Integration and Sharing of Geo-spatial Data Based on Data Engine

Through analyzing the principle of data sharing in the database system, this paper discusses the principle and method for integrating and sharing GIS data by data engine, introduces a way to achieve the high integration and sharing of GIS data on the basis of VCT in VC , and provides the method for uniting VCT into RDBMS in order to implement a spatial database with object-oriented data model.     

LightSquared effects on estimated C/N 0, pseudoranges and positions

We present experimental results showing the impact of the proposed LightSquared (LS) Long-term Evolution (LTE) signals on both GPS and Galileo civil modulations in the L1/E1 band. The experiments were conducted in radiated mode in a large anechoic chamber. Three Galileo enabled receivers were chosen for the tests, and a state of the art GNSS signal generator was used to simulate both GPS and Galileo signals. The LTE signals were generated by an Agilent Programmable Signal Generator with a license to generate the signals according to the 3GPP LTE FDD standard. The interference impact was measured in terms of a Carrier-to-Noise power spectral density ratio (C/N ₀) degradation, in accordance with the methodology which the LS/GPS Technical Working Group (TWG) established by mandate of the FCC. A model for determining the impact of the LS signal on the considered GNSS signals is provided and is validated against experimental data. It is shown that the Galileo E1 Open Service (OS) signal is marginally more susceptible to this form of interference than the GPS L1 C/A signal due to its greater proximity to the lower edge of the L1 band. The impact of LS interference was further analyzed in terms of pseudorange and position errors. Despite its relevance for most GNSS users, this aspect was not considered by the TWG. Measurement and position domain analysis along with the study of the LS impact on the Galileo OS signals are the major contributions. The analysis confirms the results obtained by the TWG and shows that the receiver front-end plays a major role in protecting GNSS signals against RF interference. While it appears that, for now, the LS network will not be deployed, the approach taken and the results obtained herein can be readily adapted for any future terrestrial mobile network that may take the place of LS.     

The effects of frequency-dependent quasar variability on the celestial reference frame

We examine the relationship between source position stability and astrophysical properties of radio-loud quasars making up the International Celestial Reference Frame (ICRF2). Understanding this relationship is important for improving quasar selection and analysis strategies, and therefore reference frame stability. We construct flux density time series, known as light curves, for 95 of the most frequently observed ICRF2 quasars at both the 2.3 and 8.4 GHz geodetic very long baseline interferometry (VLBI) observing bands. Because the appearance of new quasar components corresponds to an increase in quasar flux density, these light curves alert us about potential changes in source structure before they appear in VLBI images. We test how source position stability depends on three astrophysical parameters: (1) flux density variability at X band; (2) time lag between flares in S and X bands; (3) spectral index root-mean-square (rms), defined as the variability in the ratio between S and X band flux densities. We find that the time lag between S and X band light curves provides a good indicator of position stability: sources with time lags $<$ 0.06 years are significantly more stable ( $>$ 20 % improvement in weighted rms) than sources with larger time lags. A similar improvement is obtained by observing sources with low $(<$ 0.12) spectral index variability. On the other hand, there is no strong dependence of source position stability on flux density variability in a single frequency band. These findings can be understood by interpreting the time lag between S and X band light curves as a measure of the size of the source structure. Monitoring of source flux density at multiple frequencies therefore appears to provide a useful probe of quasar structure on scales important to geodesy. The observed astrometric position of the brightest quasar component (the core) is known to depend on observing frequency. We show how multi-frequency flux density monitoring may allow the dependence on frequency of the relative core positions along the jet to be elucidated. Knowledge of the position–frequency relation has important implications for current and future geodetic VLBI programs, as well as the alignment between the radio and optical celestial reference frames.     

Use of the L2C signal for inversions of GPS radio occultation data in the neutral atmosphere

Results from processing FORMOSAT-3/COSMIC radio occultations (RO) with the new GPS L2C signal acquired both in phase locked loop (PLL) and open loop (OL) modes are presented. Analysis of L2P, L2C, and L1CA signals acquired in PLL mode shows that in the presence of strong ionospheric scintillation not only L2P tracking, but also L1CA tracking often fails, while L2C tracking is most stable. The use of L2C improves current RO processing in the neutral atmosphere mainly by increasing the number of processed occultations (due to significant reduction in the number of L2 tracking failures) and marginally by a reduction in noise in statistics. The latter is due to the combination of reduced L2C noise (compared to L2P) and increased L1CA noise in those occultations where L2P would have failed. This result suggests application of OL tracking for L1CA and L2C signals throughout an entire occultation to optimally acquire RO data. Two methods of concurrent processing of L1CA and L2C RO signals are considered. Based on testing of individual occultations, these methods allow: (1) reduction in uncertainty of bending angles retrieved by wave optics in the lower troposphere and (2) reduction in small-scale residual errors of the ionospheric correction in the stratosphere.     

Automated approaches for displaying spatially oriented time‐series data through image processing techniques

This study demonstrated the cartographic implications of automated image processing and computer graphics for the study of time‐series data. Automated statistical and image processing techniques were applied to a case study data set consisting of weekly Crop Moisture Index (CMI) values summarized at 174 state cooperative weather stations within Oklahoma for the time period between February and October, 1980. Computer generated isoline maps of the CMI values were interpolated and rescaled into a series of 32 grid matrices for input into a raster‐based ERDAS image processing software system. Principal Components Analysis (PCA) was used to develop graphic models that synthesized the multi‐temporal data into statistical dimensions that represented the most significant elements of CMI variability. Graphic models of the PCA statistical vectors were displayed individually, in conjunction with eigenvector loadings, and as composite images. Resultant images were analyzed statistically and graphically through the generated CMI grid matrices to ascertain the location, severity, and progression of drought represented in the CMI values. Traditional image processing techniques and devices were combined with the ERDAS software system to transform the multi‐temporal CMI data into multi‐dimensional images that represented the drought's spatial and temporal signature unobscured by redundant information.     

Satellite remote sensing of forest type and landcover in the subalpine forest region,Kananaskis Valley,Alberta

Landsat Thematic Mapper (TM) imagery and a digital elevation model (DEM) of the Kananaskis Valley in southwestern Alberta have been used to separate three forest types and eight landcover classes with mapping accuracies up to 76% overall. Image transformations based on a principal components analysis (PCA) were used to distinguish vegetation type and separate surface features in visual interpretations, and to reduce the 10 channel data set (TM 1–7, elevation, slope and incidence) to a more manageable 7 channel data set (PCA 1–4, elevation, slope and incidence). The DEM was shown to be critical in providing explanation of surface cover variability even though the original model was produced from medium scale aerial photography on a relatively coarse 100 metre grid. Discrimination increased up to 50% for pure stands of Lodgepole Pine (Pinus contorta Dougl.) and Englemann Spruce (Picea englemanii Parry) based on analysis of 100 pixels in test areas. Overall increases in map accuracy were between 2 and 11%. Success at this level of classification is required prior to detailed ecological study and modelling of mountain vegetation productivity at the community level using current satellite and aerial remote sensing technology.     

Crop area monitoring within an advanced agricultural information system

This paper describes a framework for an image processing procedure for operational agricultural crop area estimation. This operational framework has been conceived within the development of an Advanced Agricultural Information System (AAIS) for the “Regione del Veneto “ (RdV ‐ Veneto Region) in northeastern Italy. The objective of this program is to develop the ability to generating timely and accurate area estimates and production information for four major agricultural crops: soybeans, sugar beets, corn, and small grains. AAIS uses state of the art methods in remote sensing and geographic information systems (GIS) technology and integrates a variety of data types including satellite imagery. This paper describes the methodology developed for image and ancillary data processing for the production of crop area statistics. Using a combination of standard unsupervised classification and GIS operations that incorporate knowledge about the agricultural system, a “sequential masking” classification procedure was derived. This sequential masking procedure yielded crop classification accuracies that at the study site level range between 76% and 99% depending on the crop under study. We believe that classification accuracies will improve with full system implementation, along with the incorporation of new and/or improved thematic information and operational experience using AAIS‐based estimation.     

ANALYSIS OF THE CHEMICAL POLLUTION OF BUFFER ZONES BY MODELING AND SUB-SATELLITE EXPERIMENTS

Principles are outlined for the use of sub-satellite soil, air, water, and vegetation samples as an auxiliary source of information in remote sensing studies of vegetation stress caused by air pollution. More specifically, procedures for satellite-synchronous aerial overflights, vegetation transects, water quality measurements, and soil tests are described as a basis for delineating boundaries between areas of vegetation stress and unpolluted areas in an industrialized area in the central Urals. Translated from: Kosmicheskiy monitoring biosfery, Yu. A. Izrael', V. V. Bugrovskiy, and Yu. V. Novikov, eds. Leningrad: Gidrometeoizdat, 1985, pp. 93-99.     

EXPERIENCE IN COMPILING LARGE-SCALE MAPS OF EROSION-PRONE AREAS

Specific criteria used in the compilation of large-scale maps of erosion-prone areas are defined and evaluated for tracts of land representing a number of different agricultural cover types. Formulas are derived which facilitate the mapping of such areas based on such readily observable morphometric characteristics as slope length and steepness. Translated by Edward Torrey, Alexandria, VA 22308 from: Vestnik Moskovskogo Universiteta, geografiya, 1988, No. 5, pp. 25-31.     

COMPUTATION AND MAPPING OF THE ELEMENTS OF THE WATER-ICE BUDGET OF GLACIERS

Two general approaches for compiling maps of components of the water-ice budget in regions of glacier nourishment are compared and the resulting maps are analyzed. The compilation of raw data is based on field measurements rather than remote sensing information. Translated by Edward Torrey, Alexandria, VA 22308 from: Materialy glyatsiologicheskikh issledovaniy, 1991, No. 72, pp. 94-102.