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Radar Corner Reflectors (CR) are increasingly used as reference targets for land surface deformation measurements with the Interferometric Synthetic Aperture Radar (InSAR) technique. When co-located with ground-based Global Navigation Satellite Systems (GNSS) infrastructure, InSAR observations at CR can be used to integrate relative measurements of surface deformation into absolute reference frames defined by GNSS. However, CR are also a potential source of GNSS multipath effects and may therefore have a detrimental effect on the GNSS observations. In this study, we compare daily GNSS coordinate time series and 30-second signal-to-noise ratio (SNR) observations for periods before and after CR deployment at a GNSS site. We find that neither the site coordinates nor the SNR values are significantly affected by the CR deployment, with average changes being within 0.1 mm for site coordinates and within 1 % for SNR values. Furthermore, we generate empirical site models by spatially stacking GNSS observation residuals to visualise and compare the spatial pattern in the surroundings of GNSS sites. The resulting stacking maps indicate oscillating patterns at elevation angles above 60 degrees which can be attributed to the CR deployed at the analysed sites. The effect depends on the GNSS antenna used at a site with the magnitude of multipath patterns being around three times smaller for a high-quality choke ring antenna compared to a ground plane antenna without choke rings. In general, the CR-induced multipath is small compared to multipath effects at other GNSS sites located in a different environment (e. g. mounted on a building). [ABSTRACT FROM AUTHOR]

• Developed 2D deformation model using multiband SAR with rates and errors. • Deformation model connect to terrestrial reference frame. • new method to estimate interpolation errors using Natural Neighbour interpolation. • error estimation method replicates the error behaviour from Ordinary Kriging. • Natural Neighbour interpolation is at least 100 times faster than Ordinary Kriging. A long term objective for Australia is to develop a continent-wide 2D deformation model based on satellite interferometric synthetic aperture radar (InSAR). Nation-wide InSAR processing has been demonstrated in European countries and Japan. However, there are some key differences to the Australian situation for a 2D model (i.e., vertical and east–west surface movement rates) where SAR data from ascending and descending satellite orbits are needed. The primary difference is that while ESA's Sentinel-1 ascending and descending satellite observations underpin 2D models in other parts of the world, the Australian continent is only covered by descending Sentinel-1 SAR data in most areas. Combined with Australia's large size of 7.63 million km2, this means a different approach is needed to realise 2D deformation models. In this article, we propose the novel approach of (1) combining supplementary multiband SAR (ascending X-band and L-band) with the descending C-band Sentinel-1 data, and (2) using natural neighbour (NN) interpolation as a computationally efficient interpolation method for combining the multiband InSAR data on common grids prior to 2D model computation. This is an alternative to the computationally intensive Ordinary Kriging (OK) approach. A disadvantage of NN compared to OK is that it does not compute an error estimate, which we address by deriving an error estimate for the NN interpolation so that errors are provided for each 2D rate to aid with their correct interpretation. To demonstrate our new approach, we compute experimental 2D deformation models that propagate the full error budget from InSAR, a GNSS connection to ITRF2014 and NN interpolation into an error grid in the Latrobe Valley in southeast Australia. The significance of our approach is that it provides a suitable combination of methods that may be used to develop 2D continental deformation models for Australia's unique circumstances. Our results demonstrate the accuracy of NN and OK interpolation are at the same level (within error), and the error estimates from both interpolation techniques are also comparable: X band (TerraSAR-X) ∼ 1 mm/yr; C band (Sentinel-1) ∼ 2.5 mm/yr, and L band (ALOS PALSAR1) 4 mm/yr. For the first time, we reveal 2D deformation in the Latrobe Valley region showing horizontal east–west deformation in the area surrounding an above-ground mine and reaching 20 mm/yr, with vertical subsidence rates reaching −40 mm/yr. [ABSTRACT FROM AUTHOR]

Interferometric synthetic aperture radar (InSAR) technology has been widely applied to measure Earth surface motions related to natural and anthropogenic crustal deformation phenomena. With the widespread uptake of data captured by the European Space Agency's Sentinel-1 mission and other recently launched or planned space-borne SAR missions, the usage of the InSAR technique to detect and monitor Earth surface displacements will increase even more in the coming years. However, InSAR can only measure a one-dimensional motion along the radar line of sight (LOS), which makes interpretation and communication of InSAR measurements challenging, and can add ambiguity to the modelling process. Within this paper, we investigate the implications of the InSAR LOS geometry using simulated and observed deformation phenomena and describe a methodology for multi-geometry data fusion of LOS InSAR measurements from many viewing geometries. We find that projecting LOS measurements to the vertical direction using the incidence angle of the satellite sensor (and implicitly assuming no horizontal motions are present) may result in large errors depending on the magnitude of horizontal motion and on the steepness of the incidence angle. We quantify these errors as the maximum expected error from simulated LOS observations based on a Mogi deformation model. However, we recommend to use LOS observations from several image geometries wherever data are available, in order to solve for vertical and E–W oriented horizontal motion. For an anthropogenic deformation phenomenon observed in seven independent InSAR analyses of Envisat SAR data from the Sydney region, Australia, we find that the strong horizontal motion present could lead to misinterpretation of the actual motion direction when projecting LOS measurements to vertical (uplift instead of subsidence). In this example, the difference between multi-geometry data fusion and vertical projection of LOS measurements (at an incidence angle of 33.8°) reach up to 67% of the maximum vertical displacement rate. Furthermore, the position of maximum vertical motion is displaced horizontally by several hundred metres when the LOS measurements are projected. [ABSTRACT FROM AUTHOR]

Earth observation (EO) satellites facilitate hazard monitoring and mapping over large-scale and remote areas. Despite Synthetic Aperture Radar (SAR) satellites being well-documented as a hazard monitoring tool, the uptake of these data is geographically variable, with the Australian continent being one example where the use of SAR data is limited. Consequently, less is known about how these data apply in the Australian context, how they could aid national hazard monitoring and assessment, and what new insights could be gleaned for the benefit of the international disaster risk reduction community. The European Space Agency Sentinel-1 satellite mission now provides the first spatially and temporally complete global SAR dataset and the first opportunity to use these data to systematically assess hazards in new locations. Using the example of Australia, where floods and uncontrolled bushfires, earthquakes, resource extraction (groundwater, mining, hydrocarbons) and geomorphological changes each pose potential risks to communities, we review past usage of EO for hazard monitoring and present a suite of new case studies that demonstrate the potential added benefits of SAR. The outcomes provide a baseline understanding of the potential role of SAR in national hazard monitoring and assessment in an Australian context. Future opportunities to improve national hazard identification will arise from: new SAR sensing capabilities, which for Australia includes a first-ever civilian EO capability, NovaSAR-1; the integration of Sentinel-1 SAR with other EO datasets; and the provision of standardised SAR products via Analysis Ready Data and Open Data Cubes to support operational applications. [ABSTRACT FROM AUTHOR]

Extracting groundwater for agricultural, aquacultural, and industrial use in central Taiwan has caused large-scale land subsidence that poses a threat to the operation of the Taiwan High Speed Railway near Yunlin County. We detected Yunlin subsidence using the Sentinel-1A Synthetic Aperture Radar (SAR) by the Small BAseline Subset (SBAS) method from April 2016 to April 2017. We calibrated the initial InSAR-derived displacement rates using GPS measurements and reduced the velocity difference between the two sensors from 15.0 to 8.5 mm/a. In Yunlin's severe subsidence regions, cumulative displacements from InSAR and GPS showed that the dry-season subsidence contributed 60%–74% of the annual subsidence. The InSAR-derived vertical velocities matched the velocities from leveling to better than 10 mm/a. In regions with few leveling measurements, InSAR increased the spatial resolution of the vertical velocity field and identified two previously unknown subsidence spots over an industrial zone and steel factory. Annual significant subsidence areas (subsidence rate > 30 mm/a) from leveling from 2011 to 2017 increased with the declining dry-season rainfalls, suggesting that the dry-season rainfall was the deciding factor for land subsidence. A severe drought in 2015 (an El Niño year) dramatically increased the significant subsidence area to 659 km2. Both InSAR and leveling detected similarly significant subsidence areas in 2017, showing that InSAR was an effective technique for assessing whether a subsidence mitigation measure worked. The newly opened Hushan Reservoir can supply surface water during dry seasons and droughts to counter rain shortage and can thereby potentially reduce land subsidence caused by groundwater extraction. [ABSTRACT FROM AUTHOR]