“…Systematic errors may also change slowly with time; e.g. the impact of signal multipath at a GNSS site may vary due to growing vegetation (Pierdicca et al, 2014).…”

Section: T Ning Et Al: the Uncertainty Of The Gnss-derived Iwvmentioning

confidence: 99%

The uncertainty of the atmospheric integrated water vapour estimated from GNSS observations

et al. 2016

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Abstract. Within the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) there is a need for an assessment of the uncertainty in the integrated water vapour (IWV) in the atmosphere estimated from ground-based global navigation satellite system (GNSS) observations. All relevant error sources in GNSS-derived IWV are therefore essential to be investigated. We present two approaches, a statistical and a theoretical analysis, for the assessment of the uncertainty of the IWV. The method is valuable for all applications of GNSS IWV data in atmospheric research and weather forecast. It will be implemented to the GNSS IWV data stream for GRUAN in order to assign a specific uncertainty to each data point. In addition, specific recommendations are made to GRUAN on hardware, software, and data processing practices to minimise the IWV uncertainty. By combining the uncertainties associated with the input variables in the estimations of the IWV, we calculated the IWV uncertainties for several GRUAN sites with different weather conditions. The results show a similar relative importance of all uncertainty contributions where the uncertainties in the zenith total delay (ZTD) dominate the error budget of the IWV, contributing over 75 % of the total IWV uncertainty. The impact of the uncertainty associated with the conversion factor between the IWV and the zenith wet delay (ZWD) is proportional to the amount of water vapour and increases slightly for moist weather conditions. The GRUAN GNSS IWV uncertainty data will provide a quantified confidence to be used for the validation of other measurement techniques.

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“…The hardware changes and the difference in measurements usually result in a constant offset (Johansson 1998), while the inconsistences due to the latter change are normally varying when reflective properties change. For example, a bias due to growing vegetation changes continuously for a certain time period (Pierdicca et al 2014), while the cutting of trees and/or different soil moisture (i.e., rain and snow) introduce a sudden bias (Larson et al 2010). Signal multipath effects are worse for observations at low elevation angles.…”

Section: Introductionmentioning

confidence: 99%

Homogenized Time Series of the Atmospheric Water Vapor Content Obtained from the GNSS Reprocessed Data

et al. 2016

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The potential temporal shifts in the integrated water vapor (IWV) time series obtained from reprocessed data acquired from global navigation satellite systems (GNSS) were comprehensively investigated. A statistical test, the penalized maximal t test modified to account for first-order autoregressive noise in time series (PMTred), was used to identify the possible mean shifts (changepoints) in the time series of the difference between the GPS IWV and the IWV obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) data. The approach allows for identification of the changepoints not only in the GPS IWV time series but also in ERA-Interim. The IWV difference time series formed for 101 GPS sites were tested, where 47 of them were found to contain in total 62 changepoints. The results indicate that 45 detected changepoints were due to the inconsistencies in the GPS IWV time series, and 16 were related to ERA-Interim, while one point was left unverified. After the correction of the mean shifts for the GPS data, an improved consistency in the IWV trends is evident between nearby sites, while a better agreement is seen between the trends from the GPS and ERA-Interim data on a global scale. In addition, the IWV trends estimated for 47 GPS sites were compared to the corresponding IWV trends obtained from nearby homogenized radiosonde data. The correlation coefficient of the trends increases significantly by 38% after using the homogenized GPS data.

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SAVERS: A Simulator of GNSS Reflections From Bare and Vegetated Soils

Cited by 99 publications

References 20 publications

Potential Applications of GNSS-R Observations over Agricultural Areas: Results from the GLORI Airborne Campaign

Potential Applications of GNSS-R Observations over Agricultural Areas: Results from the GLORI Airborne Campaign

The uncertainty of the atmospheric integrated water vapour estimated from GNSS observations

Homogenized Time Series of the Atmospheric Water Vapor Content Obtained from the GNSS Reprocessed Data

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