Mapping Land Surface Displacements in the Swiss Alps with Radar Interferometry

Abstract. Satellite measurements of coseismic displacements are typically based on Synthetic Aperture Radar (SAR) interferometry or amplitude tracking, or based on optical data such as from Landsat, Sentinel-2, SPOT, ASTER, very-high resolution satellites, or airphotos. Here, we evaluate a new class of optical satellite images for this purpose – data from cubesats. More specific, we investigate the PlanetScope cubesat constellation for horizontal surface displacements by the 14 November 2016 Mw7.8 Kaikoura, New Zealand, earthquake. Single PlanetScope scenes are 2–4 m resolution visible and near-infrared frame images of approximately 20–30 km × 9–15 km in size, acquired in continuous sequence along an orbit of approximately 375–475 km height. From single scenes or mosaics from before and after the earthquake we observe surface displacements of up to almost 10 m and estimate a matching accuracy from PlanetScope data of up to ±0.2 pixels (~ ±0.6 m). This accuracy, the daily revisit anticipated for the PlanetScope constellation for the entire land surface of Earth, and a number of other features, together offer new possibilities for investigating coseismic and other Earth surface displacements and managing related hazards and disasters, and complement existing SAR and optical methods. For comparison and for a better regional overview we also match the coseismic displacements by the 2016 Kaikoura earthquake using Landsat8 and Sentinel-2 data.

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Land Surface Displacement Study for Kryvyi Rih Mining Area using Radar Interferometry Time Series Analysis

10.3997/2214-4609.201903199 ◽

2019 ◽

Author(s):

S. Stankevich ◽

I. Piestova ◽

O. Titarenko ◽

V. Filipobich ◽

T. Dudar ◽

...

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Land Surface ◽

Surface Displacement ◽

Mining Area ◽

Radar Interferometry ◽

Series Analysis

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Geometry of surface deformations caused by induced shocks in the area of underground copper exploitation

10.5194/egusphere-egu2020-11185 ◽

2020 ◽

Author(s):

Karolina Owczarz ◽

Anna Kopeć ◽

Dariusz Głąbicki

Keyword(s):

Surface Deformation ◽

Underground Mining ◽

Surface Displacement ◽

3D Models ◽

Radar Interferometry ◽

Time Interval ◽

Mining Operations ◽

Copper Ore ◽

Surface Displacements ◽

Satellite Radar

The level of intensity of induced seismic phenomena occurring in areas of mining activity is very diverse. Induced shocks may be directly related to the exploitation carried out or to mining and tectonic factors. In the case of impact on the surface, two types of mining tremors are distinguished: energetically weak shocks, not causing surface deformation, and shocks exceeding a certain energy level, which cause terrain deformations. Surface displacements are the most common form of the effects of underground mining operations, including induced seismicity. Geological research uses Sentinel-1 imagery to determine the geometry of surface displacements that were caused by induced shocks by satellite radar interferometry. In this research four induced shocks with magnitude M>4.0 was used, which occurred in the Legnica-Glogow Copper District in the Rudna mine. This area is one of the most seismically active places in Poland due to the underground exploitation of copper ore. For calculations, the differential satellite radar interferometry (DInSAR) method was used. The DInSAR technique allowed the determination of surface displacement towards the Line of Sight (LOS) between two images acquired at different times (before and after induced shock) with millimeter accuracy. In the presented research calculations were carried out separately for observations acquired in descending and ascending orbits. The Sentinel-1 satellites are a constellation of two radar satellites that observe the surface of lands and oceans at a time interval of 6 days. Therefore, 6 days, 12 days, 18 days and 24 days were assumed as the time intervals between the images. Vertical displacements were calculated based on the generated LOS displacement maps. In addition, charts of subsidence in the N-S and W-E directions were prepared, 3D models of subsidence were made, and deformation geometry was analyzed for individual shocks. As a result of the research, the spatial extent of deformation in the horizontal surface was determined: N-S and W-E, which in both directions was over 2 km. However, surface displacements caused by induced shocks reached values up to 10 cm.

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Detection and measurement of landslide deformation prior to their failure by satellite radar interferometry.

10.5194/egusphere-egu2020-7617 ◽

2020 ◽

Author(s):

Alessandro Simoni ◽

Benedikt Bayer ◽

Pierpaolo Ciuffi ◽

Silvia Franceschini ◽

Matteo Berti

Keyword(s):

Surface Displacement ◽

Radar Interferometry ◽

Rock Outcrops ◽

Bare Rock ◽

Rainfall Events ◽

Surface Displacements ◽

Catastrophic Failures ◽

Before And After ◽

Slow Moving ◽

Satellite Radar

Landslides are widespread landscape features in the Northern Apennine mountain chain and their activity frequently cause damages to settlements and infrastructures. In such context, slow-moving landslides are very common and typically affect fine-grained weathered rocks. Long periods of sustained slow-movements (cms/year) can be interrupted by rapid acceleration and catastrophic failures (ms/day) that are caused by intense rainfall events. Space-borne synthetic aperture radar interferometry (InSAR) proved effective to detect actively deforming phenomena and monitor their evolution in the periods before and after failures. We present InSAR results derived from the Sentinel 1 satellite constellation for landslide cases that underwent reactivation during 2019. In all cases, the catastrophic failures were unexpected and no ground-based monitoring data are available. We processed pre- and post-failure interferograms of SAR images acquired by Sentinel 1 A/B with time spans ranging from 6 to 24 days, removing those having low coherence by manual inspection. The conventional 2-pass technique allowed us to obtain measurements of surface displacement despite the fact that sparse to none infrastructures nor bare rock outcrops are present on the landslide bodies. Our interferograms show that surface displacements are visible well in advance of the actual failure. They display nearly continuous downslope motion with seasonal velocity changes. Time series between 2015 and 2019 shows that surface displacements can be appreciated throughout most part of the year with snow cover and summer peak of vegetation being the most notable exceptions. Distinct accelerations can be detected in space and time during the weeks and months preceding the reactivation.We compare time-dependent deformations to precipitation patterns to explore their relationship and to document the transition from stable to unstable deformation. Our work suggests that InSAR interferometry can be successfully used to measure pre-failure displacements and detect slow-moving landslides that are more prone to reactivation in case of rainfall events.

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TopoSCALE: deriving surface fluxes from gridded climate data

Geoscientific Model Development Discussions ◽

10.5194/gmdd-6-3381-2013 ◽

2013 ◽

Vol 6 (2) ◽

pp. 3381-3426 ◽

Cited By ~ 1

Author(s):

J. Fiddes ◽

S. Gruber

Keyword(s):

High Resolution ◽

Land Surface ◽

Climate Models ◽

Good Description ◽

Longwave Radiation ◽

Surface Fluxes ◽

Swiss Alps ◽

Climate Data ◽

Heterogeneous Terrain ◽

Reference Methods

Abstract. Simulation of land surface processes is problematic in heterogeneous terrain due to the the high resolution required of model grids to capture strong lateral variability caused by e.g. topography and the lack of accurate meteorological forcing data at the site or scale it is required. Gridded data products produced by atmospheric models can fill this gap, however, often not at an appropriate spatial resolution to drive land-surface simulations. In this study we describe a method that leverages the good description of the atmospheric column provided by climate models, together with high resolution DEM's, to derive a consistent topography-based, scaling of coarse grid climate variables to fine-scale. We test the method together with unscaled grid-level data and a set of reference methods, against a large evaluation dataset (up to 210 stations per variable) in the Swiss Alps. We demonstrate that the method can be used to derive meteorological inputs in complex terrain, with most significant improvements (with respect to reference methods) seen in variables derived from pressure-levels: air temperature, relative humidity, wind speed and incoming longwave radiation. It is expected that this method can be used to improve inputs to numerical simulations in complex and/or remote terrain especially when statistical methods are not possible due to lack of observations i.e. remote areas or future periods.

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Estimate of a spatially variable reservoir compressibility by assimilation of ground surface displacement data

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-372-351-2015 ◽

2015 ◽

Vol 372 ◽

pp. 351-356 ◽

Cited By ~ 2

Author(s):

C. Zoccarato ◽

D. Baù ◽

F. Bottazzi ◽

M. Ferronato ◽

G. Gambolati ◽

...

Keyword(s):

Land Surface ◽

Ground Surface ◽

Surface Displacement ◽

Test Case ◽

Geomechanical Model ◽

Gas Field ◽

Surface Displacements ◽

Model Response ◽

Synthetic Test ◽

Gas Fields

Abstract. Fluid extraction from producing hydrocarbon reservoirs can cause anthropogenic land subsidence. In this work, a 3-D finite-element (FE) geomechanical model is used to predict the land surface displacements above a gas field where displacement observations are available. An ensemble-based data assimilation (DA) algorithm is implemented that incorporates these observations into the response of the FE geomechanical model, thus reducing the uncertainty on the geomechanical parameters of the sedimentary basin embedding the reservoir. The calibration focuses on the uniaxial vertical compressibility cM, which is often the geomechanical parameter to which the model response is most sensitive. The partition of the reservoir into blocks delimited by faults motivates the assumption of a heterogeneous spatial distribution of cM within the reservoir. A preliminary synthetic test case is here used to evaluate the effectiveness of the DA algorithm in reducing the parameter uncertainty associated with a heterogeneous cM distribution. A significant improvement in matching the observed data is obtained with respect to the case in which a homogeneous cM is hypothesized. These preliminary results are quite encouraging and call for the application of the procedure to real gas fields.

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