973 resultados para Saranac Lake Region (N.Y.)--Remote-sensing maps.
Resumo:
Time-variable gravity data from the Gravity Recovery And Climate Experiment (GRACE) mission are used to study total water content over Australia for the period 2002–2010. A time-varying annual signal explains 61% of the variance of the data, in good agreement with two independent estimates of the same quantity from hydrological models. Water mass content variations across Australia are linked to Pacific and Indian Ocean variability, associated with El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), respectively. From 1989, positive (negative) IOD phases were related to anomalously low (high) precipitation in southeastern Australia, associated with a reduced (enhanced) tropical moisture flux. In particular, the sustained water mass content reduction over central and southern regions of Australia during the period 2006–2008 is associated with three consecutive positive IOD events.
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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.
Resumo:
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.
Resumo:
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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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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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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In this paper, we present a simple algorithm for assessing the validity of the RVoG model for PolInSAR-based inversion techniques. This approach makes use of two important features characterizing a homogeneous random volume over a ground surface, i.e., the independence on polarization states of wave propagation through the volume and the structure of the polarimetric interferometric coherency matrix. These two features have led to two different methods proposed in the literature for retrieving the topographic phase within natural covers, i.e., the well-known line fitting procedure and the observation of the (1, 2) element of the polarimetric interferometric coherency matrix. We show that differences between outputs from both approaches can be interpreted in terms of the PolInSAR modeling based on the Freeman-Durden concept, and this leads to the definition of a RVoG/non-RVoG test. The algorithm is tested with both indoor and airborne data over agricultural and tropical forest areas.
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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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The complete characterization of rock masses implies the acquisition of information of both, the materials which compose the rock mass and the discontinuities which divide the outcrop. Recent advances in the use of remote sensing techniques – such as Light Detection and Ranging (LiDAR) – allow the accurate and dense acquisition of 3D information that can be used for the characterization of discontinuities. This work presents a novel methodology which allows the calculation of the normal spacing of persistent and non-persistent discontinuity sets using 3D point cloud datasets considering the three dimensional relationships between clusters. This approach requires that the 3D dataset has been previously classified. This implies that discontinuity sets are previously extracted, every single point is labeled with its corresponding discontinuity set and every exposed planar surface is analytically calculated. Then, for each discontinuity set the method calculates the normal spacing between an exposed plane and its nearest one considering 3D space relationship. This link between planes is obtained calculating for every point its nearest point member of the same discontinuity set, which provides its nearest plane. This allows calculating the normal spacing for every plane. Finally, the normal spacing is calculated as the mean value of all the normal spacings for each discontinuity set. The methodology is validated through three cases of study using synthetic data and 3D laser scanning datasets. The first case illustrates the fundamentals and the performance of the proposed methodology. The second and the third cases of study correspond to two rock slopes for which datasets were acquired using a 3D laser scanner. The second case study has shown that results obtained from the traditional and the proposed approaches are reasonably similar. Nevertheless, a discrepancy between both approaches has been found when the exposed planes members of a discontinuity set were hard to identify and when the planes pairing was difficult to establish during the fieldwork campaign. The third case study also has evidenced that when the number of identified exposed planes is high, the calculated normal spacing using the proposed approach is minor than those using the traditional approach.
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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.
Resumo:
Rock mass classification systems are widely used tools for assessing the stability of rock slopes. Their calculation requires the prior quantification of several parameters during conventional fieldwork campaigns, such as the orientation of the discontinuity sets, the main properties of the existing discontinuities and the geo-mechanical characterization of the intact rock mass, which can be time-consuming and an often risky task. Conversely, the use of relatively new remote sensing data for modelling the rock mass surface by means of 3D point clouds is changing the current investigation strategies in different rock slope engineering applications. In this paper, the main practical issues affecting the application of Slope Mass Rating (SMR) for the characterization of rock slopes from 3D point clouds are reviewed, using three case studies from an end-user point of view. To this end, the SMR adjustment factors, which were calculated from different sources of information and processes, using the different softwares, are compared with those calculated using conventional fieldwork data. In the presented analysis, special attention is paid to the differences between the SMR indexes derived from the 3D point cloud and conventional field work approaches, the main factors that determine the quality of the data and some recognized practical issues. Finally, the reliability of Slope Mass Rating for the characterization of rocky slopes is highlighted.
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The Santas Justa and Rufina Gothic church (fourteenth century) has suffered several physical, mechanical, chemical, and biochemical types of pathologies along its history: rock alveolization, efflorescence, biological activity, and capillary ascent of groundwater. However, during the last two decades, a new phenomenon has seriously affected the church: ground subsidence caused by aquifer overexploitation. Subsidence is a process that affects the whole Vega Baja of the Segura River basin and consists of gradual sinking in the ground surface caused by soil consolidation due to a pore pressure decrease. This phenomenon has been studied by differential synthetic aperture radar interferometry techniques, which illustrate settlements up to 100 mm for the 1993–2009 period for the whole Orihuela city. Although no differential synthetic aperture radar interferometry information is available for the church due to the loss of interferometric coherence, the spatial analysis of nearby deformation combined with fieldwork has advanced the current understanding on the mechanisms that affect the Santas Justa and Rufina church. These results show the potential interest and the limitations of using this remote sensing technique as a complementary tool for the forensic analysis of building structures.
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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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El presente proyecto de investigacion se orienta a estudiar la disponibilidad, evolucion y variabilidad de los recursos hidricos superficiales de la region central y norte de la pcia. de Cordoba (principalmente la cuenca de aporte a la Laguna de Mar Chiquita), incluyendo además de la propia Laguna las cuencas de los ríos Dulce, Suquia y Xanaes. Esta región por ser semiarida tiene escasa disponibilidad hídrica. Esta sometida a una variable oferta natural de agua y a una demanda variada y creciente. El estudio de las variaciones y tendencias tanto de la ofertas como de las demandas por subcuencas es clave para una correcta gestión integrada de los recursos hídricos provinciales. Para el estudio propuesto se aplicarán complementariamente técnicas experimentales de laboratorio, campo y modelos númericos.