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Under the patronage of

Minister of Energy & Chairman of Kuwait Petroleum Corporation
 

Workshop: Remote sensing of oil spills

28 May 2008

09:00 AM - 14:00 PM

Summary

    Today remote sensing is a critical element for an effective response to marine oil spills. Space and air- borne platforms are using optical, microwave, passive and active sensors. Timely response to an oil spills requires rapid reconnaissance of the spill site to determine its exact location, extent of oil contamination. This is necessary to effectively direct spill countermeasures such as mechanical containment and recovery, dispersant application and in situ burning, the timely protection of sites along threatened coastlines and the preparation of resources for shoreline clean-up. Remote sensing is useful in several modes of oil spill control, including large area surveillance, site specific monitoring and tactical assistance in emergencies. It is able to provide essential information to enhance strategic and tactical decision-making, decreasing response costs by facilitating rapid oil recovery and ultimately minimizing impacts. For marine oil spills, remote sensing data can provide dynamic information through multi-temporal imaging and input to drift prediction modeling. Important parameters are revisit times, delays in receipt of processed image.
    Examples include data from ROPME Sea Area (Bahrain, Iran, Iraq, Kuwait, Oman, Qatar, Saudi Arabia, UAE), Baltic, Black and Caspian Seas and models for international cooperation.

 

Objectives

    Participants will learn the skills and tools related to:

·        Evaluation of the available remote sensing platforms and sensors

·        Familiarization with analysis and processing techniques

·        Overview on the oil spills in ROPME Sea Area, and cases from Baltic, Black and Caspian Seas

·        Concepts of international cooperation

Course Contents:

Dr. V. Byfield, Monitoring oil pollution using remote sensing data and international cooperation. NOCentre, Southampton, UK

Multi platform data

Algorithms

Coordination

Recommendations

Baltic, Black and Caspian Seas

Dr. P. Petrov, Remote sensing monitoring of oil spills in ROPME Region, ROPME, Kuwait

Space and airborne platforms

Optical systems :

NOAA AVHRR, Landsat: MSS, TM, ETM, Terra, Aqua ASTER, MODIS

SAR : RADARSAT

Specifics of the Region

Regional Time coverage

F. Al Awadi, Exploring Open Source Software for Processing Oil Spill Data, ROPME, Kuwait

File Formats, HDF

Free Software

Image processing techniques

Registration Fees: USD 1000 ( Only for attending the short course, or USD 1600 for Conference and Short course)

Fees Include: Course Materials, Coffee Breaks, and Lunch

HYPERSPECTRAL IMAGE ANALYSIS FOR OIL SPILL DETECTION

 Dr. Foudan Salem, George Mason University

29 May 2008

09:00 AM - 14:00 PM

 

CONTENT SUMMARY

This Hyperspectral Data Processing training course is specifically designed to outline the new tools for processing and analyzing images acquired with airborne and satellite-borne imaging spectrometers. Different methods can be used to analyze hyperspectral imagery and extract useful information.  This course focuses on the advanced techniques for hyperspectral image classification and spectral analysis techniques for target identification. Therefore, it assumes students have a good understanding of the principles and basics of remote sensing concepts and image processing techniques. 

The hyperspectral course utilizes a mixture of lecture, discussion, and interactive exercises. The focus is the practical exercise of hyperspectral data analysis and processing. The latest hyperspectral softwares, the "Environment for Visualizing Images" (ENVI), will be used to illustrate key concepts and provide participants with hands-on experience, which gives participants in-depth instructions in hyperspectral data processing, analysis, and interpretation. The fundamentals and principles of imaging spectrometry will be presented and advanced methodologies will be discussed and demonstrated. It is important to notice that, often, such software (particularly) is not user-friendly and, therefore, we believe a market does exist for people with these skills. However we will also track other potential software to be included in the future.

OBJECTIVES

Course participants will learn the skills and tools to :

  • ·Search, assess, browse, and subset data sources

  • ·Import and examine metadata  and visualize hyperspectral data

  • ·Become familiar with tools and methods of HSI image processing and analysis.

  • ·Be introduced to value-added geo-information products derived from hyperspectral imagery and appreciate of their accuracy and quality.

  • ·Acquire concepts of hyperspectral remote sensing and data distribution for different applications

  • ·Obtain an overview of hyperspectral data, techniques, and various tools

General References

·T. Lillesand and R. Kiefer, Remote Sensing and Image Interpretation, Wiley,1994

·J. A. Richards, Remote Sensing Digital Image Analysis, Springer Verlag, 1993

COURSE CONTENTS

Lecture 1: Hyperspectral Concept and Fundamentals

  • ·Hyperspectral basics and data new processing strategies

  • ·Advantage and limitations of hyperspectral data (Data dimensionality)

  • ·Data-derived endmembers collection

  • ·Finding and Viewing Data

Lecture 2: New Methods for Defining Regions Of Interest (ROI’s)

  • ·Spectrum Extraction and Features Analysis

  • ·Spectral libraries and spectral variability

  • ·Compare image spectra with the spectral library (USGS, JPL, ENVI, JHU)

  • ·Limitations of conventional  multispectral techniques (training samples)

  • ·A Comparison between HSI and MS Data and image processing techniques

Lecture 3: Data Reduction Techniques

  • ·Data Spectral Reduction  Using Minimum Noise Fraction Transformation

  • ·Data Spatial Reduction Using Pixel Purity Index (PPI) Algorithm

  • ·Spectral feature analysis and spectrum identification

  • ·Spectral properties of materials ( vegetation, minerals, soil, water quality)

  • ·Spectral interpretation methods

Lecture 4: Advanced Techniques for Target Identification

  • Spectral Angel Mapper (SAM) Classification

  • Partial Unmixing (PU), pixels projection

  • Mixture Tuned Matching Filter (MTMF) Technique

  • MF score and  Signal Enhancement

  • ROI’s Clustering using N-Dimensional Visualization to extract endmembers

Lecture 5:  Review of Practical Hyperspectral Applications

  • ·    Land cover/ land use analysis

  • ·    Geology and mineral detection

  • ·    Soil survey and mapping, land suitability

  • ·    Coastal and marine information, chlorophyll, suspended sediments

  • ·    Aquatic plants, , and agriculture and forestry

  • ·    Oil spills, chemical pollution and water quality

  • ·    Environmental and natural hazards

  • ·    Oceanography,  hydrogeology and marine environment

 

Who Should attend?

Operational Responders, who have some experience in oil spills and require a more detailed understanding the use of GIS and Remote sensing in Oil Spill management.
Field supervisory personnel responsible for undertaking on-site clean up operations.
Members of emergency team that would support oil spill response effort.
Those responsible for preparing a company contingency plans.
Those responsible for the transportation and storage of oil inland.
Those working in Environment
Researchers
GIS specialists
GIS Developers


Registration Fees: USD 1000 ( Only for attending the short course, or USD 1600 for Conference and Short course)

Fees Include: Course Materials, Coffee Breaks, and Lunch

 

Sponsors

Environment Public Authority

Associate Sponsors

 

TARIQ A. AL QAHTANI & BROS

SEACOR Environmental Services Inc

Media Partner