A systematic exploration of satellite radar coherence methods for rapid landslide detection

Emergency responders require information on the distribution of triggered landslides within 2 weeks of an earthquake or storm. Useable satellite radar imagery is acquired within days of any such event worldwide. Recently, several landslide detection methods that use these data have been developed, but testing of these methods has been limited in each case to a single event and satellite sensor. Here we systematically test five methods using ALOS-2 and Sentinel-1 data across four triggering earthquakes. The best-performing method was dependent on the satellite sensor. For three of our four case study events, an initial ALOS-2 image was acquired within 2 weeks, and with these data, co-event coherence loss (CECL) is the best-performing method. Using a single post-event Sentinel-1 image, the best-performing method was the boxcar–sibling (Bx–S) method. We also present three new methods which incorporate a second post-event image. While the waiting time for this second post-event image is disadvantageous for emergency response, these methods perform more consistently and on average 10 % better across event and sensor type than the boxcar–sibling and CECL methods. Thus, our results demonstrate that useful landslide density information can be generated on the timescale of emergency response and allow us to make recommendations on the best method based on the availability and latency of post-event radar data.

ADVANCED DIFFERENTIAL INTERFEROMETRIC SAR TECHNIQUE A-DINSAR FOR THE STUDY OF LARGE LANDSLIDES

Large landslides are widespread both in the Alps and in Apennines; the observed movements are generally from extremely slow to slow with some occasional acceleration; the sudden and paroxysmal collapse of the whole mass may have catastrophic consequences. They are also difficult to characterize in their boundaries and state of activity and to monitor with traditional tools. The Advanced Differential interferometric SAR (Synthetic Aperture Radar) technique, A-DInSAR, is a remote sensing technique, which is based on satellite radar imagery for the ground motion measurement. It is based on large stacks of SAR images and enables the measure of small displacement of the ground with a millimetThe aim of this study is to apply the A-DInSAR technique in some large landslide in Alps (Brenvetto, Rosone and Alpe Baranca landslides) in order to study the effectiveness of the technique in their study and monitoring.

A Systematic Exploration of Satellite Radar Coherence Methods for Rapid Landslide Detection

Emergency responders require information on the distribution of triggered landslides within two weeks of an earthquake or storm. Useable satellite radar imagery is acquired within days of any such event worldwide. Recently, several landslide detection methods that use these data have been developed, but testing of these methods has been limited in each case to a single event and satellite sensor. Here we systematically test five methods using ALOS-2 and Sentinel-1 data across four triggering events. The best performing method was dependent on the satellite sensor. For three of our four case study events, an initial ALOS-2 image was acquired within 2 weeks, and with these data the ARIA method performs best. Using a single post-event Sentinel-1 image, the best-performing method was the boxcar-sibling method. We also present three new methods which incorporate a second post-event image. While the waiting time for this second post-event image is disadvantageous for emergency response, these methods perform more consistently and on average 10 % better across event and sensor type than the boxcar-sibling and ARIA methods. Thus, our results demonstrate that useful landslide density information can be generated on the timescale of emergency response, and allow us to make recommendations on the best method based on the availability and latency of post-event radar data.

Persistent Scatterer Interferometry of Sentinel-1 time series to detect ground subsidence in the city of Recife, Brazil

Persistent Scatterer Interferometry (PSI) analysis of Sentinel-1 time series was carried out to detect ground subsidence in the city of Recife, Brazil. The dataset consisted of sixty-eight Sentinel-1A Interferometric Wide (IW) Single Look Complex (SLC) images of the time period April 2017 – September 2019. The images were acquired in descending orbit in VV (vertical transmitting, vertical receiving) polarization. The results of the PSI analysis show that in the city of Recife occur several ground subsidence areas. The largest ground subsidence area occurs between the neighborhoods of Afogados, Torrŏes and Cordeiro. The subsidence rates in this area range from few mm/year up to -15 mm/year. This ground subsidence could be a result of groundwater extraction or of subsidence processes in urbanized reclaimed lands. Similar but smaller ground subsidence areas occur in several localities in Recife. In some cases, subsidence with rates of up to -25 mm/year is noted in small zones where new buildings have been constructed in the last decade. This should be due to ground settlement processes, taking a long time due to the particular soils and geology of the locality. This study can serve as a first contribution for further research on the ground subsidence hazard in the city of Recife and the surrounding areas by means of satellite radar imagery.

LAKE URMIA BRIDGE STABILITY ASSESSMENT: RESULTS FROM TERRASAR-X SPOTLIGHT MODE IMAGES

In this study we investigate stability of Lake Urmia bridge, locally also known as Shahid Kalantari’s highway bridge, in northwest of Iran using high-resolution satellite radar imagery. The radar dataset includes 22 SAR images acquired in SpotLight mode from 2014 to 2015 in an ascending orbit by TerraSAR-X satellite. A high-resolution Digital Elevation Model (DEM) of the area was constructed from a pair of TanDEM-X bi-static data on June 2012 to remove the effect of topography from interferometry observations. The analysis of X-band interferograms shows high number of displacement fringes, which are interpreted as being caused by thermal dilation due to temperature differences in the imaged area between two SAR acquisitions. This effect, which can often be observed in single interferograms, have important impact on time-series products and should be considered for deformation analysis of bridge structures.