scholarly journals Two decades of GPS/GNSS and DInSAR monitoring of Cardona salt mines (NE of Spain) – natural and mining-induced mechanisms and processes

2020 ◽  
Vol 382 ◽  
pp. 167-172
Author(s):  
Xavier Rodriguez-Lloveras ◽  
Carolina Puig-Polo ◽  
Nieves Lantada ◽  
Jose A. Gili ◽  
Jordi Marturià
Keyword(s):  
Spatial Distribution ◽  
Synthetic Aperture Radar ◽  
River Water ◽  
High Precision ◽  
Synthetic Aperture ◽  
Complex Processes ◽  
Differential Interferometry ◽  
Salt Mines ◽  
Mine Tunnels ◽  
Aperture Radar

Abstract. Cardona area presents surface rising and subsidence active movements. In 1999 a series of sinkholes appeared due to the infiltration of Cardener River water into the mine tunnels, damaging surface infrastructures. Since then, high precision GNSS/GPS was used annually to position a network of 40 points spread over the area. GNSS/GPS work is carried out with the Fast-Static (FS) method. Additionally the surface movements have been monitored with satellite Differential Interferometry Synthetic Aperture Radar (DInSAR). Results indicate that the movement has a complex spatial distribution although consistent along time. Some areas show surface rising during the last two decades, while other areas show subsidence. The use of the two techniques allowed to determine the most plausible causes of these movements generated by a set of interwoven natural and human-induced complex processes.

Estimation of Synthetic Aperture Radar (SAR) soil moisture with the use of fractal roughness

2021 ◽  
Author(s):  
Ju Hyoung Lee ◽  
Notarnicola Claudia ◽  
Jeff Walker
Keyword(s):  
Spatial Distribution ◽  
Soil Moisture ◽  
Synthetic Aperture Radar ◽  
Synthetic Aperture ◽  
Accurate Estimation ◽  
Distribution Data ◽  
Fractal Surface ◽  
Fractal Method ◽  
Local Point ◽  
Aperture Radar

<p>To estimate surface soil moisture from Sentinel-1 backscattering, accurate estimation of soil roughness is a key. However, it is usually error source, due to complexity of surface heterogeneity. This study investigates the fractal methods that takes multi-scale roughness into account. Fractal models are widely recognized as one of the best approaches to depict soil roughness of natural system. Unlike the conventional approach of fractal method that uses local roughness measured in the field or Digital Elevation Model information seldom considering a stochastic characteristic of soil surface, fractal surface is generated with the roughness spatially inverted from Synthetic Aperture Radar (SAR) backscatter. Assuming that the land surface in study site is on small to intermediate scales, pseudo-roughness is spatially estimated by modelling SAR roughness with the one-sided power-law spectrum. In addition, it is assumed that both multiple and single scales of roughness affect SAR backscatter in an integrative way. For validation, soil moisture is retrieved with this time-varying roughness. Based upon local validation and cost minimization, as compared with an inversion approach of surface scattering models (Integral Equation Model), a fractal method seems geometrically more sensible than an inversion, based upon a spatial distribution and a priori knowledge in the field. Although inverted roughness is used as an input, fractal model does not reproduce the same roughness. Results will show local point validation, fractal surface, and estimation of coefficients, and various spatial distribution data. This study will be useful for future satellite missions such as NASA-ISRO SAR mission.</p>

scholarly journals DESCRIPCIÓN DEL PROYECTO DE TESIS DOCTORAL: APLICACIÓN DE LA TECNOLOGIA DINSAR A LA PREVENCION DE LOS RIESGOS GEOLOGICOS NATURALES E INDUCIDOS EN CIUDADES E INFRAESTRUCTURAS PRIORITARIAS DE CENTROAMÉRICA

2021 ◽  
Author(s):  
Carlos García-Lanchares ◽  
Miguel Marchamalo ◽  
Candela Sancho
Keyword(s):  
Costa Rica ◽  
Synthetic Aperture Radar ◽  
El Salvador ◽  
Synthetic Aperture ◽  
Earth Surface ◽  
Differential Interferometry ◽  
Surface Monitoring ◽  
Aperture Radar

Este documento presenta la formulación y primeros pasos de un proyecto de Doctorado Industrial, desarrollado en elmarco del proyecto Kuk ahpán que tiene como objetivo comprender, monitorear y modelar procesos tectónicos a escalalitosférica en Centroamérica. Para ello, un equipo internacional de seis países (Nicaragua, Costa Rica, El Salvador,Guatemala, Noruega y España) trabaja integrando la investigación en diversas técnicas e ingenierías Geofísicas, con elobjetivo de actualizar los Mapas de Riesgo Sísmico de la Región, un insumo crítico. para los códigos de seguridad yconstrucción. El proyecto de doctorado propuesto se enmarca en la investigación y desarrollo de tecnologías para prevenirlos riesgos geológicos naturales e inducidos que afectan a ciudades e infraestructuras en países altamente vulnerables,utilizando la tecnología DInSAR (Differential Interferometry with Synthetic Aperture Radar) optimizada por la startupDetektia Earth Surface Monitoring en colaboración con la Universidad Politécnica de Madrid. La interferometría diferencialde radar de apertura sintética es una técnica basada en el procesamiento y análisis de series largas de imágenes de radarde apertura sintética. Esta tecnología proporciona registros (desde 1992) y movimientos actualizados en cualquiersuperficie en cualquier parte del mundo sin necesidad de instrumentación terrestre, con precisiones de alrededor de 1 mm/ año (velocidad). En este contexto, el radar satelital proporciona información valiosa sobre áreas muy grandes quecomplementan el trabajo de campo y la instrumentación in situ. Primero, comenzamos integrando datos DInSAR condiversos datos geofísicos como batimetría, geomagnetismo, gravimetría, perfiles sísmicos… para mapear completamentela falla Swan sobre Honduras y Guatemala. Usamos esta tecnología para abordar el riesgo sísmico sobre la falla y áreascercanas. En un segundo paso, aplicaremos esta evaluación de riesgo sísmico (incluyendo amenazas naturales yantropogénicas) en ciudades e infraestructuras críticas en Centroamérica.

scholarly journals High-precision, fast geolocation method for spaceborne synthetic aperture radar

2012 ◽  
Vol 57 (2-3) ◽  
pp. 287-293 ◽  
Author(s):  
QingSong Wang ◽  
HaiFeng Huang ◽  
Zhen Dong ◽  
AnXi Yu ◽  
Feng He ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
High Precision ◽  
Synthetic Aperture ◽  
Aperture Radar
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