Mapping vulnerable urban areas affected by slow-moving landslides using Sentinel-1InSAR data

Landslides are widespread natural hazards that generate considerable damage and economic losses worldwide. Detecting terrain movements caused by these phenomena and characterizing affected urban areas is critical to reduce their impact. Here we present a fast and simple methodology to create maps of vulnerable buildings affected by slow-moving landslides, based on two parameters: (1) the deformation rate associated to each building, measured from Sentinel-1 SAR data, and (2) the building damage generated by the landslide movement and recorded during a field campaign. We apply this method to Arcos de la Frontera, a monumental town in South Spain affected by a slow-moving landslide that has caused severe damage to buildings, forcing the evacuation of some of them. Our results show that maximum deformation rates of 4 cm/year in the line-of-sight (LOS) of the satellite, affects La Verbena, a newly-developed area, and displacements are mostly horizontal, as expected for a planar-landslide. Our building damage assessment reveals that most of the building blocks in La Verbena present moderate to severe damages. According to our vulnerability scale, 93% of the building blocks analysed present high vulnerability and, thus, should be the focus of more in-depth local studies to evaluate the serviceability of buildings, prior to adopting the necessary mitigation measures to reduce or cope with the negative consequences of this landslide. This methodology can be applied to slow-moving landslides worldwide thanks to the global availability of Sentinel-1 SAR data.Postprint (published version

Post-failure evolution analysis of a rainfall-triggered landslide by multi-temporal interferometry SAR approaches integrated with geotechnical analysis

Persistent Scatterers Interferometry (PSI) represents one of the most powerful techniques for Earth's surface deformation processes' monitoring, especially for long-term evolution phenomena. In this work, a dataset of 34 TerraSAR-X StripMap images (October 2013–October 2014) has been processed by two PSI techniques - Coherent Pixel Technique-Temporal Sublook Coherence (CPT-TSC) and Small Baseline Subset (SBAS) - in order to study the evolution of a slow-moving landslide which occurred on February 23, 2012 in the Papanice hamlet (Crotone municipality, southern Italy) and induced by a significant rainfall event (185 mm in three days). The mass movement caused structural damage (buildings' collapse), and destruction of utility lines (gas, water and electricity) and roads. The results showed analogous displacement rates (30–40 mm/yr along the Line of Sight – LOS-of the satellite) with respect to the pre-failure phase (2008–2010) analyzed in previous works. Both approaches allowed detect the landslide-affected area, however the higher density of targets identified by means of CPT-TSC enabled to analyze in detail the slope behavior in order to design possible mitigation interventions. For this aim, a slope stability analysis has been carried out, considering the comparison between groundwater oscillations and time-series of displacement. Hence, the crucial role of the interaction between rainfall and groundwater level has been inferred for the landslide triggering. In conclusion, we showed that the integration of geotechnical and remote sensing approaches can be seen as the best practice to support stakeholders to design remedial works.Peer ReviewedPostprint (author's final draft

Performance of TerraSAR-X for urban subsidence monitoring: Murcia case study

This paper presents an analysis of the performance of TerraSAR-X for subsidence monitoring in urban areas. The city of Murcia has been selected as a test-site due to its high deformation rate and the set of extensometers deployed along the city that provide validation data. The obtained results have been compared with those obtained from ERS/ENVISAT data belonging to the same period and validated with the in-situ measurements.Postprint (published version

Quality evaluation of DInSAR results from the phase statistical analysis

The Earth is continuously monitored by sensors capable of providing diversified information about several phenomena. In particular Synthetic Aperture Radar (SAR) is able to observe the Earth in all-day and all-weather conditions. Differential SAR Interferometry (DInSAR) regards a set of techniques able to measure displacement of the terrain. In the last decades these techniques have become very powerful geodetic tools for land deformation monitoring and have gained a prominent role in several fields, ranging from geophysical to engineering, from commercial to civil protection purposes. Measurements of direction and magnitude of landslides phenomena, monitoring of subsidence movements due to natural events or human activity are some examples of DInSAR applications. These techniques allow not only the analysis of a single deformation episode but also to estimate, with millimetric precision, the temporal evolution of large-scale deformations phenomena occurring on the Earth surface. This research covers transversally several aspects within the DInSAR applications and particularly is focused on analyzing step by step the DInSAR algorithm of the Coherent Pixel Technic (CPT) developed by the Universitat Politècnica de Catalunya (UPC) highlighting the conditions for a correct estimation of the solution. The achieved precision can be really high but anyway it is important to understand all the limitations that can change from one data-set to another. Particular attention has been paid on analyzing the different deteriorating factors that can affect the estimation, such as the quality of the data, the atmospheric artifacts or the spatial and temporal sampling of the phenomenon. In this regard, a theoretical study on the propagation of the interferometric phase noise has been carried out and validated through simulations. For reducing the impact of the interferometric phase noise normally only pixels with a certain quality can be processed. These pixels can be selected through different methods described in detail in the literature. On the one hand, each selection technique is able to detect a specific kind of target at a determined resolution. On the other hand, there is an obvious compromise between the quality and the pixels¿ density over the scene. Indeed, working with high densities could increase the reliability and the accuracy of the final result as long as poor quality pixels are not included in the processing. In this regard, in this Thesis a combination of the different kinds of targets has been studied with the objective of a joint processing at different resolutions. Finally the constant growth of the spaceborne, airborne and ground-based SAR sensors in terms of technology and number of available devices could be the beginning for exploiting at the same time different data-set in a joint processing. The integration of data coming from different sensors with different orbits, different resolution, different carrier frequencies and incidence angles can help in covering in a better way a complex displacement scenario and can provide more complete information.La Tierra está continuamente monitorizada por una gran variedad de sensores e instrumentos capaces de extraer información muy diversa de distintos fenómenos geofísicos. En este contexto, los Radares de Apertura Sintética (SAR) orbitales, terrestres o aerotransportados, están protagonizando un interés creciente, ya que permiten monitorizar escenarios de naturaleza muy diversa con independencia de las condiciones meteorológicas, operando tanto de día como de noche. Entre las diferentes aplicaciones que permiten explotar imágenes SAR, la Interferometría Diferencial SAR (DInSAR) ha adquirido una gran relevancia, permitiendo la monitorización de desplazamientos complejos de forma remota y con una elevada precisión. De hecho, en las últimas décadas, esta técnica se ha convertido en una herramienta geodésica de gran utilidad para el control del desplazamiento de superficies, adquiriendo un papel muy destacado en una gran variedad de áreas de investigación y comerciales: mediciones de dirección y magnitud en deslizamientos, control de fenómenos de subsidencia debido a eventos naturales o actividades humanas, etc. Las técnicas DInSAR no sólo permiten medir un episodio de deformación aislado sino también estimar, con precisiones milimétricas, la evolución temporal de desplazamientos de gran escala. En la presente Tesis doctoral se investigan de forma transversal varios aspectos en el marco de aplicaciones DInSAR y, en particular y de una forma más exhaustiva, el algoritmo Coherent Pixel Technique (CPT) desarrollado por la Universidad Politécnica de Cataluña (UPC), remarcando las condiciones de contorno necesarias para la correcta estimación de las soluciones. A pesar de que la precisión en los resultados obtenidos puede ser elevada, es de extremada importancia analizar en profundidad las limitaciones existentes para los distintos escenarios posibles. En este contexto, se ha prestado una especial atención al análisis de los diferentes factores de error que pueden afectar a la estimación, tales como la calidad de los datos, los artefactos atmosféricos o el muestreo espacial y temporal del fenómeno bajo observación. Con este propósito, se ha desarrollado un estudio teórico detallado relacionado con la propagación del ruido de fase interferométrica a lo largo de la cadena de procesado DInSAR, que a su vez ha sido validado mediante datos simulados. Con el objetivo de reducir el impacto del ruido de fase interferométrica, únicamente aquellos píxeles del escenario que cumplen con unos ciertos parámetros de calidad de fase deben ser incluidos en el procesado. Estos píxeles pueden ser seleccionados previamente a través de diferentes metodologías que se describen en detalle en la literatura. Por un lado, ha de tenerse en cuenta que cada una de estas técnicas es adecuada para un determinado tipo de blanco y resolución. Por otro lado, ha de remarcarse que existe un compromiso claro entre calidad y densidad. Efectivamente, trabajar con densidades elevadas favorece la fiabilidad del procesado y la utilidad de los resultados finales, siempre y cuando no sea a expensas de incluir píxeles de mala calidad. Con este propósito, en este trabajo de Tesis doctoral se propone la combinación de los distintos tipos de blanco a distintas resoluciones, obtenidos con los distintos métodos de selección disponibles, para la realización de un procesado conjunto. Finalmente, el crecimiento de sensores SAR aerotransportados y terrestres, en términos de tecnología y número de dispositivos disponibles, podría ser el comienzo para la explotación conjunta de datos desde múltiples plataformas. En este contexto, se muestra como la integración de los datos procedentes de diferentes sensores con distintas órbitas, resolución, frecuencia y ángulo de incidencia favorecen la obtención de mayores coberturas y mejoran el proceso de estimación de desplazamiento, dando lugar a una información más completa y detallada

Insar atmospheric delays compensation: case study in Tenerife island

Differential Interferometry SAR (DInSAR) is an advanced technique to retrieve ground deformation in the geoscience community. Atmospheric Phase Screen (APS) is one of the largest challenges limiting the application of DInSAR especially in mountainous areas. In this paper we propose an approach based on an empirical linear model for compensating stratified atmospheric phase delay in differential interferograms. Compared with conventional empirical linear model, the influence of turbulent APS is taken into consideration in our work. With this, the modelled stratified APS is more accurate. We test our algorithm using Envisat dataset and Sentinel dataset over Tenerife island (Spain). The performance of the approach is compared with Global Atmospheric Models (GAMs).Peer ReviewedPostprint (published version

Landslide monitoring with spotlight TerraSAR-X DATA

This paper aims to demonstrate that radar-based remote sensing techniques can be as effective as the conventional geotechnical ones for the detection and monitoring of well suited areas. Many of the high mountain landslides are vegetated areas that decorrelate faster at X-band. As in these scenarios the number of coherent scatterers is low and, in addition, the area of interest is usually small, the processing can be benefited of the usage of high-resolution data. This will maximize the chances of detecting persistent scatters coming from both natural targets and man-made structures. The high resolution Spotlight mode of TerraSAR-X is thus the perfect choice as it offers a fine resolution. On the other hand, its 11 days of revisit time and X-band carrier allows the monitoring of small variations in the landslide trend and deal with its variable dynamics.Peer Reviewe

Iterative solution to temporal phase wrapping in differential SAR interferometry for high displacement rate phenomena

Temporal phase wrapping may be an issue in Differential SAR Interferometry (DInSAR) for terrain displacement monitoring, especially when the deformation rate of the phenomena under observation is high and/or the temporal sampling of the SAR dataset is poor. This work proposes upgrades in the Coherent Pixels Technique in order to deal with these situations. They are based on an iterative method to reach the optimum solution and an approach to obtain an a priori model of the displacement phenomenon. Both methods are tested with an Envisat ASAR data-set over a mining area.Peer ReviewedPostprint (published version

A new approach to DInSAR pixel selection with spectral correlation along time between Sublooks

This paper presents a full resolution pixel selection method, alternative to the traditional ones, which is based on the study of the spectral correlation coefficient along time among different Sublooks of the image spectrum. This pixel selection criterion has been developed from the concept of the so-called Coherent Scatters (CSs), which are characterized by a deterministic point-like scattering behaviour in each single acquisition, but now including its temporal stability. The proposed method presents the advantage that it does not require any radiometric cali- bration of the data as it only uses the spectral propertie s of a point-scatter but not relying on its amplitude.Peer ReviewedPostprint (published version

A new approach to DInSAR pixel selection with spectral correlation along time between Sublooks

This paper presents a full resolution pixel selection method, alternative to the traditional ones, which is based on the study of the spectral correlation coefficient along time among different Sublooks of the image spectrum. This pixel selection criterion has been developed from the concept of the so-called Coherent Scatters (CSs), which are characterized by a deterministic point-like scattering behaviour in each single acquisition, but now including its temporal stability. The proposed method presents the advantage that it does not require any radiometric cali- bration of the data as it only uses the spectral propertie s of a point-scatter but not relying on its amplitude.Peer Reviewe

A new approach to DInSAR pixel selection with a combined multi resolution selection method

In DInSAR processing it is possible to detect different kinds of targets at different resolutions. Point like scatters can be selected with high resolution selection methods, like amplitude dispersion. Distributed scatters can be selected with a coherence spatial window. The joint combination of two or more pixel selection methods can be useful to get a higher pixel density and identify, compare and evaluate distributed and point like scatters at the same time.Peer Reviewe