An approach to multi-temporal MODIS image analysis using image classification and segmentation

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time series analysis of satellite images utilizing pixel spectral information for image classification and region-based segmentation for extracting water-covered regions. Analysis of MODIS satellite images is applied in three stages: before flood, during flood and after flood. Water regions are extracted from the MODIS images using image classification (based on spectral information) and image segmentation (based on spatial information). Multi-temporal MODIS images from ``normal'' (non-flood) and flood time-periods are processed in two steps. In the first step, image classifiers such as Support Vector Machines (SVMs) and Artificial Neural Networks (ANNs) separate the image pixels into water and non-water groups based on their spectral features. The classified image is then segmented using spatial features of the water pixels to remove the misclassified water. From the results obtained, we evaluate the performance of the method and conclude that the use of image classification (SVM and ANN) and region-based image segmentation is an accurate and reliable approach for the extraction of water-covered regions. (c) 2012 COSPAR. Published by Elsevier Ltd. All rights reserved.

Spectral-spatial MODIS image analysis using swarm intelligence algorithms and region based segmentation for flood assessment

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time-series analysis of satellite images utilizing pixel spectral information for image clustering and region based segmentation for extracting water covered regions. MODIS satellite images are analyzed at two stages: before flood and during flood. Multi-temporal MODIS images are processed in two steps. In the first step, clustering algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to distinguish the water regions from the non-water based on spectral information. These algorithms are chosen since they are quite efficient in solving multi-modal optimization problems. These classified images are then segmented using spatial features of the water region to extract the river. From the results obtained, we evaluate the performance of the methods and conclude that incorporating region based image segmentation along with clustering algorithms provides accurate and reliable approach for the extraction of water covered region.

Multi-Temporal Satellite Image Analysis Using Gene Expression Programming

This paper discusses an approach for river mapping and flood evaluation to aid multi-temporal time series analysis of satellite images utilizing pixel spectral information for image classification and region-based segmentation to extract water covered region. Analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images is applied in two stages: before flood and during flood. For these images the extraction of water region utilizes spectral information for image classification and spatial information for image segmentation. Multi-temporal MODIS images from ``normal'' (non-flood) and flood time-periods are processed in two steps. In the first step, image classifiers such as artificial neural networks and gene expression programming to separate the image pixels into water and non-water groups based on their spectral features. The classified image is then segmented using spatial features of the water pixels to remove the misclassified water region. From the results obtained, we evaluate the performance of the method and conclude that the use of image classification and region-based segmentation is an accurate and reliable for the extraction of water-covered region.

A Comparison of Machine Learning Techniques for Modeling River Flow Time Series: The Case of Upper Cauvery River Basin

Models of river flow time series are essential in efficient management of a river basin. It helps policy makers in developing efficient water utilization strategies to maximize the utility of scarce water resource. Time series analysis has been used extensively for modeling river flow data. The use of machine learning techniques such as support-vector regression and neural network models is gaining increasing popularity. In this paper we compare the performance of these techniques by applying it to a long-term time-series data of the inflows into the Krishnaraja Sagar reservoir (KRS) from three tributaries of the river Cauvery. In this study flow data over a period of 30 years from three different observation points established in upper Cauvery river sub-basin is analyzed to estimate their contribution to KRS. Specifically, ANN model uses a multi-layer feed forward network trained with a back-propagation algorithm and support vector regression with epsilon intensive-loss function is used. Auto-regressive moving average models are also applied to the same data. The performance of different techniques is compared using performance metrics such as root mean squared error (RMSE), correlation, normalized root mean squared error (NRMSE) and Nash-Sutcliffe Efficiency (NSE).

Modeling non-stationarity in intensity, duration and frequency of extreme rainfall over India

Significant changes are reported in extreme rainfall characteristics over India in recent studies though there are disagreements on the spatial uniformity and causes of trends. Based on recent theoretical advancements in the Extreme Value Theory (EVT), we analyze changes in extreme rainfall characteristics over India using a high-resolution daily gridded (1 degrees latitude x 1 degrees longitude) dataset. Intensity, duration and frequency of excess rain over a high threshold in the summer monsoon season are modeled by non-stationary distributions whose parameters vary with physical covariates like the El-Nino Southern Oscillation index (ENSO-index) which is an indicator of large-scale natural variability, global average temperature which is an indicator of human-induced global warming and local mean temperatures which possibly indicate more localized changes. Each non-stationary model considers one physical covariate and the best chosen statistical model at each rainfall grid gives the most significant physical driver for each extreme rainfall characteristic at that grid. Intensity, duration and frequency of extreme rainfall exhibit non-stationarity due to different drivers and no spatially uniform pattern is observed in the changes in them across the country. At most of the locations, duration of extreme rainfall spells is found to be stationary, while non-stationary associations between intensity and frequency and local changes in temperature are detected at a large number of locations. This study presents the first application of nonstationary statistical modeling of intensity, duration and frequency of extreme rainfall over India. The developed models are further used for rainfall frequency analysis to show changes in the 100-year extreme rainfall event. Our findings indicate the varying nature of each extreme rainfall characteristic and their drivers and emphasize the necessity of a comprehensive framework to assess resulting risks of precipitation induced flooding. (C) 2014 Elsevier B.V. All rights reserved.

The motion and the core structure of a geostrophic vortex - one-time scale inner solution and the motion of the vortex

By means of the matched asymptotic expansion method with one-time scale analysis we have shown that the inviscid geostrophic vortex solution represents our leading solution away from the vortex. Near the vortex there is a viscous core structure, with the length scale O(a). In the core the viscous stresses (or turbulent stresses) are important, the variations of the velocity and the equivalent height are finite and dependent of time. It also has been shown that the leading inner solutions of the core structure are the same for two different time scales of S/(ghoo)1/2 and S/a (ghoo)1/2. Within the accuracy of O(a) the velocity of a geostrophic vortex center is equal to the velocity of the local background flow, where the vortex is located, in the absence of the vortex. Some numerical examples demonstrate the contributions of these results.

New signal processing algorithms for automated external defibrillators

[ES]La fibrilación ventricular (VF) es el primer ritmo registrado en el 40\,\% de las muertes súbitas por paro cardiorrespiratorio extrahospitalario (PCRE). El único tratamiento eficaz para la FV es la desfibrilación mediante una descarga eléctrica. Fuera del hospital, la descarga se administra mediante un desfibrilador externo automático (DEA), que previamente analiza el electrocardiograma (ECG) del paciente y comprueba si presenta un ritmo desfibrilable. La supervivencia en un caso de PCRE depende fundamentalmente de dos factores: la desfibrilación temprana y la resucitación cardiopulmonar (RCP) temprana, que prolonga la FV y por lo tanto la oportunidad de desfibrilación. Para un correcto análisis del ritmo cardiaco es necesario interrumpir la RCP, ya que, debido a las compresiones torácicas, la RCP introduce artefactos en el ECG. Desafortunadamente, la interrupción de la RCP afecta negativamente al éxito en la desfibrilación. En 2003 se aprobó el uso del DEA en pacientes entre 1 y 8 años. Los DEA, que originalmente se diseñaron para pacientes adultos, deben discriminar de forma precisa las arritmias pediátricas para que su uso en niños sea seguro. Varios DEAs se han adaptado para uso pediátrico, bien demostrando la precisión de los algoritmos para adultos con arritmias pediátricas, o bien mediante algoritmos específicos para arritmias pediátricas. Esta tesis presenta un nuevo algoritmo DEA diseñado conjuntamente para pacientes adultos y pediátricos. El algoritmo se ha probado exhaustivamente en bases de datos acordes a los requisitos de la American Heart Association (AHA), y en registros de resucitación con y sin artefacto RCP. El trabajo comenzó con una larga fase experimental en la que se recopilaron y clasificaron retrospectivamente un total de 1090 ritmos pediátricos. Además, se revisó una base de arritmias de adultos y se añadieron 928 nuevos ritmos de adultos. La base de datos final contiene 2782 registros, 1270 se usaron para diseñar el algoritmo y 1512 para validarlo. A continuación, se diseñó un nuevo algoritmo DEA compuesto de cuatro subalgoritmos. Estos subalgoritmos están basados en un conjunto de nuevos parámetros para la detección de arritmias, calculados en diversos dominios de la señal, como el tiempo, la frecuencia, la pendiente o la función de autocorrelación. El algoritmo cumple las exigencias de la AHA para la detección de ritmos desfibrilables y no-desfibrilables tanto en pacientes adultos como en pediátricos. El trabajo concluyó con el análisis del comportamiento del algoritmo con episodios reales de resucitación. En los ritmos que no contenían artefacto RCP se cumplieron las exigencias de la AHA. Posteriormente, se estudió la precisión del algoritmo durante las compresiones torácicas, antes y después de filtrar el artefacto RCP. Para suprimir el artefacto se utilizó un nuevo método desarrollado a lo largo de la tesis. Los ritmos desfibrilables se detectaron de forma precisa tras el filtrado, los no-desfibrilables sin embargo no.

Time-resolved investigation of low-density plasma channels produced by a kilohertz femtosecond laser in air

By employing pump-probe back longitudinal diffractometry, the electron density and decay dynamics of a weak plasma channel created by a 1-KHz fs laser in air has been investigated. With ultrashort laser pulses of 50 fs and low energy of 0.6 mJ, we observe weak plasma channels with a length similar to 2 cm in air. An analytical reconstruction method of electron density has been analyzed, which is sensitive to the phase shift and channel size. The electron density in the weak plasma channel is extracted to be about 4x10(16) cm(-3). The diameters of the plasma channel and the filament are about 50 and 150 mu m, respectively, and the measurable electron density can be extended to less than 10(15) cm(-3). Moreover, a different time-frequency technique called linearly chirped longitudinal diffractometry is proposed to time-resolved investigate ultrafast ionization dynamics of laser-irradiated gas, laser interaction with cluster beam, etc.

Contributions to time series data mining departing from the problem of road travel time modeling

194 p.

Um esquema de Fourier local para análise tempo-frequência de sinais não-estacionários aplicado a ruído eletroquímico

Sinais diversos estão presentes em nosso cotidiano, assim como nas medidas realizadas nas atividades de ciência e tecnologia. Dentre estes sinais, tem grande importância tecnológica aqueles associados à corrosão de estruturas metálicas. Assim, esta tese propõe o estudo de um esquema local de transformada de Fourier janelada, com a janela variando em função da curtose, aplicada a sinais de ruído eletroquímico. A curtose foi avaliada nos domínios do tempo e da frequência e processada pelo programa desenvolvido para esse fim. O esquema foi aplicado a sinais de ruído eletroquímico dos aços UNS S31600, UNS G10200 e UNS S32750 imersos em três soluções: FeCl3 0,1 mol=L (cloreto férrico), H2SO4 5%(ácido sulfúrico) e NaOH 0,1%(hidróxido de sódio). Para os aços inoxidáveis, estas soluções promovem corrosão localizada, uniforme e passivação, respectivamente. Visando testar o desempenho do esquema de Fourier desenvolvido, testes foram realizados utilizando-se inicialmente sinais sintéticos e em seguida sinais de ruído eletroquímico. Notou-se que os sinais têm características de não-estacionaridade e a maior parte da energia está presente em baixa frequência. Os intervalos de tempo e de frequência onde se concentra a maior parte da energia do sinal foram correlacionados. Para os picos máximos dos sinais de potencial e corrente obtidos de amperimetria de resistência nula, a correlação entre eles foi baixa, independente da forma de corrosão presente. Conclui-se que o método se adaptou bastante bem às características locais do sinal eletroquímico permitindo o monitoramento dos espectros tempo-frequência. O fato de ser sensível às características locais do sinal permite analisar aspectos dos sinais que do modo clássico não podem ser diretamente processados. O método da transformada de Fourier janelada variável (Variable Short-Time Fourier Transform - VSTFT) adaptou-se muito bem no monitoramento dos sinais originados de potencial de circuito aberto e amperimetria de resistência nula.

Análise de critérios para definição da vazão remanescente em usinas hidrelétricas.

Tem crescido a demanda por energia em todo o mundo. No Brasil, com o aquecimento da economia aumentam ainda mais as pressões. O parque gerador Brasileiro é fortemente baseado na geração hidrelétrica, que representa aproximadamente 77,6% da oferta de geração de eletricidade. Entre os impactos ambientais gerados pela construção de barragens e reservatórios de aproveitamentos hidrelétricos está a mudança do regime fluvial de jusante, a chamada vazão remanescente. Entre outros, esta vazão deve garantir as condições adequadas à sobrevivência e continuação das espécies e dos ecossistemas, associando as necessidades humanas, ambientais e as características de cada região. Tomou-se como objeto de análise dois estudos de caso, a pequena central hidrelétrica (PCH) Santa Gabriela, localizada no rio Correntes, na divisa entre os estados de Mato Grosso e Mato Grosso do Sul e a usina hidrelétrica (UHE) Batalha, situada no rio São Marcos, na divisa entre os estados de Minas Gerais e Goiás. Embora o assunto seja discutido amplamente pela comunidade técnica e acadêmica, não há ainda nos marcos legais Brasileiros associados, uma definição explícita de critérios ou limites para estabelecimento da vazão remanescente. Em geral, as legislações estaduais estabelecem valores máximos outorgáveis determinados a partir de percentuais da curva de permanência (Q90, Q95) ou da vazão mínima anual de sete dias de duração e tempo de recorrência de 10 anos Q7,10, garantindo consequentemente as vazões mínimas remanescentes. Essas metodologias implicam num único valor fixo para a vazão ao longo do ano, o que não condiz com a realidade do regime hidrológico natural. Estudos atuais apontam para um hidrograma ecológico, que represente a variação das vazões entre os meses de estiagem e cheia. Assim, a metodologia envolveu a comparação entre critérios de outorga utilizados em alguns estados Q90, Q95 e Q7,10 e métodos citados na literatura para estudo da vazão ecológica (Tennant, Texas, Vazão Base e Perímetro Molhado) e as Resoluções referentes à Declaração de Reserva de Disponibilidade Hídrica (DRDH) das usinas, que especificam a vazão remanescente nas fases de enchimento e operação, emitidas pela Agência Nacional de Águas (ANA). Observaram-se valores de vazões substancialmente diferenciados entre os seis métodos empregados. Cabe destacar, que representa um avanço a publicação do Manual de Estudos de Disponibilidade Hídrica para Aproveitamentos Hidrelétricos (ANA, 2009), que visa à padronização dos documentos para fins obtenção da DRDH e da outorga do uso do potencial de energia hidráulica em corpo de água de domínio da União. Assim, o empreendedor poderá propor e negociar a demanda hídrica para as necessidades ambientais com as autoridades competentes, o que deverá ser discutido em reunião técnica inicial que deverá contar com a participação da Agência Nacional de Energia Elétrica (ANEEL), ANA, órgão ambiental, empreendedor e a empresa responsável pelos estudos ambientais.

Climatic effects on flood frequency: an example from southern Arizona

EXTRACT (SEE PDF FOR FULL ABSTRACT): After 1960, the Santa Cruz River at Tucson, Arizona, an ephemeral stream normally dominated by summer floods, experienced an apparent increased frequency of flooding coincident with an increased percentage of annual floods occurring in fall and winter. This shift reflects large-scale and low-frequency changes in the eastern Pacific Ocean, in part associated with El Niño-Southern Oscillation (ENSO) phenomena. ... Questions are raised about the validity of standard methods of flood-frequency analysis to estimate regulatory and designed floods.

Predicting shock response in uncertain structures using the Hybrid method

Using the Hybrid method (FE + SEA) it is possible to estimate the frequency response of an uncertain structure. The current work develops the Hybrid method to allow for time domain analysis of the shock response of a structure. Problems to be overcome when taking Hybrid method results into the time domain are a) the Hybrid method frequency response has no phase information, and b) the Hybrid method frequency response is smoothed in frequency and shows no modal peaks. In this paper the first problem has been overcome, using minimum phase reconstruction. Explanation of minimum phase reconstruction and its limitations are described, and application to shock problems described. © 2009 IOP Publishing Ltd.

Modelling and Fragility Analysis of Non-Ductile Reinforced Concrete Buildings in Low-to-Moderate Seismic Zones

Reinforced concrete buildings in low-to-moderate seismic zones are often designed only for gravity loads in accordance with the non-seismic detailing provisions. Deficient detailing of columns and beam-column joints can lead to unpredictable brittle failures even under moderate earthquakes. Therefore, a reliable estimate of structural response is required for the seismic evaluation of these structures. For this purpose, analytical models for both interior and exterior slab-beam-column subassemblages and for a 1/3 scale model frame were implemented into the nonlinear finite element platform OpenSees. Comparison between the analytical results and experimental data available in the literature is carried out using nonlinear pushover analyses and nonlinear time history analysis for the subassemblages and the model frame, respectively. Furthermore, the seismic fragility assessment of reinforced concrete buildings is performed on a set of non-ductile frames using nonlinear time history analyses. The fragility curves, which are developed for various damage states for the maximum interstory drift ratio are characterized in terms of peak ground acceleration and spectral acceleration using a suite of ground motions representative of the seismic hazard in the region.

Probabilistic Amplitude Demodulation

Auditory scene analysis is extremely challenging. One approach, perhaps that adopted by the brain, is to shape useful representations of sounds on prior knowledge about their statistical structure. For example, sounds with harmonic sections are common and so time-frequency representations are efficient. Most current representations concentrate on the shorter components. Here, we propose representations for structures on longer time-scales, like the phonemes and sentences of speech. We decompose a sound into a product of processes, each with its own characteristic time-scale. This demodulation cascade relates to classical amplitude demodulation, but traditional algorithms fail to realise the representation fully. A new approach, probabilistic amplitude demodulation, is shown to out-perform the established methods, and to easily extend to representation of a full demodulation cascade.