21 resultados para polarimetric SAR

em Universidad de Alicante


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In this paper we propose a two-component polarimetric model for soil moisture estimation on vineyards suited for C-band radar data. According to a polarimetric analysis carried out here, this scenario is made up of one dominant direct return from the soil and a multiple scattering component accounting for disturbing and nonmodeled signal fluctuations from soil and short vegetation. We propose a combined X-Bragg/Fresnel approach to characterize the polarized direct response from soil. A validation of this polarimetric model has been performed in terms of its consistency with respect to the available data both from RADARSAT-2 and from indoor measurements. High inversion rates are reported for different phenological stages of vines, and the model gives a consistent interpretation of the data as long as the volume component power remains about or below 50% of the surface contribution power. However, the scarcity of soil moisture measurements in this study prevents the validation of the algorithm in terms of the accuracy of soil moisture retrieval and an extensive campaign is required to fully demonstrate the validity of the model. Different sources of mismatches between the model and the data have been also discussed and analyzed.

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The phenological stages of onion fields in the first year of growth are estimated using polarimetric observables and single-polarization intensity channels. Experiments are undertaken on a time series of RADARSAT-2 C-band full-polarimetric synthetic aperture radar (SAR) images collected in 2009 over the Barrax region, Spain, where ground truth information about onion growth stages is provided by the European Space Agency (ESA)-funded agricultural bio/geophysical retrieval from frequent repeat pass SAR and optical imaging (AgriSAR) field campaign conducted in that area. The experimental results demonstrate that polarimetric entropy or copolar coherence when used jointly with the cross-polarized intensity allows unambiguously distinguishing three phenological intervals.

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A set of ten RADARSAT-2 images acquired in fully polarimetric mode over a test site with rice fields in Seville, Spain, has been analyzed to extract the main features of the C-band radar backscatter as a function of rice phenology. After observing the evolutions versus phenology of different polarimetric observables and explaining their behavior in terms of scattering mechanisms present in the scene, a simple retrieval approach has been proposed. This algorithm is based on three polarimetric observables and provides estimates from a set of four relevant intervals of phenological stages. The validation against ground data, carried out at parcel level for a set of six stands and up to nine dates per stand, provides a 96% rate of coincidence. Moreover, an equivalent compact-pol retrieval algorithm has been also proposed and validated, providing the same performance at parcel level. In all cases, the inversion is carried out by exploiting a single satellite acquisition, without any other auxiliary information.

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Ground subsidence caused by aquifer exploitation is a geotechnical hazard that affects wide areas, causing important economic damages. This phenomenon is due to soil consolidation produced by the increase of effective stress caused by piezometric depletion. In this work a Remote Sensing Technique called Coherent Pixel (CPT) is applied to monitor subsidence in the Vega Media of the Segura River during a period of eleven years.

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Surface displacement at the dykes of La Pedrera reservoir (SE Spain) has been measured by satellite differential Synthetic Aperture Radar (SAR) interferometry. At the main dyke, a displacement of about 13 cm along the satellite line of sight has been estimated between August 1995 and May 2010, from a dataset composed by ERS-1, ERS-2 and Envisat-ASAR images. Two independent short-term processing tasks were also carried out with ERS-2/Envisat-ASAR (from June 2008 to May 2010) and TerraSAR-X (from August 2008 to June 2010) images which have shown similar spatial and temporal displacement patterns. The joint analysis of historical instrument surveys and DInSAR-derived data has allowed the identification of a long-term deformation process which is reflected at the dam's surface and is also clearly recognizable in the inspection gallery. The plausible causes of the displacements measured by DInSAR are also discussed in the paper. Finally, DInSAR data have been used to compute the long-term settlement of La Pedrera dam, showing a good agreement with external studies. Consequently, this work demonstrates the integration of DInSAR with in-situ techniques which helps provide a complete spatial vision of the displacements in the dam thereby helping to differentiate the causal mechanisms.

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Information of crop phenology is essential for evaluating crop productivity. In a previous work, we determined phenological stages with remote sensing data using a dynamic system framework and an extended Kalman filter (EKF) approach. In this paper, we demonstrate that the particle filter is a more reliable method to infer any phenological stage compared to the EKF. The improvements achieved with this approach are discussed. In addition, this methodology enables the estimation of key cultivation dates, thus providing a practical product for many applications. The dates of some important stages, as the sowing date and the day when the crop reaches the panicle initiation stage, have been chosen to show the potential of this technique.

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In this paper, a novel approach for exploiting multitemporal remote sensing data focused on real-time monitoring of agricultural crops is presented. The methodology is defined in a dynamical system context using state-space techniques, which enables the possibility of merging past temporal information with an update for each new acquisition. The dynamic system context allows us to exploit classical tools in this domain to perform the estimation of relevant variables. A general methodology is proposed, and a particular instance is defined in this study based on polarimetric radar data to track the phenological stages of a set of crops. A model generation from empirical data through principal component analysis is presented, and an extended Kalman filter is adapted to perform phenological stage estimation. Results employing quad-pol Radarsat-2 data over three different cereals are analyzed. The potential of this methodology to retrieve vegetation variables in real time is shown.

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The coherent nature of the acquisition by TerraSAR-X of both copolar channels (HH and VV) enables the generation of many different polarimetric observables with physical interpretation, as have recently been used for monitoring rice fields. In this letter, the influence of incidence angle upon these polarimetric observables is analyzed by comparing three stacks of images that were acquired simultaneously at different incidence angles (22°, 30°, and 40°) during a whole cultivation campaign. We show that the response of observables related to dominance (entropy, ratios of components) and type of scattering mechanisms (alpha angles) is not greatly influenced by incidence angle at some stages: early and advanced vegetative phases, and maturation. Moreover, the acquisition geometry drives the sensitivity to the presence of the initial stems and tillers, being detected earlier at shallower angles. This analysis is a necessary step before studying potential methodologies for combining different orbits and beams for reducing the time between acquisitions for monitoring purposes.

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In this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.

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Subsidence is a natural hazard that affects wide areas in the world causing important economic costs annually. This phenomenon has occurred in the metropolitan area of Murcia City (SE Spain) as a result of groundwater overexploitation. In this work aquifer system subsidence is investigated using an advanced differential SAR interferometry remote sensing technique (A-DInSAR) called Stable Point Network (SPN). The SPN derived displacement results, mainly the velocity displacement maps and the time series of the displacement, reveal that in the period 2004–2008 the rate of subsidence in Murcia metropolitan area doubled with respect to the previous period from 1995 to 2005. The acceleration of the deformation phenomenon is explained by the drought period started in 2006. The comparison of the temporal evolution of the displacements measured with the extensometers and the SPN technique shows an average absolute error of 3.9±3.8 mm. Finally, results from a finite element model developed to simulate the recorded time history subsidence from known water table height changes compares well with the SPN displacement time series estimations. This result demonstrates the potential of A-DInSAR techniques to validate subsidence prediction models as an alternative to using instrumental ground based techniques for validation.

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Differential SAR Interferometry (DInSAR) is a remote sensing method with the well demonstrated ability to monitor geological hazards like earthquakes, landslides and subsidence. Among all these hazards, subsidence involves the settlement of the ground surface affecting wide areas. Frequently, subsidence is induced by overexploitation of aquifers and constitutes a common problem that affects developed societies. The excessive pumping of underground water decreases the piezometric level in the subsoil and, as a consequence, increases the effective stresses with depth causing a consolidation of the soil column. This consolidation originates a settlement of ground surface that must be withstood by civil structures built on these areas. In this paper we make use of an advanced DInSAR approach - the Coherent Pixels Technique (CPT) [1] - to monitor subsidence induced by aquifer overexploitation in the Vega Media of the Segura River (SE Spain) from 1993 to the present. 28 ERS-1/2 scenes covering a time interval of about 10 years were used to study this phenomenon. The deformation map retrieved with CPT technique shows settlements of up to 80 mm at some points of the studied zone. These values agree with data obtained by means of borehole extensometers, but not with the distribution of damaged buildings, well points and basements, because the occurrence of damages also depends on the structural quality of the buildings and their foundations. The most interesting relationship observed is the one existing between piezometric changes, settlement evolution and local geology. Three main patterns of ground surface and piezometric level behaviour have been distinguished for the study zone during this period: 1) areas where deformation occurs while ground conditions remain altered (recent deformable sediments), 2) areas with no deformation (old and non-deformable materials), and 3) areas where ground deformation mimics piezometric level changes (expansive soils). The temporal relationship between deformation patterns and soil characteristics has been analysed in this work, showing a delay between them. Moreover, this technique has allowed the measurement of ground subsidence for a period (1993-1995) where no instrument information was available.

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En este trabajo se presentan los sistemas radar satélite y terrestres, así como los métodos de análisis de imágenes radar clásicos y avanzados para la investigación de los movimientos del terreno, haciendo énfasis en la subsidencia y los movimientos de ladera. Para ello en primer lugar se describen los distintos sensores radar disponibles así como las principales características de las imágenes radar generadas. A continuación se detallan los aspectos fundamentales de la interferometría diferencial, de los distintos métodos de interferometría diferencial avanzada y del radar terrestre. Finalmente se presentan los resultados obtenidos en distintas zonas de estudio: la subsidencia por explotación del acuífero en el área metropolitana de Murcia, la subsidencia minera y los movimientos de ladera de la Sierra de Cartagena, los movimientos de ladera de la cuenca del río Gállego y el deslizamiento del Portalet.

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Subsidence related to multiple natural and human-induced processes affects an increasing number of areas worldwide. Although this phenomenon may involve surface deformation with 3D displacement components, negative vertical movement, either progressive or episodic, tends to dominate. Over the last decades, differential SAR interferometry (DInSAR) has become a very useful remote sensing tool for accurately measuring the spatial and temporal evolution of surface displacements over broad areas. This work discusses the main advantages and limitations of addressing active subsidence phenomena by means of DInSAR techniques from an end-user point of view. Special attention is paid to the spatial and temporal resolution, the precision of the measurements, and the usefulness of the data. The presented analysis is focused on DInSAR results exploitation of various ground subsidence phenomena (groundwater withdrawal, soil compaction, mining subsidence, evaporite dissolution subsidence, and volcanic deformation) with different displacement patterns in a selection of subsidence areas in Spain. Finally, a cost comparative study is performed for the different techniques applied.

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In this letter, a new approach for crop phenology estimation with remote sensing is presented. The proposed methodology is aimed to exploit tools from a dynamical system context. From a temporal sequence of images, a geometrical model is derived, which allows us to translate this temporal domain into the estimation problem. The evolution model in state space is obtained through dimensional reduction by a principal component analysis, defining the state variables, of the observations. Then, estimation is achieved by combining the generated model with actual samples in an optimal way using a Kalman filter. As a proof of concept, an example with results obtained with this approach over rice fields by exploiting stacks of TerraSAR-X dual polarization images is shown.

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En las últimas décadas diversas técnicas basadas en teledetección mediante sistemas de microondas han servido para aumentar el conocimiento de la superficie terrestre. En concreto, los sistemas basados en Radar de Apertura Sintética (SAR) han demostrado ser una herramienta con un gran potencial en la monitorización de cultivos y de gran ayuda a las técnicas de cultivo de precisión (Precision Farming). En la actualidad existen técnicas de clasificación de cultivos basadas en adquisiciones SAR que permiten con elevada precisión determinar la cobertura espacial de diferentes cultivos sin embargo la estimación de parámetros biofísicos resulta más compleja con estas técnicas. Recientemente diversas estrategias han sido propuestas con el objetivo de determinar el estado de un cultivo, el estado fenológico, en un determinado instante basándose en el análisis de las características de las imágenes SAR polarimétricas (PolSAR). Estas primeras aproximaciones todavía se encuentran en una etapa de desarrollo temprana y por tanto es posible profundizar y analizar las diferentes alternativas a partir de ellas de manera que podamos obtener resultados más precisos y que puedan aportar información de valor añadido a las técnicas de cultivo de precisión. En este trabajo abordaremos la alternativa de aprovechar las series de imágenes SAR obtenidas en diferentes instantes en el ciclo de un cultivo para determinar el estado fenológico de un cultivo.