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2085

Advanced ENVI Spectral Analytics (ENVI 550 - 3 days )

Discover the power of the spectral analysis tools that make ENVI the industry leader in hyperspectral imagery exploitation. Hyperspectral data analysis allows the identification of materials on the Earth’s surface due to the detailed sampling of the electromagnetic spectrum by hyperspectral sensors. This intensive four-day course focuses first on understanding the theory behind hyperspectral imaging, and then challenges the student to apply the theory with ENVI’s advanced analysis and mapping algorithms. Topics covered include image classification, principal components analysis, Minimum Noise Fraction, spectral libraries, spectral signatures, whole-pixel and sub-pixel analysis, and ENVI’s powerful endmember extraction algorithms. You’ll use data from several of the most widely used sensors, including AVIRIS, AISA and HyMap.

Prerequisite: A basic level of remote sensing knowledge is necessary to take advantage of what this course has to offer. This is an advanced ENVI class; a working knowledge of ENVI is desirable.

Multispectral Classification
  • Scatter Plots
  • Region of Interest tool
  • Supervised and Unsupervised Classification
  • Neural Net Classification

     

    Data Preprocessing
    • Sensor Calibration
    • Atmospheric and Solar Irradiance corrections
    • Sensor parameters
    • Empirical methods for conversion to reflectance
    • Model-based methods – FLAASH
    • In-scene method – QuAC

       

      Principal Components Analysis

       

      Hyperspectral Concepts
    • Z-Profiles – extracting spectra from data
    • Working with spectral libraries
    • Causes of spectral variability
    • Examples of spectra

       

      Whole Pixel Analysis Techniques
    • Spectral Angle Mapper 
    • Working with Rule Images
    • Spectral Feature Fitting (Continuum-removed spectra)

       

  • Identifying Image Endmembers
  • Mixture Models
  • Minimum Noise Fraction
  • Pixel Purity Index
  • N-Dimensional Visualizer
  • Spectral Analyst

     

    Sub-Pixel Analysis Techniques
    • Linear Spectral Unmixing
    • Matched Filter analysis
    • Mixture Tuned Matched Filter
    • Spectral Hourglass

       

      Automated Spectral Hourglass

       

      Target Recognition
    • Rx Anomaly Detection
    • Spectral Angle Mapper with BandMax
    • SMACC - Endmember Extraction (using a Mask)

       

      Target Detection Wizard
      • Hyperspectral data analysis workflow
      Georeferencing and Mosaicking
      • IGM files
      • GLT files
      • Mosaicking georeferenced images
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