Widespread environmental impacts of frequent drought episodes in Brazil have resulted in several droughtrelated diagnostics studies. However, the potential of many "opportunistic sensors", such as the Global Positioning System (GPS), has not yet been considered in hydrological hazard monitoring in Brazil. In this study, the response of the Earth's crust to Brazil's 2012-2015 drought event in different structural provinces is analyzed by comparing GPS-observed vertical crustal deformations (VCDs) with the terrestrial water storage (TWS) derived from the Gravity Recovery and Climate Experiment (GRACE). The results indicate that there is no spatial correlation between annual amplitudes of the TWS and VCDs in different structural provinces apart from the purely elastic response of the crust to TWS dynamics, at almost all the 39 GPS stations that were analyzed. However, approximately 15% of the monitoring stations show that VCD leads TWS with a phase lag of 2-4 months. Errors associated with VCD and TWS are within the accepted range for space geodetic techniques (i.e., GPS and GRACE) and despite the need for further investigation, the phase lead seems to be associated with rainfall, which impacts the TWS through the hydrographs. Overall, the GPS-based drought index (DIVCD) reflects the water depletion in many regions of Brazil, which agrees with

Surface reconstruction from point clouds generated by laser scanning technology has become a fundamental task in many fields of geosciences, such as robotics, computer vision, digital photogrammetry, computational geometry, digital building modelling, forest planning and operational activities. Point clouds produced by laser scanning, however, are limited due to the occurrence of occlusions, multiple reflectance and noise, and off-surface points (outliers), thus necessitating the need for robust fitting techniques. In this contribution, a fast, non-iterative and data invariant algebraic algorithm with constant O(1) complexity that fits planes to point clouds in the total least squares sense using Gaussian-type error distribution is proposed. The maximum likelihood estimator method is used, resulting in a multivariate polynomial system that is solved in an algebraic way. It is shown that for plane fitting when datasets are affected heavily by outliers, the proposed algebraic method can be embedded into the framework of robust methods like the Danish or the RANdom SAmple Consensus methods and computed in parallel to provide rigorous algebraic fitting with significantly reduced running times. Compared to the embedded traditional singular value decomposition and principal component analysis approaches, the performance of the proposed algebraic algorithm demonstrated its efficiency on both synthetic data and real laser-scanned measurements. The evaluation of a symbolic algebraic formula is practically independent of the values of its coefficients; however, the computation of the coefficients depends on the complexity of the data. Since the main advantage of the symbolic solution is its non-requirement of numerical iteration, the data complexity will have weak influence on the speed-up. The novelty of the proposed method is the use of algebraic technique in a robust plane fitting algorithm that could be applied to remote sensing data analysis/delineation/classification. In general, the method could be applied to most plane fitting problems in the geoscience field.

In general, any national or regional height reference system is related to an individual vertical datum, defined by one or several tide gauges. The discrepancies of these local vertical datums cause height datum offsets in a range of about +/- 1-2 m at a global scale. For the purpose of height system unification, global geopotential models derived from homogeneous satellite data provide an important contribution. However, to achieve a unification of high precision, the use of local terrestrial gravity data in the framework of a Geodetic Boundary Value Problem (GBVP) is required. By solving the GBVP at GNSS/leveling benchmarks, the unknown height datum offsets can be estimated in a least squares adjustment. In contrast to previous studies, related to the scalar free GBVP based on gravity anomalies, this paper discusses the alternative use and benefit of the fixed GBVP. This modern formulation of the GBVP is related to gravity disturbances, using the surface of the Earth as boundary surface. In contrast to gravity anomalies, gravity disturbances are not affected by the discrepancies of the local height datum. Therefore, in comparison to a scalar free GBVP approach, the proposed method is not affected by indirect bias terms, which will simplify a height system unification. In this paper, the theory of the fixed GBVP approach is developed and formulas in spherical approximation are derived. Moreover, the method is validated using a closed loop simulation based on the global geopotential model EGM2008, showing mm-accuracy of the estimated height datum offsets.

Spatio-temporal patterns of hydrological droughts over the Greater Horn of Africa (GHA) are explored based on total water storage (TWS) changes derived from time-variable gravity field solutions of Gravity Recovery And Climate Experiment (GRACE, 2002-2014), together with those simulated by Modern Retrospective Analysis for Research Application (MERRA, 1980-2014). These hydrological extremes are then related to meteorological drought events estimated from observed monthly precipitation products of Global Precipitation Climatology Center (GPCC, 1979-2010) and Tropical Rainfall Measuring Mission (TRMM, 1998-2014). The major focus of this contribution lies on the application of spatial Independent Component Analysis (sICA) to extract distinguished regions with similar rainfall and TWS with similar overall trend and seasonality. Rainfall and TWS are used to estimate Standard Precipitation Indices (SPIs) and Total Storage Deficit Indices (TSDIs), respectively that are employed to characterize frequency and intensity of hydro-meteorological droughts over GHA. Significant positive (negative) changes in monthly rainfall over Ethiopia (Sudan) between 2002 and 2010 leading to a significant increase in TWS over the central GHA region were noted in both MERRA and GRACE TWS (2002-2014). However, these trends were completely reversed in the long-term (1980-2010) records of rainfall (GPCC) and TWS (MERRA). The four independent hydrological sub-regions extracted based on the sICA (i.e., Lake Victoria Basin, Ethiopia Sudanese border, South Sudan, and Tanzania) indicated fairly distinct temporal patterns that matched reasonably well between precipitation and TWS changes. While meteorological droughts were found to be consistent with most previous studies in all sub-regions, their impacts are clearly observed in the TWS changes resulting in multiple years of extreme hydrological droughts. Correlations between SPI and TSDI were found to be significant over Lake Victoria Basin, South Sudan, and Tanzania. The low correlations between SPI and TSDI over Ethiopia are likely related to inconsistency between TWS and precipitation signals. Further, we found that hydrological droughts in these regions were significantly associated with Indian Ocean Dipole (IOD) events while El Nifio Southern Oscillation (ENSO) plays a secondary role. (C) 2016 Elsevier Ltd. All rights reserved.

The usage of individual calibration values for GNSS (Global Navigation Satellite Systems) antennas is of fundamental importance for state-of-the-art GNSS positioning at millimeter accuracy level, especially concerning precise height determination. In Brazil, the awareness of the user community regarding this important error source has to be sharpened. In contrast to Europe, where manifold research is carried out focusing on antenna calibration and different agencies provide calibration services, in Latin America the users have to be sensitized with respect to receiver antenna handling. Therefore, the first Latin American GNSS antenna calibration basis BCAL/UFPR (Baseline Calibration Station for GNSS Antennas at UFPR) was established at the Federal University of Parana (UFPR; Curitiba, Parana, Brazil) in close cooperation with the Geodetic Institute of the Karlsruhe Institute of Technology (Karlsruhe, Germany). The BCAL/UFPR is actually equipped with three pillars and enables the determination of antenna parameters applying the relative field calibration approach. The antenna modeling parameters are derived at absolute level, because the reference antenna (3D choke ring antenna type) was calibrated absolutely by GeoCC (Garbsen, Germany). In this context, five antennas of the same model (Trimble Zephyr GNSS Geodetic II) were calibrated at BCAL/UFPR. The goal of the case study is to verify the difference between individual parameters determined at BCAL/UFPR and mean parameters published by the NGS (National Geodetic Service, USA). This article presents information related to BCAL/UFPR and discusses the results of recent calibration investigations.

Remote sensing data have been increasingly used to measure the content of water vapor in the atmosphere and to characterize its temporal and spatial variations. In this paper, we use observations from Global Navigation Satellite System(s) (GNSS) to estimate time series of precipitable water vapor (PWV) by applying the technique of precise point positioning. For an accurate quantification of the absolute PWV, it is necessary to combine the GNSS observations with meteorological data measured directly or inferred at the GNSS site. In addition, measurements of the surface temperature are used to calculate the empirical constant required to convert the GNSS-based delay into water vapor. Our results show strong agreement between the total precipitable water estimated based on GNSS observations and that measured by the sensor MEdium Resolution Imaging Spectrometer with a mean RMS value of 0.98 mm. In a similar way, we compared the GNSS-based total PWV estimates with those produced by the Weather Research and Forecasting (WRF) Modeling System. We found that the WRF model simulations agree well with the GNSS estimates with a mean RMS value of 0.97 mm.

The intra-plate deformation of the Upper Rhine Graben (URG) located in Central Europe is investigated using geodetic measurement techniques. We present a new approach to calculate a combined velocity field from InSAR, levelling and GNSS measurements. As the expected tectonic movements in the URG area are small (less than 1 mm a(-1)), the best possible solutions for linear velocity rates from single-technique analyses are estimated in a first step. Second, we combine the velocity rates obtained from InSAR (line of sight velocity rates in ascending and descending image geometries), levelling (vertical velocity rates) and GNSS (horizontal velocity rates) using least-squares adjustment (LSA). Focusing on the Northern URG area, we analyse SAR data on four different image stacks (ERS ascending, ERS descending, Envisat ascending, Envisat descending) using the Persistent Scatterer (PS) approach. The linear velocity rates in ascending and descending image geometries, respectively, are estimated in an LSA from joint time-series analysis of ERS and Envisat data. Vertical velocity rates from levelling are obtained from a consistent adjustment of more than 40 000 measured height differences using a kinematic displacement model. Horizontal velocity rates in east and north direction are calculated from a time-series analysis of daily coordinate estimates at 76 permanently operating GNSS sites in the URG region. As the locations, at which the measurement data of PS-InSAR, levelling and GNSS reside, do not coincide, spatial interpolation is needed during several steps of the rigorous processing. We use Ordinary Kriging to interpolate from a given set of data points to the locations of interest with a special focus on the modeling and propagation of errors. The final 3-D velocity field is calculated at a 200 m grid, which carries values only close to the location of PS points, resulting in a mean horizontal and vertical precision of 0.30 and 0.13 mm a(-1), respectively. The vertical component of the combined velocity field shows a significant subsidence of about 0.5 mm a(-1) in the northern part of the graben coinciding with a well-known quaternary basin structure. Horizontal displacement rates of up to 0.8 mm a(-1) in southeast direction are observed outside the graben, in reasonable alignment with the average direction of maximum horizontal stress. Within the graben, the velocity directions rotate toward east in the non-subsiding part, while an opposite trend is observed in the subsiding part of the graben. The complexities of the observed velocity field are compatible to the geomechanical situation in our investigation area which is characterized by a transition from a restraining to a releasing bend setting. Glacial isostatic adjustment is another potential source influencing the observed velocity field, as well as anthropogenic signals due to mining, oil exploration and groundwater usage that have been identified in some places.

Understanding water storage changes within the Nile's main sub-basins and the related impacts of climate variability is an essential step in managing its water resources. The Gravity Recovery And Climate Experiment (GRACE) satellite mission provides a unique opportunity to monitor changes in total water storage (TWS) of large river basins such as the Nile. Use of GRACE-TWS changes for monitoring the Nile is, however, difficult since stronger TWS signals over the Lake Victoria Basin (LVB) and the Red Sea obscure those from smaller sub-basins making their analysis difficult to undertake. To mitigate this problem, this study employed Independent Component Analysis (ICA) to extract statistically independent TWS patterns over the sub-basins from GRACE and the Global Land Data Assimilation System (GLDAS) model. Monthly precipitation from the Tropical Rainfall Measuring Mission (TRMM) over the entire Nile Basin are also analysed by ICA. Such extraction enables an in-depth analysis of water storage changes within each sub-basin and provides a tool for assessing the influence of anthropogenic as well as climate variability caused by large scale ocean-atmosphere interactions such as the El Nino Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). Our results indicate that LVB experienced effects of both anthropogenic and climate variability (i. e., a correlation of 0.56 between TWS changes and IOD at 95% confidence level) during the study period 2002-2011, with a sharp drop in rainfall between November and December 2010, the lowest during the entire study period, and coinciding with the drought that affected the Greater Horn of Africa. Ethiopian Highlands (EH) generally exhibited a declining trend in the annual rainfall over the study period, which worsened during 2007-2010, possibly contributing to the 2011 drought over GHA. A correlation of 0.56 was found between ENSO and TWS changes over EH indicating ENSO's dominant influence. TWS changes over Bar-el-Ghazal experienced mixed increase-decrease, with ENSO being the dominant climate variability in the region during the study period. A remarkable signal is noticed over the Lake Nasser region indicating the possibility of the region losing water not only through evaporation, but also possibly through over extraction from wells in the Western Plateau (Nubian aquifer). (C) 2014 Elsevier Ltd. All rights reserved.

It has been postulated that Lake Naivasha, Kenya, has experienced a rapid decrease (and fluctuations) in its spatial extent and level between the years 2002 to 2010. Many factors have been advanced to explain this, with horticultural and floricultural activities, as well as climatic change, featuring prominently. This study offers a multi-disciplinary approach based on several different types of space-borne observations to look at the problem bedeviling Lake Naivasha, which is a Ramsar listed wetland of international importance. The data includes: (1) Gravity Recovery and Climate Experiment (GRACE) time-variable gravity field products to derive total water storage (TWS) variations within a region covering the Lakes Naivasha and Victoria basins; (2) precipitation records based on Tropical Rainfall Measurement Mission (TRMM) products to evaluate the impact of climate change; (3) satellite remote sensing (Landsat) images to map shoreline changes and to correlate these changes over time with possible causes; and (4) satellite altimetry observations to assess fluctuations in the lake's level. In addition, data from an in situ tide gauge and rainfall stations as well as the output from the African Drought Monitor (ADM) model are used to evaluate the results. This study confirms that Lake Naivasha has been steadily declining with the situation being exacerbated from around the year 2000, with water levels falling at a rate of 10.2 cm/year and a shrinkage in area of 1.04 km(2)/year. GRACE indicates that the catchment area of 4 degrees x 4 degrees that includes Lake Naivasha loses water at a rate of 1.6 cm/year for the period from August 2002 to May 2006, and 1.4 cm/year for the longer period of May 2002 to 2010. Examining the ADM outputs also supports our results of GRACE. Between the time periods 2000-2006 and 2006-2010, the lake surface area decreased by 14.43% and 10.85%, respectively, with a corresponding drop in the water level of 192 cm and 138 cm, respectively, over the same periods. Our results show a correlation coefficient value of 0.68 between the quantity of flower production and the lake's level for the period 2002-2010 at 95% confidence level, indicating the probable impact of anthropogenic activities on the lake's level drop. (C) 2013 Elsevier Ltd. All rights reserved.

Global Navigation Satellite Systems (GNSS) are emerging as possible tools for remote sensing high-resolution atmospheric water vapour that improves weather forecasting through numerical weather prediction models. Nowadays, the GNSS-derived tropospheric zenith total delay (ZTD), comprising zenith dry delay (ZDD) and zenith wet delay (ZWD), is achievable with sub-centimetre accuracy. However, if no representative near-site meteorological information is available, the quality of the ZDD derived from tropospheric models is degraded, leading to inaccurate estimation of the water vapour component ZWD as difference between ZTD and ZDD. On the basis of freely accessible regional surface meteorological data, this paper proposes a height-dependent linear correction model for a priori ZDD. By applying the ordinary least-squares estimation (OLSE), bootstrapping (BOOT), and leave-one-out cross-validation (CROS) methods, the model parameters are estimated and analysed with respect to outlier detection. The model validation is carried out using GNSS stations with near-site meteorological measurements. The results verify the efficiency of the proposed ZDD correction model, showing a significant reduction in the mean bias from several centimetres to about 5mm. The OLSE method enables a fast computation, while the CROS procedure allows for outlier detection. All the three methods produce consistent results after outlier elimination, which improves the regression quality by about 20% and the model accuracy by up to 30%.

The Gravity Recovery and Climate Experiment (GRACE) products allow the quantification of total water storage (TWS) changes at global to regional scales. However, the quantity measured by GRACE represents mass signals integrated over vertical columns, requiring their separation into their original sources. Such a separation is vital for Australia, for which GRACE estimates are affected by leakage from the surrounding oceans. The independent component analysis (ICA) method that uses higher-order statistics, is implemented here to separate GRACE-derived water storage signals over the Australian continent from its surrounding oceans, covering from October 2002 to May 2011. The performance of ICA applied to GRACE is then compared to the ICA of WaterGAP Global Hydrology Model (WGHM) and the ICA of the Australian Water Resources Assessment (AWRA) system. To study the influence of rainfall variability on the derived independent patterns, use is made of Tropical Rainfall Measuring Mission (TRMM) data set, from January 2000 to May 2011. Implementing ICA on GRACE-TWS showed a remarkable improvement in separating the continental hydrological signals from the surrounding oceanic anomalies, which was not achievable using a conventional principle component analysis. Reconstructing the continental TWS changes using only those independent components of GRACE that were located over the continent showed a high correlation with WGHM-TWS and AWRA-TWS. Mass concentrations over the oceans and particularly S2 semi-diurnal aliased pattern were separated as independent modes. Correlation analysis between the independent components of GRACE and climate teleconnections showed that the mass anomalies over the northern ocean, Gulf of Carpentaria and north-eastern parts of Australia were significantly correlated with the El Niño-Southern Oscillation, while those over south and south-eastern parts of Australia were mainly linked to the Indian Ocean Dipole.

The classical least-squares (LS) algorithm is widely applied in processing data from Global Navigation Satellite Systems (GNSS). However, some limiting factors impacting the accuracy measures of unknown parameters such as temporal correlations of observational data are neglected in most GNSS processing software products. In order to study the temporal correlation characteristics of GNSS observations, this paper introduces autoregressive (integrated) moving average (AR(I)MA) processes to analyse residual time series resulting from the LS evaluation. Based on a representative data base the influences of various factors, like baseline length, multipath effects, observation weighting, atmospheric conditions on ARIMA identification are investigated. Additionally, different temporal correlation models, for example first-order AR processes, ARMA processes, and empirically determined analytical autocorrelation functions are compared with respect to model appropriateness and efficiency.

In terrestrial and airborne gravity field determination the formulae for the gravitational potential and its first order derivatives have been used, while the second order derivatives are related to the analysis of upcoming satellite gravity gradiometry missions of GOCE type. Especially there, the reduction of topographic and isostatic effects is important to produce a smooth gravity field suitable for downward continuation. In this paper various isostatic models, namely the models of Airy–Heiskanen (A–H) and Pratt–Hayford (P–H), the combination of the Airy–Heiskanen model (land area) and the Pratt–Hayford model (ocean area), the first (H1) condensation model of Helmert as well as a crust density model are analyzed for a GOCE-like satellite orbit in two selected regions: Japan and central part of Europe. The different topographic–isostatic effects are compared with respect to the degree of smoothing of the measured satellite gradiometric data. The results of this paper can serve as a base for further investigations of the suitability of particular reduction models for downward continuation.

Hydrological monitoring is essential for meaningful water-management policies and actions, especially where water resources are scarce and/or dwindling, as is the case in Australia. In this paper, we investigate the regional 4°×4° mascon (mass concentration) GRACE solutions for Australia provided by GSFC (Goddard Space Flight Center, NASA) for their suitability in monitoring Australian hydrology, with a particular focus on the Murray-Darling Basin (MDB). Using principal component analysis (PCA) and multi-linear regression analysis (MLRA), the main components of spatial and temporal variability in the mascon solutions are analysed over the whole Australian continent and the MDB. The results are compared to those from global solutions provided by CSR (Center for Space Research, University of Texas at Austin, USA) and CNES/GRGS (Centre National d'Études Spatiales/Groupe de Recherche de Geodesie Spatiale, France) and validated using data from the Tropical Rainfall Measuring Mission (TRMM), water storage changes predicted by the WaterGap Global Hydrological Model (WGHM) and the Global Land Data Assimilation System (GLDAS), and ground-truth (river-gauge) observations. For the challenging Australian case with generally weak hydrological signals, the mascon solutions provide similar results to those from the global solutions, with the advantage of not requiring additional filtering (destriping and smoothing) as, for example, is necessary for the CSR solutions. A further advantage of the mascon solutions is that they offer a higher temporal resolution (i.e., 10days) compared to approximately monthly CSR solutions. Examining equivalent water volume (EWV) time series for the MDB shows a good cross-correlation (generally>0.7) among the GRACE solutions when considering the whole basin, although lower (generally<0.5) when all the GRACE solutions are compared to the TRMM, WGHM and GLDAS time series. Examining smaller portions of the MDB see the correlation among the GRACE solutions and the TRMM, WGHM and GLDAS EWV time series increase slightly (>0.6), with all time series appearing to visually follow the general behaviour of the river-gauge data, although the cross-correlations are relatively low (between 0.3 and 0.6).

The Procrustes method is a very effective method for determining the Helmert's datum transformation parameters since it requires neither initial starting values nor iteration. Due to these attractive attributes, the ABC-Procrustes algorithm is extended to solve the 3D affine transformation problem where scale factors are different in the 3 principal directions X, Y, Z. In this study, it is shown that such a direct extension is restricted to cases of mild anisotropy in scaling. For strong anisotropy, however, the procedure fails. The PZ-method is proposed as an extension of the ABC algorithm for this special case. The procedures are applied to determine transformation parameters for; (i) transforming the Australian Geodetic Datum (AGD 84) to the Geocentric Datum Australia (GDA 94), i. e., mild anisotropy and (ii) synthetic data for strong anisotropy. The results indicate that the PZ-algorithm leads to a local multivariate minimization as opposed to the ABC-algorithm, thus requiring slightly longer computational time. However, the ABC-method is found to be useful for computing proper initial values for the PZ-method, thereby increasing its efficiency.

Radio occultation (RO) techniques that use signals transmitted by Global Navigation Satellite Systems (GNSS) have emerged over the past decade as an important tool for measuring global changes in tropopause temperature and height, a valuable capacity given the tropopause’s sensitivity to temperature variations. This study uses 45,091 RO data from the CHAMP (CHAllenging Minisatellite Payload, 80 months), GRACE (Gravity Recovery And Climate Experiment, 23 months) and COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate, 20 months) satellites to analyse the variability of the tropopause’s height and temperature over Australia. GNSS RO temperature profiles from CHAMP, GRACE, and COSMIC are first validated using radiosonde observations provided by the Bureau of Meteorology (Australia). These are compared to RO soundings from between 2001 and 2007 that occurred within 3 h and 100 km of a radiosonde. The results indicate that RO soundings provide data of a comparable quality to radiosonde observations in the tropopause region, with temperature deviations of less than 0.5 ± 1.5 K. An analysis of tropopause height and temperature anomalies indicates a height increase over Australia as a whole of ca. 4.8 ± 1.3 m between September 2001 and April 2008, with a corresponding temperature decrease of −0.019 ± 0.007 K. A similar pattern of increasing height/decreasing temperature was generally observed when determining the spatial distribution of the tropopause height and temperature rate of change over Australia. Although only a short period has been considered in this study, a function of the operating time of these satellites, the results nonetheless show an increase in the height of the tropopause over Australia during this period and thus may indicate regional warming. Several mechanisms could be responsible for these changes, such as an increase in the concentration of greenhouse gases in the atmosphere, and lower stratospheric cooling due to ozone loss, both of which have been observed during the last decades.

PROBRAL - Precise positioning and height determination by means of GPS: Modeling of errors and transformation into physical heights is the name of a joint venture between the Department of Geomatics (DGEOM), Federal University of Parana (UFPR), Curitiba (Brazil) and the Geodetic Institute (GIK), University Karlsruhe (TH), Karlsruhe (Germany). The aim of this research project, which started in 2006 and is founded by the Brazilian academic exchange service CAPES and the German academic exchange service DAAD, is to validate and to improve the quality of GNSS-based positioning, especially concerning the height component.Therefore, the close cooperation between the DGEOM and the GIK was intensified. One main objective of the first year of this three years lasting cooperation was to establish a receiver antenna calibration field for GNSS instrumentations on the roof top of the so-called LAGE (http://www.lage.ufpr.br/).In the framework of PROBRAL case studies were carried out in close collaboration at the DGEOM as well as at the GIK concerning site-specific effects (e.g. multipath, receiver antenna modeling), especially.The status of the establishment of a GNSS receiver antenna calibration field, called First Baseline Calibration Station for GNSS Antennas in Brazil (1(a). BCALBR), is going to be presented within this paper.The very first results derived on 1(a). BCALBR showed that the pillar 1000 is affected by carrier phase multipath less than pillar 2000. The IBGE (Brazilian Institute of Geography and Statistics) reference station PARA is slightly affected by carrier phase multipath.

The coastal region of the State of Parana, located between the 25 degrees and 26 degrees S parallels and the 48 degrees and 49 degrees W meridians, is formed by the Serra do Mar mountain range, extensive coastal plains and estuary complexes. The objective of this paper is to present some surveys at the coast of Parana State (Brazil) that began in 1996 because of the lack of previous available data and the need of better control over the coast of Parana State and its conformations. Among the GPS surveys that have ever been accomplished within such area it should be mentioned the monitoring of the shoreline, in some parts in retreat or in progradation; such as on the island "Ilha do Mel" and in the Municipality of Matinhos (PR). GPS, DGPS, and PDGPS have been used at Such sites because there is a need of precision. With the aid of GPS along with multidisciplinary actions in this area, a systematic view of the environmental issue will be provided as well as better information for its environmental monitoring. In the municipality of Matinhos (PR), the monitoring of the shoreline has been done and erosion effects have been detected. The coastlines in the northwest and in the Southeast of the Isthmus of the "Ilha do Mel" are affected by retreat and they have shifted towards the continent. The next step is to integrated temporal datas, considered a difficult task. A new line in this project has the focus on the future modeling prediction.

In many GNSS software packages a simplified observation weighting model is used which is merely based on the satellite elevation angle and valid under the assumption of azimuthal symmetry. This elevation-dependent weighting model is only suitable for undisturbed GNSS signals based on the existing strong correlation between signal quality and satellite elevation angle. However, for high-precision geodetic applications this geometry-related weighting model becomes obsolete if observations are strongly affected by multipath effects, signal diffraction as well as receiver characteristic under non-ideal observation conditions. An improved observation weighting model based on signal-to noise power ratio measurements has been developed and experimentally implemented in the Bernese GPS software 5.0. Tests indicate that when this weighting model is used for low elevation data additional 10% ambiguities can be resolved and the accuracy of the estimated site-specific neutrosphere parameters can be. improved by nearly 25% compared with the standard elevation-dependent weighting model.