Cryosat-2 SARin altimetric FBR data facilitates an opportunity to investigate phase differences between inland water radar reflections at the two antennae. With the antennae positioned cross-track, SARin was designed for the recovery of slope over ice margins, but here, it was used to recover off-pointing over inland waters. The ability to measure non-nadir off-pointing is verified using ocean data near the Amazon estuary to determine the satellite roll angle. Over inland waters, off-pointing requires correction to the nadir range and the geographic location of the reflectance. By using an SRTM-based water mask, the number of inland water reflectance increases significantly when off-pointing is considered. Comparisons between altimetric and river heights utilise gauge data at Tabatinga on the Solimões–Amazon. A least-squares adjustment yielded a river slope of −0.03506 ± 0.00003 m/km and a mean velocity of 1.803 ± 0.014 m/s over a river stretch of nearly 290 km. RMSE differences between the gauge and altimetry improve from 0.423 m to 0.404 m when off-pointing is taken into account for nadir inland water returns, showing the asymmetric effect of off-pointing. If all potential off-pointings are considered, the number of measurements increases by 66%, but the RMSE of 0.524 m is higher due to additional errors in the off-pointing corrections.

A change detection and thresholding methodology has been adapted from previous studies to determine the extent of flooding for 13 Sentinel‐1 synthetic aperture radar images captured during the floods of winter 2015–2016 in Yorkshire, UK. Both available polarisations, VH and VV, have been processed to allow for a comparison of their respective accuracy for delineating surface water. Peak flood extents are found on 29 December 2015 during the aftermath of storms Eva and Frank. Results have been validated against a Sentinel‐2 optical image, with both polarisations producing a total accuracy of 97%. Of the two polarisations, VV produces fewer misclassifications, mirroring the similar results reported in previous research. Mapped results are compared to the Environment Agency Flood Maps for Planning (EA FMP), with good correlation observed for inundation on the floodplains. Differences occur away from the floodplains, with the satellite data identifying pluvial flooding not highlighted by the EA FMP.

This study uniquely processes Cryosat-2 Full Bit Rate (FBR) SAR Level 1A data to recover inland water heights. The processing methodology involves an azimuthal Fast Fourier Transform (FFT) for the burst echo data followed by beam formation directed towards equi-angular ground points, stacking, slant range correction, multi-looking and finally retracking. It is seen that speckle in the burst echo data affects the recovered heights with precise heights recovered only through stacking and forming multi-look waveforms. Also investigated is the effect of different numbers of multi-looks in the stack to form the final waveform for retracking. A number of empirical retrackers are utilized over inland waters and compared against the oceanic SAMOSA2 and the OCOG/Threshold retrackers. Use of the SAMOSA2 retracker is shown to be inappropriate for inland waters. The use of 81 multi-looks from the stack centred on the nadir direction is shown to be preferred across Tonle Sap with the RMS of height residuals in the range 4-6 cm. External validation across Tonle Sap using gauge data shows that CryoSat-2 heights (RMS 42.1 cm) are comparable to OSTM (RMS 42.6 em) despite the CryoSat-2 non-repeating orbit which precludes the use of a mean profile. Validation against gauge data at Kratie on the Mekong gives an RMS of 59.9 cm for Cryosat-2 against an RMS of 35.5 cm and 52.2 cm derived from Envisat. The CryoSat-2 results utilize an approximate correction for river slope as the river crossings span 5 km upstream to 80 km downstream of the gauge while the repeat pass crossings of Envisat are at 7 km and 43 km from the gauge. Validation of Amazon altimetric Surface Water Elevation (SWE) showed RMS agreement of 27.3 cm with Obidos gauge data and 56.3 cm at Manacapuru 650 km upstream of Obidos. Overall validations showed that CryoSat-2 altimetric river heights are more accurate than those from TOPEX/Poseidon, OSTM and Envisat for relatively large water bodies but less accurate than the Ka band SARAL (Satellite with ARgos and ALtiKa). (C) 2017 Published by Elsevier Ltd on behalf of COSPAR.

Landslides are hazardous events with often disastrous consequences. Monitoring landslides with observations of high spatio-temporal resolution can help mitigate such hazards. Mini unmanned aerial vehicles (UAVs) complemented by structure-from-motion (SfM) photogrammetry and modern per-pixel image matching algorithms can deliver a time-series of landslide elevation models in an automated and inexpensive way. This research investigates the potential of a mini UAV, equipped with a Panasonic Lumix DMC-LX5 compact camera, to provide surface deformations at acceptable levels of accuracy for landslide assessment. The study adopts a self-calibrating bundle adjustment-SfM pipeline using ground control points (GCPs). It evaluates misalignment biases and unresolved systematic errors that are transferred through the SfM process into the derived elevation models. To cross-validate the research outputs, results are compared to benchmark observations obtained by standard surveying techniques. The data is collected with 6 cm ground sample distance (GSD) and is shown to achieve planimetric and vertical accuracy of a few centimetres at independent check points (ICPs). The co-registration error of the generated elevation models is also examined in areas of stable terrain. Through this error assessment, the study estimates that the vertical sensitivity to real terrain change of the tested landslide is equal to 9 cm.

Terrestrial water storage (TWS) change for 2003–2011 is estimated over Africa from GRACE gravimetric data. The signatures from change in water of the major lakes are removed by utilizing kernel functions with lake heights recovered from retracked ENVISAT satellite altimetry. In addition, the contribution of gravimetric change due to soil moisture and biomass is removed from the total GRACE signal by utilizing the GLDAS land surface model. The residual TWS time series, namely groundwater and the surface waters in rivers, wetlands, and small lakes, are investigated for trends and the seasonal cycle using linear regression. Typically, such analyses assume that the data are temporally uncorrelated but this has been shown to lead to erroneous inferences in related studies concerning the linear rate and acceleration. In this study, we utilize autocorrelation and investigate the appropriate stochastic model. The results show the proper distribution of TWS change and identify the spatial distribution of significant rates and accelerations. The effect of surface water in the major lakes is shown to contribute significantly to the trend and seasonal variation in TWS in the lake basin. Lake Volta, a managed reservoir in Ghana, is seen to have a contribution to the linear trend that is a factor of three greater than that of Lake Victoria despite having a surface area one‐eighth of that of Lake Victoria. Analysis also shows the confidence levels of the deterministic trend and acceleration identifying areas where the signatures are most likely due to a physical deterministic cause and not simply stochastic variations.

Precise point positioning (PPP) is a GNSS processing technique that utilizes undifferenced observations to calculate a position to centimeter accuracy. Much work has been carried out investigating the impact of time correlation on double difference observations in relative processing techniques, whereas its effect in PPP is not well known. This paper investigates the level of time correlation that is exhibited in the post-fit residuals from PPP processing and shows that this can be modelled as an autoregressive process. This can potentially impact quality control and fault detection as well as making formal errors appear optimistic.

In geopotential space, the fundamental geodetic parameter W 0 defines the Gauss–Listing geoid which can be used to best represent the Earth’s mean sea level (MSL) and hence specifies a conventional zero height level to unify vertical datums employed by mapping agencies throughout the world. Further, W 0 cannot be considered invariant as the parameter varies temporally as a direct response to sea level change and mass redistributions. This study determines W 0 and its rate, d W 0 /d t , by utilizing altimetric MSL models and an independent mean dynamic topography (MDT) model to define points on the geoid. W 0 and d W 0 /d t are estimated by two approaches: (i) by means of a global gravity field model (GGM) and (ii) within normal gravity field space as the geopotential value of the best fitting reference ellipsoid. The study shows that uncertainty in W 0 is mainly influenced by MDT while the choice of methodology, GGM and MSL data coverage are not significant within reason. Our estimate W 0 = 62636854.2 ± 0.2 m 2 s −2 at epoch 2005.0 differs by 1.8 m 2 s −2 from the International Astronomical Union reference value. This study shows that, at a sub-decadal time scale, the time variation d W 0 /d t stems mainly from sea level change with negligible effect from gravity field variations. d W 0 /d t = (−2.70 ± 0.03) × 10 −2 m 2 s −2 year −1 , corresponding to a MSL rise of 2.9 mm year −1 , is evaluated from sea level change based on 16 years of TOPEX and Jason-1 data.

The new global Earth gravitational model EGM2008 has been evaluated within geopotential space by comparison with its predecessor EGM96 and the GRACE combination model EIGEN-GL04C. The methodology comprises establishing geodetic coordinates of mean sea level (MSL) from GPS observations, tide gauge (TG) time series and levelling. The gravity potential at MSL was estimated at each TG location by utilising the ellipsoidal harmonic coefficients of the adopted gravity field models to their maximum degree and order. This study uses data from 23 TGs around the Baltic Sea, nine in the UK and one in France. Comparison involves testing the agreement between geopotential values for each country as gravity potentials at MSL are supposed to be consistent for regions where mean dynamic topography (MDT) does not differ significantly. Results show significant improvement with the EGM2008 model compared against its counterparts. The study shows the effect of omission errors on the solution by limiting the EGM2008 model to maximum degree and order 360 in the regional study. In addition to the regional study, EGM2008 was also evaluated globally using MSL derived from altimetric data. The global study shows that W 0 , the potential value on the geoid, is not affected by high degree terms of the EGM2008.

Changes in J2, resulting from past and present changes in Earth's climate, are traditionally observed by Satellite Laser ranging (SLR). Assuming an elastic Earth, it is possible to infer changes in J2 from changes in Earth's shape observed by GPS. We compare estimates of non‐secular J2 changes from GPS, SLR, GRACE, and a load model. The GPS and SLR annual signals agree but are different (16%) to the load model. Subtraction of the load model removes the annual variation from GPS, SLR, and GRACE, and the semi‐annual variation in GPS. The GPS and SLR long‐term signals are highly correlated, but GPS is better correlated with the loading model. Subtraction of the load model removes the 1998 anomaly from the GPS J2 series but not completely from the SLR J2 series, suggesting that the SLR anomaly may not be entirely due to mass re‐distribution as has been presumed.

A collection of slides from the author's seminar presentation is given.

The Auto-BAHN software under development at Newcastle University aims to incorporate a near real-time capability for GPS orbits and clocks into the GPS software BAHN, currently in operational use for IGS related activities at ESOC/ESA. As a first step the deterministic least-squares batch processor in BAHN has been replaced by an Extended Kalman Filter facilitating continuous computation of GPS satellite orbits and clocks and other receiver and satellite parameters. In this paper the underlying methodology behind the Extended Kalman Filter approach is introduced as required to handle GPS phase and code data from a global network of GPS tracking stations. In addition, details are presented about the replacement of global, arc-dependent and epoch-dependent deterministic parameters by stochastic processes. Current accuracies for the GPS orbits and clocks achieved with Auto-BAHN are illustrated through comparisons with IGS final solutions.

A numerical study has been conducted in order to estimate how a gravity field model obtained from GOCE data can be improved in the range of low degrees by addition of GRACE data. The GRACE data are simulated as inter-satellite accelerations. Different types of noise in the inter-satellite accelerations are considered, including white noise. The gravity field model is represented as a series of spherical harmonics; the Stokes coefficients are computed by a least-squares adjustment. It is shown that the incorporation of GRACE data may improve a GOCE-based gravity field model up to degree 120 or even higher depending on the type of noise in the inter-satellite accelerations. Moreover, the joint model at lower degrees may show a significantly higher quality that either a stand-alone GOCE-based or a stand-alone GRACE-based model. It is important, however, that proper covariance matrices of the involved data sets are used in the joint data processing.

In association with precise modelling of the Earth's gravity field, analytical integration can be used as an alternative to numerical integration, particularly for the intermediate neighbourhood of the computation point. Accordingly, closed analytical formulae for the gravitational potential and attraction are derived after expressing Newton's integral in terms of polar spherical coordinates. As the elemental volume for the integration element is defined by finite changes of the polar spherical coordinates, the actual mass density distribution is discretized so that each integration element is represented by a constant value of density.

The explicit formula for the geoid-to-quasigeoid correction is derived in this paper. On comparing the geoidal height and height anomaly, this correction is found to be a function of the mean value of gravity disturbance along the plumbline within the topography. To evaluate the mean gravity disturbance, the gravity field of the Earth is decomposed into components generated by masses within the geoid, topography and atmosphere. Newton’s integration is then used for the computation of topography-and atmosphere-generated components of the mean gravity, while the combined solution for the downward continuation of gravity anomalies and Stokes’ boundary-value problem is utilized in computing the component of mean gravity disturbance generated by mass irregularities within the geoid. On application of this explicit formulism a theoretical accuracy of a few millimetres can be achieved in evaluation of the geoid-to-quasigeoid correction. However, the real accuracy could be lower due to deficiencies within the numerical methods and to errors within the input data (digital terrain and density models and gravity observations).