Comparative Assessment of Techniques for Bioresource Monitoring Using GIS and Remote Sensing

Growing concern over the status of global and regional bioenergy resources has necessitated the analysis and monitoring of land cover and land use parameters on spatial and temporal scales. The knowledge of land cover and land use is very important in understanding natural resources utilization, conversion and management. Land cover, land use intensity and land use diversity are land quality indicators for sustainable land management. Optimal management of resources aids in maintaining the ecosystem balance and thereby ensures the sustainable development of a region. Thus sustainable development of a region requires a synoptic ecosystem approach in the management of natural resources that relates to the dynamics of natural variability and the effects of human intervention on key indicators of biodiversity and productivity. Spatial and temporal tools such as remote sensing (RS), geographic information system (GIS) and global positioning system (GPS) provide spatial and attribute data at regular intervals with functionalities of a decision support system aid in visualisation, querying, analysis, etc., which would aid in sustainable management of natural resources. Remote sensing data and GIS technologies play an important role in spatially evaluating bioresource availability and demand. This paper explores various land cover and land use techniques that could be used for bioresources monitoring considering the spatial data of Kolar district, Karnataka state, India. Slope and distance based vegetation indices are computed for qualitative and quantitative assessment of land cover using remote spectral measurements. Differentscale mapping of land use pattern in Kolar district is done using supervised classification approaches. Slope based vegetation indices show area under vegetation range from 47.65 % to 49.05% while distance based vegetation indices shoes its range from 40.40% to 47.41%. Land use analyses using maximum likelihood classifier indicate that 46.69% is agricultural land, 42.33% is wasteland (barren land), 4.62% is built up, 3.07% of plantation, 2.77% natural forest and 0.53% water bodies. The comparative analysis of various classifiers, indicate that the Gaussian maximum likelihood classifier has least errors. The computation of talukwise bioresource status shows that Chikballapur Taluk has better availability of resources compared to other taluks in the district.

Vegetation Analysis in Uttara Kannada District Using GIS and Remote Sensing Techniques

Uttara Kannada is the only district in Karnataka, which has a forested area of about 80% and falls in the region of the Western Ghats. It is considered to be a very resourceful in terms of abundant natural resources and constitutes an important district in Karnataka. The forest resources of the district are under pressure as a large portion of the forested area has been converted to non-forestry activities since independence owing to the increased demands from human and animal population resulting in degradation of the forest ecosystem. This has led to poor productivity and regenerative capacity which is evident in the form of barren hill tops, etc in Coastal taluks of Uttara Kannada, entailing regular monitoring of the forest resources very essential. The classification of forest is a prerequisite for managing forest resources. Geographical Information System (GIS), allows the spatial and temporal analysis of the features of interest, and helps in solving the problem of deforestation and associated environmental and ecological problems. Spatial and temporal tools such as GIS and remotely sensed data helps the planners and decision makers in evolving the sustainable strategies for management and conservation of natural resources. Uttara Kannada district was classified on the basis of the land-use using supervised hard classifiers. The land use categories identified were urban area, water bodies, agricultural land, forest cover, and waste land. Further classification was carried out on the basis of forest type. The types of forest categorised were semi-evergreen, evergreen, moist deciduous, dry deciduous, plantations and scrub, thorny and non-forested area. The identified classes were correlated with the ground data collected during field visits. The observed results were compared with the historic data and the changes in the forest cover were analysed. From the assessment made it was clear that there has been a considerable degree of forest loss in certain areas of the district. It was also observed that plantations and social forests have increased drastically over the last fifteen years,and natural forests have declined.

A survey of temporal data mining

Data mining is concerned with analysing large volumes of (often unstructured) data to automatically discover interesting regularities or relationships which in turn lead to better understanding of the underlying processes. The field of temporal data mining is concerned with such analysis in the case of ordered data streams with temporal interdependencies. Over the last decade many interesting techniques of temporal data mining were proposed and shown to be useful in many applications. Since temporal data mining brings together techniques from different fields such as statistics, machine learning and databases, the literature is scattered among many different sources. In this article, we present an overview of techniques of temporal data mining.We mainly concentrate on algorithms for pattern discovery in sequential data streams.We also describe some recent results regarding statistical analysis of pattern discovery methods.

Uncertainty visualization using HDR volume rendering

In this paper, we explore a novel idea of using high dynamic range (HDR) technology for uncertainty visualization. We focus on scalar volumetric data sets where every data point is associated with scalar uncertainty. We design a transfer function that maps each data point to a color in HDR space. The luminance component of the color is exploited to capture uncertainty. We modify existing tone mapping techniques and suitably integrate them with volume ray casting to obtain a low dynamic range (LDR) image. The resulting image is displayed on a conventional 8-bits-per-channel display device. The usage of HDR mapping reveals fine details in uncertainty distribution and enables the users to interactively study the data in the context of corresponding uncertainty information. We demonstrate the utility of our method and evaluate the results using data sets from ocean modeling.

Efficient asynchronous executions of AMR computations and visualization on a GPU system

Adaptive Mesh Refinement is a method which dynamically varies the spatio-temporal resolution of localized mesh regions in numerical simulations, based on the strength of the solution features. In-situ visualization plays an important role for analyzing the time evolving characteristics of the domain structures. Continuous visualization of the output data for various timesteps results in a better study of the underlying domain and the model used for simulating the domain. In this paper, we develop strategies for continuous online visualization of time evolving data for AMR applications executed on GPUs. We reorder the meshes for computations on the GPU based on the users input related to the subdomain that he wants to visualize. This makes the data available for visualization at a faster rate. We then perform asynchronous executions of the visualization steps and fix-up operations on the CPUs while the GPU advances the solution. By performing experiments on Tesla S1070 and Fermi C2070 clusters, we found that our strategies result in 60% improvement in response time and 16% improvement in the rate of visualization of frames over the existing strategy of performing fix-ups and visualization at the end of the timesteps.

Scalar field visualization via extraction of symmetric structures

Identifying symmetry in scalar fields is a recent area of research in scientific visualization and computer graphics communities. Symmetry detection techniques based on abstract representations of the scalar field use only limited geometric information in their analysis. Hence they may not be suited for applications that study the geometric properties of the regions in the domain. On the other hand, methods that accumulate local evidence of symmetry through a voting procedure have been successfully used for detecting geometric symmetry in shapes. We extend such a technique to scalar fields and use it to detect geometrically symmetric regions in synthetic as well as real-world datasets. Identifying symmetry in the scalar field can significantly improve visualization and interactive exploration of the data. We demonstrate different applications of the symmetry detection method to scientific visualization: query-based exploration of scalar fields, linked selection in symmetric regions for interactive visualization, and classification of geometrically symmetric regions and its application to anomaly detection.

High speed digital holographic interferometry for hypersonic flow visualization

Optical imaging techniques have played a major role in understanding the flow dynamics of varieties of fluid flows, particularly in the study of hypersonic flows. Schlieren and shadowgraph techniques have been the flow diagnostic tools for the investigation of compressible flows since more than a century. However these techniques provide only the qualitative information about the flow field. Other optical techniques such as holographic interferometry and laser induced fluorescence (LIF) have been used extensively for extracting quantitative information about the high speed flows. In this paper we present the application of digital holographic interferometry (DHI) technique integrated with short duration hypersonic shock tunnel facility having 1 ms test time, for quantitative flow visualization. Dynamics of the flow fields in hypersonic/supersonic speeds around different test models is visualized with DHI using a high-speed digital camera (0.2 million fps). These visualization results are compared with schlieren visualization and CFD simulation results. Fringe analysis is carried out to estimate the density of the flow field.

An exploration framework to identify and track movement of cloud systems

We describe a framework to explore and visualize the movement of cloud systems. Using techniques from computational topology and computer vision, our framework allows the user to study this movement at various scales in space and time. Such movements could have large temporal and spatial scales such as the Madden Julian Oscillation (MJO), which has a spatial scale ranging from 1000 km to 10000 km and time of oscillation of around 40 days. Embedded within these larger scale oscillations are a hierarchy of cloud clusters which could have smaller spatial and temporal scales such as the Nakazawa cloud clusters. These smaller cloud clusters, while being part of the equatorial MJO, sometimes move at speeds different from the larger scale and in a direction opposite to that of the MJO envelope. Hitherto, one could only speculate about such movements by selectively analysing data and a priori knowledge of such systems. Our framework automatically delineates such cloud clusters and does not depend on the prior experience of the user to define cloud clusters. Analysis using our framework also shows that most tropical systems such as cyclones also contain multi-scale interactions between clouds and cloud systems. We show the effectiveness of our framework to track organized cloud system during one such rainfall event which happened at Mumbai, India in July 2005 and for cyclone Aila which occurred in Bay of Bengal during May 2009.

Estimation of voice-onset time in continuous speech using temporal measures

This paper proposes an automatic acoustic-phonetic method for estimating voice-onset time of stops. This method requires neither transcription of the utterance nor training of a classifier. It makes use of the plosion index for the automatic detection of burst onsets of stops. Having detected the burst onset, the onset of the voicing following the burst is detected using the epochal information and a temporal measure named the maximum weighted inner product. For validation, several experiments are carried out on the entire TIMIT database and two of the CMU Arctic corpora. The performance of the proposed method compares well with three state-of-the-art techniques. (C) 2014 Acoustical Society of America

High resolution light-sheet based high-throughput imaging cytometry system enables visualization of intra-cellular organelles

Visualization of intracellular organelles is achieved using a newly developed high throughput imaging cytometry system. This system interrogates the microfluidic channel using a sheet of light rather than the existing point-based scanning techniques. The advantages of the developed system are many, including, single-shot scanning of specimens flowing through the microfluidic channel at flow rate ranging from micro-to nano- lit./min. Moreover, this opens-up in-vivo imaging of sub-cellular structures and simultaneous cell counting in an imaging cytometry system. We recorded a maximum count of 2400 cells/min at a flow-rate of 700 nl/min, and simultaneous visualization of fluorescently-labeled mitochondrial network in HeLa cells during flow. The developed imaging cytometry system may find immediate application in biotechnology, fluorescence microscopy and nano-medicine. (C) 2014 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

CHEXVIS: a tool for molecular channel extraction and visualization

Background: Understanding channel structures that lead to active sites or traverse the molecule is important in the study of molecular functions such as ion, ligand, and small molecule transport. Efficient methods for extracting, storing, and analyzing protein channels are required to support such studies. Further, there is a need for an integrated framework that supports computation of the channels, interactive exploration of their structure, and detailed visual analysis of their properties. Results: We describe a method for molecular channel extraction based on the alpha complex representation. The method computes geometrically feasible channels, stores both the volume occupied by the channel and its centerline in a unified representation, and reports significant channels. The representation also supports efficient computation of channel profiles that help understand channel properties. We describe methods for effective visualization of the channels and their profiles. These methods and the visual analysis framework are implemented in a software tool, CHEXVIS. We apply the method on a number of known channel containing proteins to extract pore features. Results from these experiments on several proteins show that CHEXVIS performance is comparable to, and in some cases, better than existing channel extraction techniques. Using several case studies, we demonstrate how CHEXVIS can be used to study channels, extract their properties and gain insights into molecular function. Conclusion: CHEXVIS supports the visual exploration of multiple channels together with their geometric and physico-chemical properties thereby enabling the understanding of the basic biology of transport through protein channels. The CHEXVIS web-server is freely available at http://vgl.serc.iisc.ernet.in/chexvis/. The web-server is supported on all modern browsers with latest Java plug-in.

Control of dynamical systems with temporal logic specifications

This thesis is motivated by safety-critical applications involving autonomous air, ground, and space vehicles carrying out complex tasks in uncertain and adversarial environments. We use temporal logic as a language to formally specify complex tasks and system properties. Temporal logic specifications generalize the classical notions of stability and reachability that are studied in the control and hybrid systems communities. Given a system model and a formal task specification, the goal is to automatically synthesize a control policy for the system that ensures that the system satisfies the specification. This thesis presents novel control policy synthesis algorithms for optimal and robust control of dynamical systems with temporal logic specifications. Furthermore, it introduces algorithms that are efficient and extend to high-dimensional dynamical systems.

The first contribution of this thesis is the generalization of a classical linear temporal logic (LTL) control synthesis approach to optimal and robust control. We show how we can extend automata-based synthesis techniques for discrete abstractions of dynamical systems to create optimal and robust controllers that are guaranteed to satisfy an LTL specification. Such optimal and robust controllers can be computed at little extra computational cost compared to computing a feasible controller.

The second contribution of this thesis addresses the scalability of control synthesis with LTL specifications. A major limitation of the standard automaton-based approach for control with LTL specifications is that the automaton might be doubly-exponential in the size of the LTL specification. We introduce a fragment of LTL for which one can compute feasible control policies in time polynomial in the size of the system and specification. Additionally, we show how to compute optimal control policies for a variety of cost functions, and identify interesting cases when this can be done in polynomial time. These techniques are particularly relevant for online control, as one can guarantee that a feasible solution can be found quickly, and then iteratively improve on the quality as time permits.

The final contribution of this thesis is a set of algorithms for computing feasible trajectories for high-dimensional, nonlinear systems with LTL specifications. These algorithms avoid a potentially computationally-expensive process of computing a discrete abstraction, and instead compute directly on the system's continuous state space. The first method uses an automaton representing the specification to directly encode a series of constrained-reachability subproblems, which can be solved in a modular fashion by using standard techniques. The second method encodes an LTL formula as mixed-integer linear programming constraints on the dynamical system. We demonstrate these approaches with numerical experiments on temporal logic motion planning problems with high-dimensional (10+ states) continuous systems.

Ultrafast temporal pattern generation and recognition

Ultrafast temporal pattern generation and recognition with femtosecond laser technology is presented, analyzed, and experimentally implemented. Ultrafast temporal pattern generation and recognition are realized by taking advantage of two well-known techniques: the space-time conversion technique and the ultrafast pulse measurement technique. Here the temporal pattern for the designed multiple pulses, optimized with a preassumed Gaussian spectral distribution of an ultrashort pulse, is described. With the simulation of a Gaussian spectral distribution, we realize that the uniformity of the generated multiple ultrafast temporal pulses is relevant to the repeated number of modulation periods in the mask in the spectral plane. Moreover, the change of Gaussian spectral phases with the wavelengths in the modulated phase plate is considered. Experiments of ultrafast temporal pattern recognition by the frequency-resolved optical gating (FROG) characterization technique are also given. (C) 2004 Society of Photo-Optical Instrumentation Engineers.

Caracterização espaço-temporal de plumas de sedimentos por sensoriamento remoto: um estudo de caso na foz do rio Paraíba do Sul.

Sedimentos em suspensão representam um dos principais fatores que afetam a qualidade dos sistemas aquáticos no mundo; influenciam os processos geomórficos de construção da paisagem e podem indicar problemas de erosão e perda de solo na bacia hidrográfica contribuinte. O seu monitoramento espacial e temporal é fundamental nas atividades de gestão ambiental de áreas costeiras. Nesse sentido, a hipótese básica desta pesquisa é que o padrão espacial e temporal de plumas de sedimentos costeiras associado ao regime hidrológico do rio pode ser caracterizado a partir de imagens orbitais de média resolução espacial. Para comprová-la, elegeu-se a foz do rio Paraíba do Sul como área de estudo para definição e teste metodológico, e formulou-se como principal objetivo mapear qualitativamente a pluma costeira deste rio a partir de imagens Landsat 5 e CBERS-2, ao longo do período compreendido entre 1985 e 2007. As datas avaliadas foram criteriosamente definidas através de três estratégias de análise, totalizando cinqüenta imagens. Pesquisa bibliográfica e avaliação da resposta espectral da feição de interesse nas imagens selecionadas consistiram nas etapas principais da definição da metodologia. As plumas foram então identificadas, mapeadas e extraídas; posteriormente, suas características espaciais e temporais foram analisadas por intermédio de sistemas de informação geográfica e avaliadas em conjunto com dados históricos de vazão. Os resultados indicam que a banda do vermelho forneceu uma melhor discriminação interna da pluma, sendo, portanto, utilizada como base para as análises realizadas neste trabalho. Com exceção do procedimento de correção atmosférica, a metodologia proposta consiste na utilização de técnicas simples de processamento digital de imagens, baseadas na integração de técnicas semi-automáticas e de análise visual. A avaliação do padrão dos sedimentos e dos mapas temáticos qualitativos de concentração de sedimentos em suspensão indica a forte diferenciação existente entre cenários representativos de épocas de cheia e seca do rio. Análises espaciais do comportamento da pluma contribuem ainda para um maior conhecimento do espaço geográfico, fornecendo subsídios aos mais variados setores do planejamento e gestão ambiental.

Measurement of polycyclic aromatic hydrocarbons in ambient air by fluorescence spectroscopic techniques

250 p. + anexos