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Dynamic Data-Driven Environmental Systems Science

First International Conference, DyDESS 2014, Cambridge, MA, USA, November 5-7, 2014, Revised Selected Papers

  • Conference proceedings
  • © 2015

Overview

Editors:
  1. Sai Ravela

    1. Massachusetts Inst. of Technology, Cambridge, USA

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    You can also search for this editor in PubMed   Google Scholar

  2. Adrian Sandu

    1. VA Polytechnic Institute and State Univ., Blacksburg, USA

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 8964)

Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)

Included in the following conference series:

Conference proceedings info: DyDESS 2014.

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Table of contents (31 papers)

  1. Front Matter

    Pages I-XI
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  2. Sensing

    1. Front Matter

      Pages 1-1
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    2. Small Satellite Constellations for Data Driven Atmospheric Remote Sensing

      • W. Blackwell, K. Cahoy
      Pages 3-9

    3. A Novel Approach to Atmospheric Measurements Using Gliding UASs

      • Ru-Shan Gao, James W. Elkins, Gregory J. Frost, Allison C. McComiskey, Fred L. Moore, Daniel M. Murphy et al.
      Pages 10-15

    4. In Situ Sampling of Volcanic Emissions with a UAV Sensorweb: Progress and Plans

      • David Pieri, Jorge Andres Diaz
      Pages 16-27

    5. Advances in Light Field Imaging for Measurement of Fluid Mechanical Systems

      • Jesse Belden, Jonathon Pendlebury, Alexander Jafek, Tadd Truscott
      Pages 28-38

  3. Environmental Applications

    1. Front Matter

      Pages 39-39
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    2. Multiscale Method for Hazard Map Construction

      • E. Ramona Stefanescu, Abani Patra, E. Bruce Pitman, Marcus Bursik, Puneet Singla, Tarunraj Singh
      Pages 41-53

    3. Coupled Dynamic Data-Driven Framework for Forest Fire Spread Prediction

      • Carlos Brun, Ana Cortés, Tomàs Margalef
      Pages 54-67

    4. iSPUW: A Vision for Integrated Sensing and Prediction of Urban Water for Sustainable Cities

      • Dong-Jun Seo, Branko Kerkez, Michael Zink, Nick Fang, Jean Gao, Xinbao Yu
      Pages 68-78

    5. Local-Scale Assessment of Tropical Cyclone Induced Storm Surge Inundation over the Coastal Zones of India in Probabilistic Climate Risk Scenario

      • A. D. Rao, Jismy Poulose, Puja Upadhyay, Sachiko Mohanty
      Pages 79-88

    6. A Data Driven Scientific Approach to Environmental Probes

      • Craig C. Douglas, Tainara Mendes de Andrade Soares, Mauricío Vieira Kritz
      Pages 89-99

    7. Towards Intelligent Closed-Loop Workflows for Ecological Research

      • JD Knapp, Matias Elo, James Shaeffer, Paul G. Flikkema
      Pages 100-111

  4. Reduced Representations and Features

    1. Front Matter

      Pages 113-113
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    2. Objective Detection of Lagrangian Vortices in Unsteady Velocity Data

      • George Haller
      Pages 115-120

    3. Statistical Inference for Coherent Fluids

      • Sai Ravela
      Pages 121-133

    4. Reduced Order Probabilistic Prediction of Rogue Waves in One-Dimensional Envelope Equations

      • Will Cousins, Themistoklis P. Sapsis
      Pages 134-143

    5. Analytical Approximation of the Heavy-Tail Structure for Intermittently Unstable Complex Modes

      • Mustafa A. Mohamad, Themistoklis P. Sapsis
      Pages 144-156

    6. Multiscale Stochastic Representation in High-Dimensional Data Using Gaussian Processes with Implicit Diffusion Metrics

      • Charanraj Thimmisetty, Arman Khodabakhshnejad, Nima Jabbari, Fred Aminzadeh, Roger Ghanem, Kelly Rose et al.
      Pages 157-166

    7. Recent Advances in Scaling Up Gaussian Process Predictive Models for Large Spatiotemporal Data

      • Kian Hsiang Low, Jie Chen, Trong Nghia Hoang, Nuo Xu, Patrick Jaillet
      Pages 167-181
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  1. Dynamic Data-Driven Environmental Systems Science

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About this book

This book constitutes the refereed proceedings of the First International Conference on Dynamic Data-Driven Environmental Systems Science, DyDESS 2014, held in Cambridge, MA, USA, in November 2014.
The 24 revised full papers and 7 short papers were carefully reviewed and selected from 62 submissions and cover topics on sensing, imaging and retrieval  for the oceans, atmosphere, space, land, earth and planets that is informed by the environmental context;  algorithms for modeling and simulation, downscaling, model reduction, data assimilation, uncertainty quantification and statistical learning; methodologies for planning and control, sampling and adaptive observation, and efficient coupling of these algorithms into information-gathering and observing system designs; and applications of methodology to environmental estimation, analysis and prediction including climate, natural hazards, oceans, cryosphere, atmosphere, land, space, earth and planets.

Editors and Affiliations

  • Massachusetts Inst. of Technology, Cambridge, USA

    Sai Ravela

  • VA Polytechnic Institute and State Univ., Blacksburg, USA

    Adrian Sandu

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