9 resultados para Polarimetric Radar

em Universidad de Alicante


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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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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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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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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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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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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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The Huangtupo landslide is one of the largest in the Three Gorges region, China. The county-seat town of Badong, located on the south shore between the Xiling and Wu gorges of the Yangtze River, was moved to this unstable slope prior to the construction of the Three Gorges Project, since the new Three Gorges reservoir completely submerged the location of the old city. The instability of the slope is affecting the new town by causing residential safety problems. The Huangtupo landslide provides scientists an opportunity to understand landslide response to fluctuating river water level and heavy rainfall episodes, which is essential to decide upon appropriate remediation measures. Interferometric Synthetic Aperture Radar (InSAR) techniques provide a very useful tool for the study of superficial and spatially variable displacement phenomena. In this paper, three sets of radar data have been processed to investigate the Huangtupo landslide. Results show that maximum displacements are affecting the northwest zone of the slope corresponding to Riverside slumping mass I#. The other main landslide bodies (i.e. Riverside slumping mass II#, Substation landslide and Garden Spot landslide) exhibit a stable behaviour in agreement with in situ data, although some active areas have been recognized in the foot of the Substation landslide and Garden Spot landslide. InSAR has allowed us to study the kinematic behaviour of the landslide and to identify its active boundaries. Furthermore, the analysis of the InSAR displacement time-series has helped recognize the different displacement patterns on the slope and their relationships with various triggering factors. For those persistent scatterers, which exhibit long-term displacements, they can be decomposed into a creep model (controlled by geological conditions) and a superimposed recoverable term (dependent on external factors), which appears closely correlated with reservoir water level changes close to the river's edge. These results, combined with in situ data, provide a comprehensive analysis of the Huangtupo landslide, which is essential for its management.

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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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Beijing is one of the most water-stressed cities in the world. Due to over-exploitation of groundwater, the Beijing region has been suffering from land subsidence since 1935. In this study, the Small Baseline InSAR technique has been employed to process Envisat ASAR images acquired between 2003 and 2010 and TerraSAR-X stripmap images collected from 2010 to 2011 to investigate land subsidence in the Beijing region. The maximum subsidence is seen in the eastern part of Beijing with a rate greater than 100 mm/year. Comparisons between InSAR and GPS derived subsidence rates show an RMS difference of 2.94 mm/year with a mean of 2.41 ± 1.84 mm/year. In addition, a high correlation was observed between InSAR subsidence rate maps derived from two different datasets (i.e., Envisat and TerraSAR-X). These demonstrate once again that InSAR is a powerful tool for monitoring land subsidence. InSAR derived subsidence rate maps have allowed for a comprehensive spatio-temporal analysis to identify the main triggering factors of land subsidence. Some interesting relationships in terms of land subsidence were found with groundwater level, active faults, accumulated soft soil thickness and different aquifer types. Furthermore, a relationship with the distances to pumping wells was also recognized in this work.