A Network-Based Enhanced Spectral Diversity Approach for TOPS Time-Series Analysis

For multitemporal analysis of synthetic aperture radar (SAR) images acquired with a terrain observation by progressive scan (TOPS) mode, all acquisitions from a given satellite track must be coregistered to a reference coordinate system with accuracies better than 0.001 of a pixel (assuming full SAR resolution) in the azimuth direction. Such a high accuracy can be achieved through geometric coregistration, using precise satellite orbits and a digital elevation model, followed by a refinement step using a time-series analysis of coregistration errors. These errors represent the misregistration between all TOPS acquisitions relative to the reference coordinate system. We develop a workflow to estimate the time series of azimuth misregistration using a network-based enhanced spectral diversity (NESD) approach, in order to reduce the impact of temporal decorrelation on coregistration. Example time series of misregistration inferred for five tracks of Sentinel-1 TOPS acquisitions indicates a maximum relative azimuth misregistration of less than 0.01 of the full azimuth resolution between the TOPS acquisitions in the studied areas. Standard deviation of the estimated misregistration time series for different stacks varies from 1.1e-3 to 2e-3 of the azimuth resolution, equivalent to 1.6-2.8 cm orbital uncertainty in the azimuth direction. These values fall within the 1-sigma orbital uncertainty of the Sentinel-1 orbits and imply that orbital uncertainty is most likely the main source of the constant azimuth misregistration between different TOPS acquisitions. We propagate the uncertainty of individual misregistration estimated with ESD to the misregistration time series estimated with NESD and investigate the different challenges for operationalizing NESD

Mexico City land subsidence in 2014-2015 with Sentinel-1 IW TOPS: results using the Intermittent SBAS (ISBAS) technique

Differential Interferometric Synthetic Aperture Radar (DInSAR) can be considered as an efficient and cost effective technique for monitoring land subsidence due to its large spatial coverage and high accuracy provided. The recent commissioning of the first Sentinel-1 satellite offers improved support to operational surveys using DInSAR due to regular observations from a wide-area product. In this paper we show the results of an intermittent small-baseline subset (ISBAS) time-series analysis of 18 Interferometric Wide swath (IW) products of a 39,000 km2 area of Mexico acquired between 3 October 2014 and 7 May 2015 using the Terrain Observation with Progressive Scans in azimuth (TOPS) imaging mode. The ISBAS processing was based upon the analysis of 143 small-baseline differential interferograms. After the debursting, merging and deramping steps necessary to process Sentinel-1 IW roducts, the method followed a standard approach to the DInSAR analysis. The Sentinel-1 ISBAS results confirm the magnitude and extent of the deformation that was observed in Mexico City, Chalco, Ciudad Nezahualcóyotl and Iztapalapa by other C-band and L-band DInSAR studies during the 1990s and 2000s. Subsidence velocities from the Sentinel-1 analysis are, in places, in excess of -24 cm/year along the satellite line-of-sight, equivalent to over ~-40 cm/year vertical rates. This paper demonstrates the potential of Sentinel-1 IW TOPS imagery to support wide-area DInSAR surveys over what is a very large and diverse area in terms of land cover and topography

Displacements Monitoring over Czechia by IT4S1 System for Automatised Interferometric Measurements Using Sentinel-1 Data

The Sentinel-1 satellite system continuously observes European countries at a relatively high revisit frequency of six days per orbital track. Given the Sentinel-1 configuration, most areas in Czechia are observed every 1–2 days by different tracks in a moderate resolution. This is attractive for various types of analyses by various research groups. The starting point for interferometric (InSAR) processing is an original data provided in a Single Look Complex (SLC) level. This work represents advantages of storing data augmented to a specifically corrected level of data, SLC-C. The presented database contains Czech nationwide Sentinel-1 data stored in burst units that have been pre-processed to the state of a consistent well-coregistered dataset of SLC-C. These are resampled SLC data with their phase values reduced by a topographic phase signature, ready for fast interferometric analyses (an interferogram is generated by a complex conjugate between two stored SLC-C files). The data can be used directly into multitemporal interferometry techniques, e.g., Persistent Scatterers (PS) or Small Baseline (SB) techniques applied here. A further development of the nationwide system utilising SLC-C data would lead into a dynamic state where every new pre-processed burst triggers a processing update to detect unexpected changes from InSAR time series and therefore provides a signal for early warning against a potential dangerous displacement, e.g., a landslide, instability of an engineering structure or a formation of a sinkhole. An update of the processing chain would also allow use of cross-polarised Sentinel-1 data, needed for polarimetric analyses. The current system is running at a national supercomputing centre IT4Innovations in interconnection to the Czech Copernicus Collaborative Ground Segment (CESNET), providing fast on-demand InSAR results over Czech territories. A full nationwide PS processing using data over Czechia was performed in 2017, discovering several areas of land deformation. Its downsampled version and basic findings are demonstrated within the article

Time Series Analysis of Surface Deformation Associated With Fluid Injection and Induced Seismicity in Timpson, Texas Using DInSAR Methods

In recent years, a rise in unconventional oil and gas production in North America has been linked to an increase in seismicity rate in these regions (Ellsworth, 2013). As fluid is pumped into deep formations, the state of stress within the subsurface changes, potentially reactivating pre-existing faults and/or causing subsidence or uplift of the surface. Therefore, hydraulic fracturing and/or fluid disposal injection can significantly increase the seismic hazard to communities and structures surrounding the injection sites (Barnhart et al., 2014). On 17th May 2012 an Mw4.8 earthquake occurred near Timpson, TX and has been linked with wastewater injection operations in the area (Shirzaei et al., 2016). This study aims to spatiotemporally relate, wastewater injection operations to seismicity near Timpson using differential interferometric synthetic aperture radar (DInSAR) analysis. Results are presented as a set of time series, produced using the Multidimensional Small Baseline Subset (MSBAS) InSAR technique, revealing two-dimensional surface deformation

3-D Satellite Interferometry for Interseismic Velocity Fields

The global interseismic strain rate map is being accomplished rapidly with measurements of the space-based geodetic technique of InSAR. High-resolution measurements of crustal deformation from InSAR can provide crucial constraints on a region's active tectonics, geodynamics, and seismic hazard. However, space-based InSAR usually only provides good constraints on horizontal displacement in the east-west direction, with the north-south component typically provided by low-resolution GNSS measurements. Sentinel-1, on the other hand, has the potential to provide measurements that are sensitive to north-south motion, through exploitation of the burst overlap areas produced by the TOPS acquisition mode. However, the significant noise contributions from decorrelation and propagation through the ionosphere make it challenging to detect surface displacements associated with interseismic deformation needing millimeters per year accuracy. The ionospheric phase advance is a significant nuisance term that can bias InSAR measurements. Although methods have been developed to mitigate the effect, they are not always routinely applied when processing C-band SAR images, for which the effect is generally expected to be small. Nevertheless, the effect can be significant, especially when analyzing low deformation gradients over large areas using time-series analysis. Here, the work in Chapter 3 presents a time-series approach to ionospheric noise mitigation, which improves on existing methods. Firstly, I estimate the ionospheric contribution for each individual acquisition from multiple interferograms, which reduces noise. Secondly, this work improved the identification of unwrapping errors, which can bias the estimation. Thirdly, I introduce a new filtering approach, which gives better results, particularly at image edges and areas with variable density of coherent measurements. Furthermore, the approach is applicable when estimating along-track motion in burst overlap areas. The results show that applying the correction improves velocity accuracy significantly for both conventional line-of-sight and burst overlap interferometry techniques. The application of measuring long-term tectonic signals that concentrate in the north-south component with millimeters per year accuracy is essential to constrain interseismic strain globally. In Chapter 4, I also demonstrate a time-series approach with the burst overlap interferometry appropriate for extracting subtle long-term displacements. The approach includes mitigation of ionospheric noise, and I investigate different filtering approaches to optimize the reduction of decorrelation noise. I present the mean ground velocity in the azimuth direction from data acquired between 2014 and 2019 along the West-Lut Fault, a north-south striking fault in eastern Iran. The chi-square statistic defines a good agreement between the results and independent GNSS measurements. Moreover, the denser coverage of the technique allows to detect the variation in strain accumulation between northern and southern segments of the fault, with our modeling indicating a variation of slip rate from 9.2±0.5 mm/yr in the south to 4.3±0.5 mm/yr in the north. With current efforts to use InSAR to constrain strain rates globally, along-track measurements can fill a crucial gap in north-south sensitivity. With the achievement of that the burst overlap InSAR technique can measure azimuth motions across a slowly deforming area where the surface displacements are concentrated in the north-south component, this results in that, in the TOPS burst overlap region, the number of observations for a ground displacement can reach 3-4 times with different observational components. Measurement redundancy allows for the decomposition of observed velocities into three-dimensional components. In Chapter 5, I apply InSAR observations to estimate a deformation across the Chaman fault in both line-of-sight and along-track components using images from ascending and descending passes. I demonstrate an inversion to estimate the decomposed velocities. The algorithm employs a sparse GNSS network across the region to transform InSAR velocities to the GNSS reference frame. The results show that constraining the long-wavelength signal across the InSAR observations using GNSS data can mitigate the long-wavelength ionospheric disturbance that remains in the observations. The variation in slip rates across the Chaman fault is depicted by two transect profiles. The mean velocity profile at latitude 31˚N, where the Chaman fault is the only tectonic structure to accommodate strain, is consistent with 10.4±0.4 mm/yr of slip rate derived from the interseismic modeling. The optimal fault slip rate to fit with the mean velocity of the southern profile at latitude 29˚N is 5.5±0.8 mm/yr across the Chaman fault and 15.5±0.9 mm/yr across the parallel fault (the Ghazaband fault). I also demonstrate the benefits of high temporal sampling of InSAR observations with TOPS acquisition mode to study time-dependent surface deformation. I present the evolution of fault creeps, including seismic and aseismic fault slip along the Chaman fault during 2014-2018

Ground Investigations and Detection and Monitoring of Landslides Using SAR Interferometry in Gangtok, Sikkim Himalaya

The Himalayan state of Sikkim is prone to some of the world’s largest landslides, which have caused catastrophic damage to lives, properties, and infrastructures in the region. The settlements along the steep valley sides are particularly subject to frequent rainfall-triggered landslide events during the monsoon season. The region has also experienced smaller rock slope failures (RSF) after the 2011 Sikkim earthquake. The surface displacement field is a critical observable for determining landslide depth and constraining failure mechanisms to develop effective mitigation techniques that minimise landslide damage. In the present study, the persistent scatterers InSAR (PSI) method is employed to process the series of Sentinel 1-A/B synthetic aperture radar (SAR) images acquired between 2015 and 2021 along ascending and descending orbits for the selected areas in Gangtok, Sikkim, to detect potentially active, landslide-prone areas. InSAR-derived ground surface displacements and their spatio-temporal evolutions are combined with field investigations to better understand the state of activity and landslide risk assessment. Field investigations confirm the ongoing ground surface displacements revealed by the InSAR results. Some urban areas have been completely abandoned due to the structural damage to residential housing, schools, and office buildings caused by displacement. This paper relates the geotechnical investigations carried out on the ground to the data obtained through interferometric synthetic aperture radar (InSAR), focusing on the triggering mechanisms. A strong correlation between seasonal rainfall and landslide acceleration, as well as predisposing geological-structural setting, suggest a causative mechanism of the landslides.Ground Investigations and Detection and Monitoring of Landslides Using SAR Interferometry in Gangtok, Sikkim HimalayapublishedVersio

Uncertainties and Perspectives on Forest Height Estimates by Sentinel-1 Interferometry

Forest height is a key parameter in forestry. SAR interferometry (InSAR) techniques have been extensively adopted to retrieve digital elevation models (DEM) to give a representation of the continuous variation of the Earth’s topography, including forests. Unfortunately, InSAR has been proven to fail over vegetation due to low coherence values; therefore, all phase unwrapping algorithms tend to avoid these areas, making InSAR-derived DEM over vegetation unreliable. In this work, a sensitivity analysis was performed with the aim of properly initializing the relevant operational parameters (baseline and multilooking factor) to maximize the theoretical accuracy of the height difference between the forest and reference point. Some scenarios were proposed to test the resulting “optimal values”, as estimated at the previous step. A simple model was additionally proposed and calibrated, aimed at predicting the optimal baseline value (and therefore image pair selection) for height uncertainty minimization. All our analyses were conducted using free available data from the Copernicus Sentinel-1 mission to support the operational transfer into the forest sector. Finally, the potential uncertainty affecting resulting height measures was quantified, showing that a value lower than 5 m can be expected once all user-dependent parameters (i.e., baseline, multilooking factor, temporal baseline) are properly tuned

The 2-Look TOPS Mode: Design and Demonstration with TerraSAR-X

Burst-mode acquisition schemes achieve wide coverage at the expense of a degraded azimuth resolution, reducing therefore the performance on the retrieval of ground displacements in the azimuth direction, when interferometric acquisitions are combined. Moreover the azimuth varying line-of-sight can induce discontinuities in the interferometric phase when local azimuth displacements are present, e.g., due to ground deformation. In this contribution we propose the interferometric 2-look TOPS mode, a sustaining innovation, which records bursts of radar echoes of two separated slices of the Doppler spectrum. The spectral separation allows to exploit spectral diversity techniques, achieving sensitivities to azimuth displacements better than with StripMap, and eliminating discontinuities in the interferometric phase. Moreover some limitations of the TOPS mode to compensate ionospheric perturbations, in terms of data gaps or restricted sensitivity to azimuth shifts, are overcome. The design of 2-look TOPS acquisitions will be provided, taking the TerraSAR-X system as reference to derive achievable performances. The methodology for the retrieval of the azimuth displacement is exposed for the case of using pairs of images, as well as for the calculation of mean azimuth velocities when working with stacks. We include results with experimental TerraSAR-X acquisitions demonstrating its applicability for both scenarios

Method for landslides detection with semi-automatic procedures: The case in the zone center-east of Cauca department, Colombia

Landslides are a common natural hazard that causes human casualties, but also infrastructure damage and land-use degradation. Therefore, a quantitative assessment of their presence is required by means of detecting and recognizing the potentially unstable areas. This research aims to develop a method supported on semiautomatic methods to detect potential mass movements at a regional scale. Five techniques were studied: Morphometry, SAR interferometry (InSAR), Persistent Scatterer InSAR (PS-InSAR), SAR polarimetry (PolSAR) and NDVI composites of Landsat 5, Landsat 7, and Landsat 8. The case study was chosen within the mid-eastern area of the Cauca state, which is characterised by its mountainous terrain and the presence of slope instabilities, officially registered in the CGS-SIMMA landslide inventory. This inventory revealed that the type `slide' occurred with 77.4% from the entire registries, `fall' with 16.5%, followed by `creeps' with 3%, flows with 2.6%, and `lateral spread' with 0.43%. As a result, we obtained the morphometric variables: slope, CONVI, TWI, landform, which were highly associated with landslides. The effect of a DEM in the processing flow of the InSAR method was similar for the InSAR coherence variable using the DEMs ASTER, PALSAR RTC, Topo-map, and SRTM. Then, a multiInSAR analysis gave displacement velocities in the LOS direction between -10 and 10 mm/year. With the dual-PolSAR analysis (Sentinel-1), VH and VV C-band polarised radar energy emitted median values of backscatters, for landslides, about of -14.5 dB for VH polarisation and -8.5 dB for VV polarisation. Also, L-band fully polarimetric NASA-UAVSAR data allowed to nd the mechanism of dispersion of CGS landslide inventory: 39% for surface scattering, 46.4% for volume dispersion, and 14.6% for double-bounce scattering. The optical remote sensing provided NDVI composites derived from Landsat series between 2012 and 2016, showing that NDVI values between 0.40 and 0.70 had a high correlation to landslides. In summary, we found the highest categories related to landslides by Weight of Evidence method (WofE) for each spaceborne technique applied. Finally, these results were merged to generate the landslide detection model by using the supervised machine learning method of Random Forest. By taking training and test samples, the precision of the detection model was of about 70% for the rotational and translational types.Los deslizamientos son una amenaza natural que causa pérdidas humanas, daños a la infraestructura y degradación del suelo. Una evaluación cuantitativa de su presencia se requiere mediante la detección y el reconocimiento de potenciales áreas inestables. Esta investigación tuvo como alcance desarrollar un método soportado en métodos semi-automáticos para detectar potenciales movimientos en masa a escala regional. Cinco técnicas fueron estudiadas: Morfometría, Interferometría radar, Interferometría con Persistent Scatterers, Polarimetría radar y composiciones del NDVI con los satélites Landsat 5, Landsat 7 y Landsat 8. El caso de estudio se seleccionó dentro de la región intermedia al este del departamento del Cauca, la cual se caracteriza por terreno montañoso y la presencia de inestabilidades de la pendiente oficialmente registrados en el servicio SIMMA del Servicio Geológico Colombiano. Este inventario reveló que el tipo de movimiento deslizamiento ocurrió con una frecuencia relativa de 77.4%, caidos con el 16.5% de los casos y reptaciones con 3%, flujos con 2.6% y propagación lateral con 0.43%. Como resultado, se obtuvo las variables morfométricas: pendiente, convergencia, índice topográfico de humedad y forma del terreno altamente asociados con los deslizamientos. El efecto de un DEM en el procesamiento del método InSAR fue similar para la variable coherencia usando los DEMs: ASTER, PAlSAR RTC, Topo-map y SRTM. Un análisis Multi-InSAR estimó velocidades de desplazamiento en dirección de vista del radar entre -10 y 10 mm/año. El análisis de polarimetría dual del Sentinel-1 arrojó valores de retrodispersión promedio de -14.5 dB en la banda VH y -8.5dB en la banda VV. Las cuatro polarimetrías del sensor aéreo UAVSAR permitió caracterizar el mecanismo de dispersión del Inventario de Deslizamiento así: 39% en el mecanismo de superficie, 46.4% en el mecanismo de volumen y 14.6% en el mecanismo de doble rebote. La información generada en el rango óptico permitió obtener composiciones de NDVI derivados de la plataforma Landsat entre los años 2012 y 2016, mostrando que el rango entre 0.4 y 0.7 tuvieron una alta asociación con los deslizamientos. En esta investigación se determinaron las categorías de las variables de Teledetección más altamente relacionadas con los movimientos en masa mediante el método de Pesos de Evidencias (WofE). Finalmente, estos resultados se fusionaron para generar el modelo de detección de deslizamientos usando el método supervisado de aprendizaje de máquina Random Forest. Tomando muestras aleatorias para entrenar y validar el modelo en una proporción 70:30, el modelo de detección, especialmente los movimientos de tipo rotacional y traslacional fueron clasificados con una tasa general de éxito del 70%.Ministerio de CienciasConvocatoria 647 de 2014Research line: Geotechnics and Geoenvironmental HazardDoctorad