TRE Altamira s.r.l.

- Advanced Algorithm for Surface Displacement Detectiona Software


The most advanced algorithm for surface displacement detection, SqueeSAR is the latest InSAR technique developed by TRE ALTAMIRA for the detection of millimetre surface displacements, improving our previous PSInSAR algorithm.

PSI techniques first emerged in 1999 when the Polytechnic University of Milan (POLIMI) produced and patented its Permanent Scatterers Interferometry (or PSInSAR) algorithm.

PSInSAR is a significant evolution of conventional InSAR whereby:

  • A multi-image data set is used (minimum of 20-25 images).
  • Atmospheric and orbital errors are essentially removed.
  • Sub-pixel radar reflections are analyzed.
  • Linear and non-linear deformation patterns are identified.
  • Time histories of movement are generated for every radar target (PS).

The use of multi-image datasets makes it possible to identify stable reflectors, referred to as Permanent Scatterers, or PS, which are points on the ground that return stable signals to the satellite sensor (e.g. buildings, metallic objects, pylons, antennae, exposed rocks), allowing surface displacement velocities to be measured with millimeter accuracy. The PSInSAR algorithm was licensed to TRE for worldwide application.

Since its introduction in 2010, SqueeSAR has challenged the industry standard by identifying many more ground points, hence increasing the overall understanding of ground displacement occurring in an area of interest.

SqueeSAR™ is the only algorithm that we offer to clients, providing a significantly increased coverage of ground points, especially over non-urban areas. As it was standard with the previous PSInSAR™ algorithm, SqueeSAR™ continues to identify PS but it also exploits spatially distributed scatterers (DS). Whilst PS usually correspond to man-made objects, DS are typically identified from homogeneous ground, scattered outcrops, debris flows, non-cultivated lands and desert areas.

SqueeSAR results can be visualized as:

  • Average velocity map (for an overview of ground motion over the entire area of interest)
  • Displacement time Series, for each measurement point.

The position of each measurement point (latitude, longitude, elevation) and its quality values (standard deviation and coherence, which give an idea of how reliable each individual point is) are provided within the SqueeSAR database. The database can be easily imported in a GIS software and visualized or delivered in our web platform TREmaps.

In addition to principle results, the following SqueeSAR™ maps can also be delivered according to the movement expected or any interest in particular features:

  • Cumulative displacement, to map the total displacement that has occurred from the first satellite image acquisition to any sequential acquisition (from the second to the last).
  • Average acceleration, to highlight areas affected by increasing or decreasing rates of velocity
  • Periodic variation (seasonality), to highlight areas that exhibit cyclic behavior

Differential displacement, to allow displacements, that have occurred between two single satellite acquisitions (two discreet time periods), to be mapped and analyzed.

Single satellite geometry
What is actually measured in interferometric applications is the projection of a target’s motion onto the satellite’s Line Of Sight (LOS). However, the LOS motion can often differ noticeably from the real value of motion, especially in cases where the ground motion is not vertical.

Double satellite geometry: true vertical and horizontal east-west displacement
By using both ascending and descending imageries, it is possible to obtain an accurate estimate of the true vertical and east-west components of the motion.

The most important factors impacting on measurement quality are:

  • Spatial density of the measurement points (the lower the density, the higher the error bar)
  • Quality of the radar targets (signal-to-noise ratio levels)
  • Climatic conditions at the time of the acquisitions
  • Distance between the measurement point and the reference (REF)
  • Number and temporal distribution of acquisitions

The table below describes the precision values obtained from many analyses of data from the ERS, Envisat and Radarsat-1 satellites. Typical values of precision (1σ) for a point less than 1 km from the reference point (REF), considering a multi-year dataset of radar images.

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