GPS observations of the ionospheric F2-layer behavior during the 20th November 2003 geomagnetic storm over South Korea

The ionospheric F2-layer peak density (NmF2) and its height (hmF2) are of great influence on the shape of the ionospheric electron density profile Ne (h) and may be indicative of other physical processes within the ionosphere, especially those due to geomagnetic storms. Such parameters are often estimated using models such as the semiempirical international reference ionosphere (IRI) models or are measured using moderately priced to expensive instrumentation, such as ionosondes or incoherent scatter radars. Global positioning system (GPS) observations have become a powerful tool for mapping high-resolution ionospheric structures, which can be used to study the ionospheric response to geomagnetic storms. In this paper, we describe how 3-D ionospheric electron density profiles were produced from data of the dense permanent Korean GPS network using the tomography reconstruction technique. These profiles are verified by independent ionosonde data. The responses of GPS-derived parameters at the ionospheric F2-layer to the 20th November 2003 geomagnetic storm over South Korea are investigated. A fairly large increase in the electron density at the F2-layer peak (the NmF2) (positive storm) has been observed during this storm, which is accompanied by a significant uplift in the height of the F2 layer peak (the hmF2). This is confirmed by independent ionosonde observations. We suggest that the F2-layer peak height uplift and NmF2 increase are mainly associated with a strong eastward electric field, and are not associated with the increase of the O/N₂ ratio obtained from the GUVI instruments aboard the TIMED satellite. It is also inferred that the increase in NmF2 is not caused by the changes in neutral composition, but is related to other nonchemical effects, such as dynamical changes of vertical ion motions induced by winds and E × B drifts, tides and waves in the mesosphere/lower thermosphere region, which can be dynamically coupled upward to generate ionospheric perturbations and oscillations.     

High-Resolution Forecast Models of Water Vapor Over Mountains: Comparison With MERIS and Meteosat Data

Propagation delay due to variable tropospheric water vapor (WV) is one of the most intractable problems for radar interferometry, particularly over mountains. The WV field can be simulated by an atmospheric model, and the difference between the two fields is used to correct the radar interferogram. Here, we report our use of the U.K. Met Office Unified Model in a nested mode to produce high-resolution forecast fields for the 3-km-high Mount Etna volcano. The simulated precipitable-water field is validated against that retrieved from the Medium-Resolution Imaging Spectrometer (MERIS) radiometer on the Envisat satellite, which has a resolution of 300 m. Two case studies, one from winter (November 24, 2004) and one from summer (June 25, 2005), show that the mismatch between the model and the MERIS fields ( rms = 1.1 and 1.6 mm, respectively) is small. One of the main potential sources of error in the models is the timing of the WV field simulation. We show that long-wavelength upper tropospheric troughs of low WV could be identified in both the model output and Meteosat WV imagery for the November 24, 2004 case and used to choose the best time of model output.     

Non-destructive estimation of potato leaf chlorophyll from canopy hyperspectral reflectance using the inverted PROSAIL model

Optimizing nitrogen (N) fertilization in crop production by in-season measurements of crop N status may improve fertilizer N use efficiency. Hyperspectral measurements may be used to assess crop N status by estimating leaf chlorophyll content. This study evaluated the ability of the PROSAIL canopy-level reflectance model to predict leaf chlorophyll content. Trials were conducted with two potato cultivars under different N fertility rates (0–300 kg N ha⁻¹). Canopy reflectance, leaf area index (LAI) and leaf chlorophyll and N contents were measured. The PROSAIL model was able to predict leaf chlorophyll content with reasonable accuracy later in the growing season. The low estimation accuracy earlier in the growing season could be due to model sensitivity to non-homogenous canopy architecture and soil background interference before full canopy closure. Canopy chlorophyll content (leaf chlorophyll content × LAI) was predicted less accurately than leaf chlrophyll content due to the low estimation accuracy of LAI for values higher than 4.5.     

VLBI-derived troposphere parameters during CONT08

Time-series of zenith wet and total troposphere delays as well as north and east gradients are compared, and zenith total delays (ZTD) are combined on the level of parameter estimates. Input data sets are provided by ten Analysis Centers (ACs) of the International VLBI Service for Geodesy and Astrometry (IVS) for the CONT08 campaign (12?C26 August 2008). The inconsistent usage of meteorological data and models, such as mapping functions, causes systematics among the ACs, and differing parameterizations and constraints add noise to the troposphere parameter estimates. The empirical standard deviation of ZTD among the ACs with regard to an unweighted mean is 4.6?mm. The ratio of the analysis noise to the observation noise assessed by the operator/software impact (OSI) model is about 2.5. These and other effects have to be accounted for to improve the intra-technique combination of VLBI-derived troposphere parameters. While the largest systematics caused by inconsistent usage of meteorological data can be avoided and the application of different mapping functions can be considered by applying empirical corrections, the noise has to be modeled in the stochastic model of intra-technique combination. The application of different stochastic models shows no significant effects on the combined parameters but results in different mean formal errors: the mean formal errors of the combined ZTD are 2.3?mm (unweighted), 4.4?mm (diagonal), 8.6?mm [variance component (VC) estimation], and 8.6?mm (operator/software impact, OSI). On the one hand, the OSI model, i.e. the inclusion of off-diagonal elements in the cofactor-matrix, considers the reapplication of observations yielding a factor of about two for mean formal errors as compared to the diagonal approach. On the other hand, the combination based on VC estimation shows large differences among the VCs and exhibits a comparable scaling of formal errors. Thus, for the combination of troposphere parameters a combination of the two extensions of the stochastic model is recommended.     

SIMD correlator library for GNSS software receivers

Software receivers have had a discernable impact on the GNSS research community. Often such receivers are implemented in a compiled programming language, such as C or C++. A software receiver must emulate the digital signal processing (DSP) algorithms executed on dedicated hardware in a traditional receiver. The DSP algorithms, most notably correlation, have a high computational cost; this burden precludes many software receivers from running in real time. However, the computational cost can be lessened by utilizing single instruction multiple data (SIMD) operations found on modern ×86 processors. The following demonstrates how C/C++ compatible code can be written to directly utilize the SIMD instructions. First, an analysis is carried out to demonstrate why real time operation is not possible when using traditional C/C++ code is carried out. Secondly a tutorial outlines how to write and insert ×86 assembly, with SIMD operations, into C/C++ code. Performance gains achieved via SIMD operations are then demonstrated, and pseudo code outlines how SIMD operations can be employed to perform correlation. Finally, a C/C++ compatible SIMD enabled arithmetic library is added to the GPS Toolbox for use in software receivers.     

A high-precision heuristic model to detect home and work locations from smart card data

Smart card-automated fare collection systems now routinely record large volumes of data comprising the origins and destinations of travelers. Processing and analyzing these data open new opportunities in urban modeling and travel behavior research. This study seeks to develop an accurate framework for the study of urban mobility from smart card data by developing a heuristic primary location model to identify the home and work locations. The model uses journey counts as an indicator of usage regularity, visit-frequency to identify activity locations for regular commuters, and stay-time for the classification of work and home locations and activities. London is taken as a case study, and the model results were validated against survey data from the London Travel Demand Survey and volunteer survey. Results demonstrate that the proposed model is able to detect meaningful home and work places with high precision. This study offers a new and cost-effective approach to travel behavior and demand research.     

Predicting plant water content in Eucalyptus grandis forest stands in KwaZulu-Natal,South Africa using field spectra resampled to the Sumbandila Satellite Sensor

The measurement of plant water content is essential to assess stress and disturbance in forest plantations. Traditional techniques to assess plant water content are costly, time consuming and spatially restrictive. Remote sensing techniques offer the alternative of a non-destructive and instantaneous method of assessing plant water content over large spatial scales where ground measurements would be impossible on a regular basis. In the context of South Africa, due to the cost and availability of imagery, studies focusing on the estimation of plant water content using remote sensing data have been limited. With the scheduled launch of the South African satellite SumbandilaSat evident in 2009, it is imperative to test the utility of this satellite in estimating plant water content. This study resamples field spectral data measured from a field spectrometer to the band settings of the SumbandilaSat in order to test its potential in estimating plant water content in a Eucalyptus plantation. The resampled SumbandilaSat wavebands were input into a neural network due to its ability to model non-linearity in a dataset and its inherent ability to perform better than conventional linear models. The integrated approach involving neural networks and the resampled field spectral data successfully predicted plant water content with a correlation coefficient of 0.74 and a root mean square error (RMSE) of 1.41% on an independent test dataset outperforming the traditional multiple regression method of estimation. The best-trained neural network algorithm that was chosen for assessing the relationship between plant water content and the SumbandilaSat bands was based on a few points only and more research is required to test the robustness and effectiveness of this sensor in estimating plant water content across different species and seasons. This is critical for monitoring plantation health in South Africa using a cheaply available local sensor containing key vegetation wavelengths.     

Variability analysis of groundwater levels — AGIS-based case study

The present study has analyzed the variability in depth to water level below ground level (bgl) vis-à-vis groundwater development and rainfall from 1987 to 2007 in agriculture dominated Kaithal district of Haryana state in India. Spatial distribution of groundwater depth was mapped and classified into different zones using ILWIS 3.6 GIS tools. Change detection maps were prepared for 1987–1997 and 1997–2007. Groundwater depletion rates during successive decades were compared and critical areas with substantial fall in groundwater levels were identified. Further, block wise trends of change in groundwater levels were also analyzed. The water table in fresh belt areas of the district (Gulha, Pundri and Kaithal blocks) was observed to decline by a magnitude ranging from 10 m to 23 m. In Kalayat and Rajaund blocks, the levels were found fluctuating in a relatively narrow range of 4–9 m. During 1997–2007, the depletion has been faster compared to the preceding decade. Excessive groundwater depletion in major part of the district may be attributed to indiscriminate abstraction for irrigation and decrease in rainfall experienced since 1998. Changes in cropping pattern and irrigation methods are needed in the study area for sustainable management of the resource.     

Automated GPS Data Analysis Service

Automatic analysis of geodetic-quality GPS data is available with the use of e-mail and ftp (file transfer program) as an interface to a computer at the Jet Propulsion Laboratory (JPL), where precise transmitter parameters – GPS ephemerides and clock errors – are computed regularly. The interface is such that e-mail from an external user causes the JPL computer to fetch the user's data. The computer than analyzes the data, and places the results in an area accessible to the user. An e-mail to the user gives information on the location of the analysis results, which the user can subsequently fetch. Operations on the JPL computer are entirely automatic, and require essentially no labor. ? 1999 John Wiley & Sons, Inc.     

Characterization of Doppler collision and its impact on carrier phase ambiguity resolution using geostationary satellites

GPS Solutions - Doppler collision is a unique phenomenon in GNSS where tracking errors are introduced in the measurements due to cross-correlation between two or more satellites. It occurs when the...