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Summary of Proposal LAN0666

TitleAssessment of Landslide Dynamics and Spatio Temporal Evolution by X-Band Offset Tracking and InSAR (ALanDyn-X)
Investigator de Michele, Marcello - French Geological Survey (BRGM), Natural Risks Division
Team Member
PhD Raucoules, Daniel - French Geological Survey (BRGM), Natural Risks Division
PhD Grandjean, Gilles - French Geological Survey (BRGM), Natural Risks Division
Summaryhe aim of the project is to assess the potential of TS-X High Resolution SAR imagery to detect and monitor surface displacements related to landslides dynamics. Given that the expected deformation on the selected test sites ranges approximately from dm/year to m/year, we propose to use both Sub Pixel Correlation of SAR amplitude images, yielding horizontal and LOS displacement precision of about 1/10 of the pixel size, along with conventional and PSI InSAR. By using large temporal data series (more than 20-30 acquisitions per site) along with different acquisition geometry, we expect to produce time series of surface displacement in X, Y and Z components over a annual period. The objective of the project is to study landslide dynamics. An effort would be done to try to put in evidence any seasonal variations in the displacement field. Data will be processed with the GAMMA software along with specific algorithm development in IDL or C++, if required. We will focus on two test sites: 1 La Valette (Barcelonnette, Fr). This site is well instrumented and will provide a basis for validation. 2 Landslides on Cirque de Salazie, la Réunion Island (Fr). This area (~100km²) is affected by several landslides. We have a particular interest for Hellbourg and Grand Ilet landslide that are a threat for population. Required data: 20-30 Terrasar-X images planned for 2010-2011 for each site (i.e. 60 images) Data processing and interpretation would be carried out on the 2010-2012 period. We expect to provide a report about the results as well as a scientific publication if relevant to the results. This proposal is associated to the SAFELAND (7th Framework Programme of the European Commission) and MVTERRE2 (FEDER) projects funded by the European Commission.
Final ReportThis is from the published paper : • We propose to use image correlation techniques on High Resolution (HR) SAR images for characterizing landslide displacement rates. • The proposed methodology is applied to the La Valette landslide (South French Alps) using HR amplitude data provided by the TerraSAR-X sensor. • The multitemporal analysis allows identifying morphological units characterized by different displacement patterns (amplitude and direction of movement, spatial and temporal evolution). • The displacement pattern identified from the spaceborne sensor is consistent with local ground-based GNSS observations. ____ Slope movements such as landslides are one of the most significant geo-hazards in terms of socio-economic costs. Displacement monitoring of unstable slopes is thus crucial for the prevention and the forecast. In areas where large landslides cannot be stabilized and may accelerate suddenly, remote monitoring is often the only solution for surveying and early-warning. The choice of an adequate monitoring system depends on several constraints such as the landslide type, the areal extension, the range of observed velocity, the frequency of data acquisition, the desired accuracy and by the cost of data acquisition and processing. Techniques based on High Resolution (HR) Space-Borne SAR could provide valuable information in terms of landslide monitoring. In this framework, the availability of HR SAR such as the German Space Agency (DLR) Terrasar-X (TSX) data with frequent repeat cycle (11 days) represents an opportunity for constructing frequent landslide displacement maps in the perspective of an operational use. The sub-pixel correlation technique is based on the measurement of sub-pixel offsets between SAR images acquired at different dates. The method is based on a local correlation analysis that can be performed in the Fourier domain (as is presented in the current study) or in the spatial domain (e.g. Delacourt et al., 2004). Once the SAR data are perfectly co-registered, lines and columns (e.g. azimuth and range directions) offsets between two SAR data are converted in surface displacement estimates (e.g. Michel & Avouac, 2002; de Michele et al., 2010). Typically, the precision of the technique can reach about 1/10 of a pixel or even more (e. g. Leprince et al., 2007) depending both on the characteristics of the data (acquisition geometry, changes that occurred between the acquisitions, instrumental noise) and the amplitude of ground displacement (e.g. notably its spatial wavelength with respect to the size of the correlation window). This technique has been successfully applied to optical and radar data for studying deformation patterns originated from earthquakes (e.g. Michel and Avouac, 2002; de Michele et al., 2010), glacier kinematics (e.g. Scambos et al., 1992; Wangensteen et al., 2006) and landslides (Delacourt et al., 2009; Travelletti et al., 2012a). However, in regions characterized by the presence of persistent cloud cover, passive sensor data have important limitations preventing the creation of reliable archives of images for long-term monitoring. Data from active sensors such as HR SAR amplitude can be an alternative to optical imagery. The primary interests of using such data are threefold. First, the SAR amplitude is little or even not affected by the cloud cover or the atmospheric disturbances compared to SAR interferometry (InSAR). Second, the backscatter amplitude is less affected by multi-temporal vegetation changes than the phase of the signal commonly used in InSAR. Third, SAR amplitude is not affected by signal saturation in the presence of high displacement gradient. Ionospheric disturbances could, in specific cases (e.g. Quegan & Lamont, 1986), produce anomalous signatures on the azimuth offset estimations due to azimuth misregistration errors of the processed images. As the ionosphere is a dispersive medium for microwaves, such an effect mainly concerns the radar data obtained by sensors based on longer wavelength (e.g. L-band sensors). It is thus assumed that results derived from X-band data are little disturbed by the ionosphere except for the geographic locations that are affected by very high Total Electron Content (such as the polar regions; Mattar & Gray, 2002). It has been shown that a posteriori comparison of several azimuth offset maps allows detecting and rejecting offset results affected by ionospheric disturbances (e.g. Raucoules & de Michele, 2010). A further advantage of using SAR imagery is the high attitude control of the platform, which provides very similar geometrical conditions for image acquisitions (e.g perpendicular baselines generally shorter than few hundreds of metres). In such conditions, where the Base to Height ratio (B/H) ~ 10-3, the topographic contribution to the range offsets is rather moderate (for 1m pixel size, a 100 m height variation would correspond to about 0.1 pixel). By selecting smaller baselines, the topographic component can even be decreased (in the presence of steep relief, for instance) and in most cases there is no need to correct the topographic component. With this basis, the ability of TSX (as well as other HR SAR sensors) of providing amplitude images with resolution equivalent to optical remote sensing data (~1m) is of major interest. Given the high spatial resolution of the TSX data, displacements fields in the azimuth and range directions can be measured with an expected precision of about 0.1 m at different acquisition dates. The objectives of this work are threefold. First, we intend to evaluate the capability of the SAR amplitude offset technique to obtain landslide displacement maps with TSX data. Second, we explore the possibility of combining offsets maps into time series using least-square approaches (Usai, 2003; Le Mouelic et al., 2005; Casu et al., 2011). Third, we intend to combine ascending and descending modes to retrieve the multi-temporal 3D surface displacement fields,. The study could be of particular interest for detecting changes in surface displacement rates (e.g. acceleration and deceleration) at high spatial resolution. This could help for the forecast of large movements. To reach the aforementioned goals, we have decided to plan the acquisitions of TSX Spotlight data (1m resolution) at La Valette landslide (South French Alps) during one year, from April 2010 to March 2011. This landslide is characterized by displacement rates of about a dam/yr (e.g. Colas & Locat, 1992; Travelletti et al., 2012b). Eight TSX Spotlight data in ascending mode and thirteen in descending mode have been acquired. High resolution radar dataset The Table 1 lists the TSX spotlight images used for the analysis. The objective of the satellite programmation was to obtain a sufficient amount of data to estimate the changes in displacement rates during the study period. Thus the image acquisition rate has been deliberately increased for the periods between March and June as changes in the displacement regime (due to possible changes in the sub-surface water circulation in spring) were expected The ascending data set is incomplete due to failure in the data acquisition. However, the period between April and November 2010 is globally well covered. We preferred to plan data acquisitions with incidence angles of 41°.2 (ascending mode) and 49°.3 (descending mode) in order to minimize the surface affected by lay-over and shadowing phenomena. Methodology Sub-pixel image correlation The objective is to estimate local changes in the position of elements at the ground surface by comparing two images acquired at different dates. The observed position change on the image is interpreted as displacement. The estimation of such offsets (both in azimuth and range directions) is obtained by local correlation processing on the image pair. The method applied to SAR amplitude images has been firstly described by Michel et al. (1999) and is today widely used in characterization of tectonic plate movement associated to earthquake (e.g. de Michele et al, 2010a, b). This kind of technique is known to provide offsets estimation with a precision up to 1/20-1/10 pixel (and thus sometimes named sub-pixel correlation). Multi-temporal processing: The multi-temporal approach used for obtaining the evolution of the deformation is based on algorithms initially designed for deriving interferometric Time Series from a set of differential unwrapped interferograms (Berardino et al., 2002; Usai, 2003; Le Mouelic et al., 2005). Conclusions and perspectives This work demonstrates the interest of sub-pixel image correlation techniques applied to series of HR X-band SAR images for mapping and quantifying landslide displacement patterns. The characteristics of these data in terms of spatial resolution, geometry, repetitiveness and low dependence to the weather conditions are very suitable for landslide monitoring. It appears as a performing alternative to optical HR image correlation whose data can be hampered by atmospheric conditions. In the case of the La Valette landslide, the displacements observed for the period 2010-2011 are well depicted and are in agreement with the ground-based displacement observations. Displacement rates of up to 16 m.yr-1 are mapped and changes in the kinematic regime are detected with a decrease of the displacement rates between the months of July to November. The procedure for deriving such maps has revealed to be simple (and therefore easily automatable) and robust (no biases were detected during the processing). Noteworthy is the fact that the displacement rates are much higher than the expected accuracy with the reduced data set (seven images in ascending mode): in fact, the image acquisition was planned according to a priori knowledge on the foreseen displacement. Therefore, for landslides characterized by a different kinematic regime, a different data acquisition strategy should be used. In particular, for faster landslides (with displacement rates of m.month-1), the high repetitiveness of the current HR X-band space-borne sensors (TSX or Cosmo-Skymed) would allow to adjust (by increasing the acquisition rate) the inter-acquisition time span to higher displacement rates. As well, the accuracy of the method is also sufficient for monitoring slower landslides (with displacement rates of dm.yr-1) if longer time spans (e.g. years and more) are used. The proposed monitoring technique can therefore be applied to a wide range of landslide types. Acknowledgements The TerraSAR-X data used for this study was provided by DLR in the framework of the LAN0666 project. Processing was carried out in the framework of the project SafeLand “Living with landslide risk in Europe: assessment, effects of global change, and risk management strategies” (Grant Agreement No. 226479) funded by the 7th Framework Programme of the European Commission. The GNSS data are provided by the French Landslide Observatory (OMIV: Observatoire Multidisciplinaire des Instabilités de Versants: http://omiv.unistra.fr).

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