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Ray Arvidson

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Posts posted by Ray Arvidson

  1. CAT does not take care of aerosols. Only removes gas bands when you do the volcano scan atmospheric corrections. Removing aerosols explicitly is difficult. See below reference as an example. The TER and MTRDR processed versions on our ODE site do have an empirical removal included:  https://www.lpi.usra.edu/planetary_news/2016/03/14/planetary-data-systems-mars-reconnaissance-orbiter-crism-mrtdr-and-ter-data-release/

    Kreisch, C. D., O’Sullivan, J. A., Arvidson, R. E., Politte, D. V., He, L., Stein, N. T., Finkel, J., Guinness, E. A., Wolff, M. J., and Lapotre, M. G. A., 2017, Regularization of Mars Reconnaissance Orbiter CRISM along-track oversampled hyperspectral imaging observations of Mars, Icarus, DOI: 10.1016/j.icarus.2016.09.033. [Online]

    Ray Arvidson

  2. Never flatten a map projected product. Flattening is only for sensor space products. Please read the Software Specification Document on the PDS site under CRISM to understand the nature of the various product types. For MTRDR nothing more than examining the spectra and associated products is required. For the TRDR IF products use CAT to do a volcano scan correction and map projection. Generate spectral parameters in sensor space, flatten them, and then project them. Then do your science.

    Ray

  3. I mean under data filtering ,choose  flatten summary products. This is because the spectral summary products vary from column to column. Flattening does some column wise smoothing to make a better product. Do this in sensor space.

    Ray Arvidson

  4. Sehajpal: Destriping must be done on the sensor space data. That way each column is from one spectral detector set and destriping takes advantage of this simple arrangement. Did you try destriping after projection? You state: "Projecting the cube and applying destriping (Display 3 in screenshot) gives unusual results." If so, that is likely your problem.

    Ray Arvidson

  5. HiRISE and CRISM map projected data will not exactly overlay because they have slightly different pointings and associated errors. In addition, sometimes one needs to use a GDAL app (see attachment) to first change the map information for HiRISE to be consistent with the CRISM projection. I employ the GDAL app to get them closer and then I use ENVI's Image Registration Workflow with lots of control points and a triangular warp to do fine registration of HiRISE to CRISM. An issue associated with the ENVI app is that the difference in resolution between the two data sets cannot be more than a factor of six (check this number, I may be wrong). Thus, first down sample the HiRISE image to be amenable to use with CRISM data coregistration. So, the HiRISE data should have 3 m/pixel to work with 18 m/pixel ENVI data.

    jue.txt

  6. Hi Nathan:

    Multiple questions here. First you can do math on a spectrum by choosing Spectral Math under the Spectral tool on the ENVI menu. This is not a CAT tool, rather an ENVI tool. Once you are happy with whatever you derive you can switch to ENVI's Band Math to apply your new spectral parameter math to a hyperspectral image, e.g. CRISM data. Then you will have a parameter value output image to work with, colorizing or whatever you wish to do. Make sure you save your Band Math equation. Again, these steps do not use CAT.

    Ray Arvidson
    CRISM Science Team Member and Geoscience Node Manager

     

  7. OK, now I see what you mean. These 1.2 micrometer features could be real absorptions. Smectite clays present such an absorption. Look at the ENVI spectral library that is part of CAT. Given that my job is to help you get to the spectra and interpret without interpreting artifacts, I will leave it to you to do the assignments.

    Ray

  8. You must join files of the same size, in terms of lines and samples. Subset the larger file using the smaller file to generate a mask of for the smaller size and then use the mask to subset the larger file to fit the size of the smaller file. Then use New File Builder. Read the instructions on doing New File Builder and you will see where you went astray. Rochdi, as before in our many emails, may I suggest that you need to read the documentation before embarking on a new process.

    Ray

  9. These are spike artifacts in the data. Sometimes the instrument individual detectors are ill behaved and this is an example. Sometimes it is associated with going over sharp albedo boundaries where a detector has memories of what it was just sampling. There are no minerals that I know of that have such narrow single detector absorptions. Please ignore these spikes.

    Ray

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