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R Lanari - One of the best experts on this subject based on the ideXlab platform.
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improved emcf sbas Processing Chain based on advanced techniques for the noise filtering and selection of small baseline multi look dinsar interferograms
IEEE Transactions on Geoscience and Remote Sensing, 2015Co-Authors: Antonio Pepe, Yang Yang, M Manzo, R LanariAbstract:We present in this paper a solution to drastically improve the deformation time-series retrieval capability of the small baseline differential SAR interferometry (DInSAR) Processing Chain based on the cascade of the extended minimum cost flow (EMCF) phase unwrapping method and of the small baseline subset (SBAS) inversion technique. This improvement relies on the inclusion of two preProcessing steps implementing an effective noise-filtering operation and an efficient interferogram selection procedure, respectively. The former step filters out the noise affecting the phase components of a redundant set of conventional multi-look small baseline interferograms. This is achieved by solving, for each pixel, a nonlinear minimization problem based on computing the wrapped phase vector that minimizes the weighted circular variance of the phase difference between the original and noise-filtered interferograms. This technique is very easy to implement because it does not require any pixel selection step to be applied to the exploited full-resolution SAR images, and it has no need of any a priori information on the statistics of the complex-valued SAR images. The latter step, implementing the interferogram selection procedure, is carried out via a computationally efficient simulated annealing algorithm and allows identifying the optimum set of previously filtered small baseline interferograms to be used as input for the original EMCF-SBAS Processing Chain by maximizing the (average) coherence values. The presented results, achieved by Processing three data sets collected by the ENVISAT ASAR sensor over the Abruzzi region (Central Italy), Mt. Etna volcano (South Italy), and Yellowstone Caldera (WY, USA), demonstrate the effectiveness of the proposed advanced EMCF-SBAS Processing Chain.
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sbas dinsar parallel Processing for deformation time series computation
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014Co-Authors: F Casu, Stefano Elefante, Pasquale Imperatore, Ivana Zinno, Michele Manunta, Claudio De Luca, R LanariAbstract:The aim of this paper is to design a novel parallel computing solution for the Processing Chain implementing the Small BAseline Subset (SBAS) Differential SAR Interferometry (DInSAR) technique. The proposed parallel solution (P-SBAS) is based on a dual-level parallelization approach and encompasses combined parallelization strategies, which are fully discussed in this paper. Moreover, the main methodological aspects of the proposed approach and their implications are also addressed. Finally, an experimental analysis, aimed at quantitatively evaluating the computational efficiency of the implemented parallel prototype, with respect to appropriate metrics, has been carried out on real data; this analysis confirms the effectiveness of the proposed parallel computing solution. In the current scenario, characterized by huge SAR archives relevant to the present and future SAR missions, the P-SBAS Processing Chain can play a key role to effectively exploit these big data volumes for the comprehension of the surface deformation dynamics of large areas of Earth.
Stephen B Heard - One of the best experts on this subject based on the ideXlab platform.
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Short-term dynamics of Processing Chain systems
Ecological Modelling, 1995Co-Authors: Stephen B HeardAbstract:Abstract A Processing Chain results when a single resource passes through a sequence of changes in condition and two (or more) consumer species specialize on resource in different stages of transformation. Each consumer species removes some resource from the total pool and may also accelerate Processing of resource to the next condition in the sequence. As a result of the tradeoff between Processing and consumption, interactions in Processing Chains may be either amensal or commensal at equilibrium. In this paper I examine short-term (transient) dynamics of Processing Chains, by considering population growth through time in a simple two-species Processing Chain model. I address interspecific interactions by comparing the performance of one species, to a given time horizon, in patches with and without the second. I examine the dependence of short-term interactions on various model parameters. The three parameters with the most influence on short-term interactions are those which largely determine interactions at equilibrium: the consumer-independent Processing rate, upstream consumer sloppiness, and upstream resource loss rate. More generally, and regardless of the details of the model, short-term Processing Chain interactions are often commensal even when the equilibrium interaction in the same system is amensal. The tendency towards commensalism is most pronounced with the shortest time horizons: all Processing Chain interactions are commensal for at least an infinitesimal interval. This tendency to short-term commensalism, combined with the non-equilibrium nature of many ecological systems and the limited duration of many experiments, may explain why literature examples of Processing Chains are nearly all commensal. I discuss the importance of temporal scale in planning and interpreting field experiments with Processing Chain systems.
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pitcher plant midges and mosquitoes a Processing Chain commensalism
Ecology, 1994Co-Authors: Stephen B HeardAbstract:Larvae of the midge Metriocnemus knabi and of the mosquito Wyeomyia smithii are found only inside the water—filled leaves of the carnivorous pitcher plant, Sarracenia purpurea, where they feed on decaying invertebrate carcasses. I examined the interaction between the two species in a natural population in western Newfoundland, Canada. Experimental manipulations of rates of prey capture by pitcher—plant leaves indicated that both insect species are limited by carcass supply. However, the interaction between them is commensal rather than competitive. Midge growth was unaffected by experimental quadrupling of mosquito density in otherwise unmanipulated leaves. Mosquito growth, on the other hand, increased with midge density in both natural leaves and artificial leaf microcosms. This interaction is an example of a Processing Chain commensalism. Although both species feed on carcass material, they use it in different stages of decay; midges feed by chewing on solid material, while mosquitoes filter—feed on particles derived from the decaying matter. Consumption of particles by mosquitoes does not affect resource availability for midges, but feeding by midges does influence particle availability. In artificial leaf microcosms, high bacterial densities occurred sooner in artificial leaves with midges present than in identical leaves without them. Bacteria are a direct food source for mosquitoes, and high bacterial densities also indicate that other organic material is being comminuted, providing particles for mosquitoes and surface area for bacterial growth. Although midges remove some of the carcass resource that also limits mosquitoes, their net effect on mosquitoes in positive because they accelerate conversion of the remaining resource to particles.
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Processing Chain Ecology: Resource Condition and Interspecific Interactions
Journal of Animal Ecology, 1994Co-Authors: Stephen B HeardAbstract:When units of a resource pass through a sequence of condition changes over time, and when some consumers specialize on resource in each condition, consumer dynamics may be coupled through their effects on the resource even though they cannot directly compete. Consumers may also influence the rate at which resource is transformed between conditions (e.g. shredders Processing leaf detritus in streams). I call such a system a Processing Chain. Although examples in which consumers influence one another through resource Processing have been recognized (if poorly documented), a general treatment of Processing Chain dynamics has not been available. I use simple compartment models to examine the population behaviour and interspecific interactions of consumers in two-species Processing Chains
Andrew Hooper - One of the best experts on this subject based on the ideXlab platform.
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Measuring Urban Subsidence in the Rome Metropolitan Area (Italy) with Sentinel-1 SNAP-StaMPS Persistent Scatterer Interferometry
Remote Sensing, 2019Co-Authors: Jose Manuel Delgado Blasco, Michael Foumelis, Chris Stewart, Andrew HooperAbstract:Land subsidence in urban environments is an increasingly prominent aspect in the monitoring and maintenance of urban infrastructures. In this study we update the subsidence information over Rome and its surroundings (already the subject of past research with other sensors) for the first time using Copernicus Sentinel-1 data and open source tools. With this aim, we have developed a fully automatic Processing Chain for land deformation monitoring using the European Space Agency (ESA) SentiNel Application Platform (SNAP) and Stanford Method for Persistent Scatterers (StaMPS). We have applied this automatic Processing Chain to more than 160 Sentinel-1A images over ascending and descending orbits to depict primarily the Line-Of-Sight ground deformation rates. Results of both geometries were then combined to compute the actual vertical motion component, which resulted in more than 2 million point targets, over their common area. Deformation measurements are in agreement with past studies over the city of Rome, identifying main subsidence areas in: (i) Fiumicino; (ii) along the Tiber River; (iii) Ostia and coastal area; (iv) Ostiense quarter; and (v) Tivoli area. Finally, post-Processing of Persistent Scatterer Inteferometry (PSI) results, in a Geographical Information System (GIS) environment, for the extraction of ground displacements on urban infrastructures (including road networks, buildings and bridges) is considered.
Jean-philippe Malet - One of the best experts on this subject based on the ideXlab platform.
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Improved co-registration of Sentinel-2 and Landsat-8 imagery for Earth surface motion measurements
Remote Sensing, 2018Co-Authors: André Stumpf, David Michea, Jean-philippe MaletAbstract:The constellation of Landsat-8 and Sentinel-2 optical satellites offers opportunities for a wide range of Earth Observation (EO) applications and scientific studies in Earth sciences mainly related to geohazards. The multi-temporal co-registration accuracy of images provided by both missions is, however, currently not fully satisfactory for change detection, time-series analysis and in particular Earth surface motion measurements. The objective of this work is the development, implementation and test of an automatic Processing Chain for correcting co-registration artefacts targeting accurate alignment of Sentinel-2 and Landsat-8 imagery for time series analysis. The method relies on dense sub-pixel offset measurements and robust statistics to correct for systematic offsets and striping artefacts. Experimental evaluation at sites with diverse environmental settings is conducted to evaluate the efficiency of the Processing Chain in comparison with previously proposed routines. The experimental evaluation suggests lower residual offsets than existing methods ranging between R M S E x y = 2.30 and 2.91 m remaining stable for longer time series. A first case study demonstrates the utility of the processor for the monitoring of continuously active landslides. A second case study demonstrates the use of the processor for measuring co-seismic surface displacements indicating an accuracy of 1/5 th of a pixel after corrections and 1/10th of a pixel after calibration with ground measurements. The implemented Processing Chain is available as an open source tool to support a better exploitation of the growing archives of Sentinel-2 and Landsat-8.
Gwenaëlle Pennober - One of the best experts on this subject based on the ideXlab platform.
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A Sentinel-1 Based Processing Chain for Detection of Cyclonic Flood Impacts
Remote Sensing, 2020Co-Authors: Cyprien Alexandre, Rosa Johary, Thibault Catry, Pascal Mouquet, Christophe Révillion, Solofo Rakotondraompiana, Gwenaëlle PennoberAbstract:In the future, climate change will induce even more severe hurricanes. Not only should these be better understood, but there is also a necessity to improve the assessment of their impacts. Flooding is one of the most common powerful impacts of these storms. Analyzing the impacts of floods is essential in order to delineate damaged areas and study the economic cost of hurricane-related floods. This paper presents an automated Processing Chain for Sentinel-1 synthetic aperture radar (SAR) data. This Processing Chain is based on the S1-Tiling algorithm and the normalized difference ratio (NDR). It is able to download and clip S1 images on Sentinel-2 tiles footprints, perform multi-temporal filtering, and threshold NDR images to produce a mask of flooded areas. Applied to two different study zones, subject to hurricanes and cyclones, this Chain is reliable and simple to implement. With the rapid mapping product of EMS Copernicus (Emergency Management Service) as reference, the method confers up to 95% accuracy and a Kappa value of 0.75.
