Lab 07, Hyperspectral Remote Sensing

 Background and goals:

    The goal of this lab was to gain knowledge and technical skills in hyperspectral imagery and hyperspectral imagery analysis. The second goal of this lab was it introduce the user to FLAASH processes, including correcting a hyperspectral image & calculating vegetation metrics.

    The results portion of this report will be omitted, as there was no major result from this lab so all deliverables will be present in the methods section.

Methods:

    First was an introduction to spectral processing. A ROI file was added to a hyperspectral image, which was then used to extract mean spectras within the ROI. This was then compared in the spectral library, as seen below.

The ROI statistics dialogue with results from spectral library.

           Next, 20 bands were animated within a greyscale image. This is done to make the spatial occurrence of spectral reflectance more obvious.   

    All operations within FLAASH were not actually ran, there was either a workaround used or the result was already within the lab folder. This was done because currently the UWEC Geography program does not have a FLAASH license.

    Using imagery that had been atmospherically corrected using FLAASH, various vegetation analysis was conducted. One of these tools that was ran was fire fuel tool. This tool produced the below image.

    Fire fuel analysis

        The last portion of the lab was focused on hyperspectral transformations. The dimensionality of the image was reduced using MNF(Minimum Noise Fraction). This resulted in the eigenvalues plot is shown below. 

Eigenvalues plot

Sources:

    Harris geospatial.(2020).[ENVI Basic and Advanced Hyperspectral Analysis dataset].Harris geospatial. Provided by Cyrl Wilson.