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.
Recent estimates of Antarctica's present-day rate of ice-mass contribution to changes in sea level range from 31 gigatonnes a year (Gt yr(-1); ref. 1) to 246 Gt yr(-1) (ref. 2), a range that cannot be reconciled within formal errors. Time-varying rates of mass loss contribute to this, but substantial technique-specific systematic errors also exist. In particular, estimates of secular ice-mass change derived from Gravity Recovery and Climate Experiment (GRACE) satellite data are dominated by significant uncertainty in the accuracy of models of mass change due to glacial isostatic adjustment (GIA). Here we adopt a new model of GIA, developed from geological constraints, which produces GIA rates systematically lower than those of previous models, and an improved fit to independent uplift data. After applying the model to 99 months (from August 2002 to December 2010) of GRACE data, we estimate a continent-wide ice-mass change of -69 ± 18 Gt yr(-1) (+0.19 ± 0.05 mm yr(-1) sea-level equivalent). This is about a third to a half of the most recently published GRACE estimates, which cover a similar time period but are based on older GIA models. Plausible GIA model uncertainties, and errors relating to removing longitudinal GRACE artefacts ('destriping'), confine our estimate to the range -126 Gt yr(-1) to -29 Gt yr(-1) (0.08-0.35 mm yr(-1) sea-level equivalent). We resolve 26 independent drainage basins and find that Antarctic mass loss, and its acceleration, is concentrated in basins along the Amundsen Sea coast. Outside this region, we find that West Antarctica is nearly in balance and that East Antarctica is gaining substantial mass.
Abstract:Satellite altimetry is routinely used to provide levels for oceans or large inland water bodies from space. By utilizing retracking schemes specially designed for inland waters, meaningful river stages can also be recovered when standard techniques fail. Utilizing retracked waveforms from ERS-2 and ENVISAT along the Mekong, comparisons against observed stage measurements show that the altimetric measurements have a root mean square error (RMSE) of 0Ð44-0Ð65 m for ENVISAT and 0Ð46-0Ð76 m for ERS-2. For many applications, however, stage is insufficient because discharge is the primary requirement. Investigations were therefore undertaken to estimate discharges at a downstream site (Nakhon Phanom (NP)) assuming that in situ data are available at a site 400 km upstream (Vientiane). Two hypothetical, but realistic scenarios were considered. Firstly, that NP was the site of a de-commissioned gauge and secondly, that the site has never been gauged. Using both scenarios, predictions were made for the daily discharge using methods with and without altimetric stage data. In the first scenario using a linear regression approach the altimetry data improved the Nash-Sutcliffe r 2 value from 0Ð884 to 0Ð935. The second scenario used known river cross-sections while lateral inflows were inferred from a hydrological model: this scenario gave an increase in the r 2 value from 0Ð823 to 0Ð893. The use of altimetric stage data is shown to improve estimated discharges and further applications are discussed.
Higher order ionospheric effects are increasingly relevant as precision requirements on GPS data and products increase. The refractive index of the ionosphere is affected by its electron content and the magnetic field of the Earth, so the carrier phase of the GPS L1 and L2 signals is advanced and the modulated code delayed. Due to system design the polarisation is unaffected. Most of the effect is removed by expanding the refractive index as a series and eliminating the first term with a linear combination of the two signals. However, the higher order terms remain. Furthermore, transiting gradients in refractive index at a non-perpendicular angle causes signal bending. In addition to the initial geometric bending term, another term allows for the difference that the curvature makes in electron content along each signal. Varying approximations have been made for practical implementation, mainly to avoid the need for a vertical profile of electron density. The magnetic field may be modelled as a tilted co-centric dipole, or using more realistic models such as the International Geomagnetic Reference Field. The largest effect is from the second term in the expansion of the refractive index. Up to several cm on L2, it particularly affects z-translation, and satellite orbits and clocks in a global network of GPS stations. The third term is at the level of the errors in modelling the second order term, while the bending terms appear to be absorbed by tropospheric parameters. Modelling improvements are possible, and three frequency transmissions will allow new possibilities.
ABSTRACT: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 selfcalibrating 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.
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