The Interferometric Use of Radar Sensors for the Urban Monitoring of Structural Vibrations and Surface Displacements

In this paper, we propose a combined use of real aperture radar (RAR) and synthetic aperture radar (SAR) sensors, within an interferometric processing chain, to provide a new methodology for monitoring urban environment and historical buildings at different temporal and spatial scales. In particular, ground-based RAR measurements are performed to estimate the vibration displacements and the natural oscillation frequencies of structures, with the aim of supporting the understanding of the building dynamic response. These measurements are then juxtaposed with ground-based and space-borne SAR data to monitor surface deformation phenomena, and hence, point out potential risks within an urban environment. In this framework, differential interferometric SAR algorithms are implemented to generate short-term (monthly) surface displacement and long-term (annual) mean surface displacement velocity maps at local (hundreds m2) and regional (tens km2) scale, respectively. The proposed methodology, developed among the activities carried out within the national project Programma Operativo Nazionale MASSIMO (Monitoraggio in Area Sismica di SIstemi MOnumentali), is tested and discussed for the ancient structure of Saint Augustine compound, located in the historical center of Cosenza (Italy) and representing a typical example of the Italian Cultural Heritage

A Hybrid Particle Swarm Optimization with Affine Transformation Approach for Cloud Free Multi-Temporal Image Registration

An image registration is the major part of the image categorization and cluster formation in multi temporal image processing. The images are affected by the different factors such as cloud shadow, water level, building shadows etc. In this paper, an enhanced registration process and the cloud removal technique is proposed for image enhancement. The Daemons, Combined Registration and Segmentation (CRS) approach, Markov Random Field (MRF) approach and Mutual Information (MI) based approaches results in more computational complexity, minimum edge preservation measure (QAB/F) and Mutual Information in image registration. In order to maximize the quality of edge preservation measure and MI with minimum computational time, this paper proposes Particle Swarm Optimization (PSO) based affine transformation technique. The proposed techniques measure and compare the computation time against the number of pixels of an image with the existing methods of CRS and MRF for the number of images. The comparative analysis of QAB/F and MI with the traditional methods of Clock Point -Least Square (CP-LS) and the Multi-Focus Image Fusion (MFIF) and Discrete Wavelet Transform (DWT) is presented to confirm the effective performance. The simulation results of the proposed transformation for registration process confirms the effective image registration in the multi-temporal image processing

A markovian approach to unsupervised change detection with multiresolution and multimodality SAR data

In the framework of synthetic aperture radar (SAR) systems, current satellite missions make it possible to acquire images at very high and multiple spatial resolutions with short revisit times. This scenario conveys a remarkable potential in applications to, for instance, environmental monitoring and natural disaster recovery. In this context, data fusion and change detection methodologies play major roles. This paper proposes an unsupervised change detection algorithmfor the challenging case of multimodal SAR data collected by sensors operating atmultiple spatial resolutions. The method is based on Markovian probabilistic graphical models, graph cuts, linear mixtures, generalized Gaussian distributions, Gram-Charlier approximations, maximum likelihood and minimum mean squared error estimation. It benefits from the SAR images acquired at multiple spatial resolutions and with possibly different modalities on the considered acquisition times to generate an output change map at the finest observed resolution. This is accomplished by modeling the statistics of the data at the various spatial scales through appropriate generalized Gaussian distributions and by iteratively estimating a set of virtual images that are defined on the pixel grid at the finest resolution and would be collected if all the sensors could work at that resolution. A Markov random field framework is adopted to address the detection problem by defining an appropriate multimodal energy function that is minimized using graph cuts

Vulnerability and response measures to natural hazard and sea level rise impacts: long-term coastal zone management, NE of the State of Pará, Brazil

The coastal zone of the NE of the State of Pará (Brazil)is affected by erosion and flooding problems. Their impacts are more evident in the main urban centers. This study aims to analyze how the natural hazards issue can be included into a contexts of a long-term integrated coastal zone management (ICZM) program, and to support state and municipal government activities. Within a modified Pressure-State-Impact-Response framework, current and potential pressures on the system are considered, as the global and relative sea level rise, and the growing human population and development scenarios for the next century. A GIS-based index was created to combine natural and socioeconomic variables in order to analyse the regional vulnerability and identify the most susceptible sectors. Response strategies and measures were analyzed according to the Intergovernmental Panel for Climate Change classification: no action, protection, accommodation, and retreat. Finally, some recommendations have been proposed to permit implementing new strategies and measures, and modifying and improving those already existent

Estudio de la dinámica de los asentamientos periurbanos bonaerenses. El caso de estudio de los partidos de Moreno, Pilar y Tigre

Tesis (Magister en Aplicaciones Espaciales de Alerta y Respuesta Temprana a Emergencias)--Universidad Nacional de Córdoba, Facultad de Matemática, Astronomía, Física y Computación, 2017.Maestría conjunta con el Instituto de Altos Estudios Espaciales "Mario Gulich"-CONAE.En este trabajo, se proponen cadenas de procesamiento que permiten extraer mapas de los usos del suelo del periurbano bonaerense y analizar su vulnerabilidad frente a amenazas ambientales locales. Los métodos empleados para la obtención de coberturas son el desmezclado espectral lineal y la clasificación supervisada de imágenes multiespectrales (EO1 Hyperion, Landsat TM y OLI, SPOT 5). Luego, se identifican los tipos de urbanización predominantes mediante la dimensión fractal (D) que describe el grado de compactación de un área. Por último, se aplica la suma lineal ponderada multicriterio para evaluar la vulnerabilidad de las urbanizaciones a eventos como las inundaciones, entre otras. El estudio se realiza en los partidos de Moreno, Pilar y Tigre, todos ellos pertenecientes al periurbano bonaerense en el período de 1985 a 2015.This study proposes processing chains that allow the extraction of land use maps of peri-urban areas and the analysis of their vulnerability to environmental threats. The methods used for the analysis include spectral linear unmixing and supervised classification of multispectral images (EO1 Hyperion, Landsat, SPOT). Subsequently, predominant urbanization types in peri-urban areas were identified based on their fractal dimension (D), that describes the compaction degree of an area. Lastly, multicriterial weighted linear addition was applied to assess the vulnerability of urbanization to environmental threats such as floods, among others. The study was carried out in three districts located in Buenos Aires peri-urban area, Moreno, Pilar and Tigre, in the period 1985-2015

Development and validation of multitemporal image analysis methodologies for multirisk monitoring of critical structures and infrastructures

In the framework of the monitoring of structures and infrastructures from environmental disasters, the COSMO-SkyMed constellation has a huge potential, thanks to up to metric spatial resolution, short revisit time, and the day/night all-weather acquisition capability ensured by SAR. This paper focuses on the scientific results of the project "Development and validation of multitemporal image analysis methodologies for multirisk monitoring of critical structures and infrastructures," funded by the Italian Space Agency. Several change-detection, data-fusion, and feature-extraction techniques, which were developed and experimentally validated in the project for COSMO-SkyMed imagery and for their integration with other data sources (including very high resolution optical data), are described and examples of processing results are discussed

Development and Validation of Multitemporal Image Analysis Methodologies for Multirisk Monitoring of Critical Structures and Infrastructures

none20S. Serpico;L. Bruzzone;G. Corsini;W. Emery;P. Gamba;A. Garzelli;G. Mercier;J. Zerubia;N. Acito;B. Aiazzi;F. Bovolo;F. Dell’Acqua;M. D. Martino;M. Diani;V. Krylov;G. Lisini;C. Marin;G. Moser;A. Voisin;C. ZoppettiS. Serpico;L. Bruzzone;G. Corsini;W. Emery;P. Gamba;A. Garzelli;G. Mercier;J. Zerubia;N. Acito;B. Aiazzi;F. Bovolo;F. Dell’Acqua;M. D. Martino;M. Diani;V. Krylov;G. Lisini;C. Marin;G. Moser;A. Voisin;C. Zoppett