Ray Arvidson

I believe that your problem is that MSV0003211d has an incidence angle of ~87 degrees, which is very close to the horizon, and thus signal to noise is very low. In ODE Mars search find this frame and look at the metadata (look at incidence angle in the metadata list), which is an option when you select this frame. Ray Arvidson

Specifically, which scene ID corresponds to the image that shows stripes? I will take a look. Ray Arvidson

Nathan: Hard for me to evaluate what is wrong. If you are willing, send me the Matlab code for one or more of your spectral index calculations and I will try and replicate your steps. Ray Arvidson

Sehaj: Did you see my last reply? No aerosol corrections in CAT. Not sure there is a method for correcting for aerosols other than radiative transfer modeling. Ray Arvidson

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

Hi: In your message "ERDAS it says there are no bands in the information". Not sure what you mean. ERDAS recognizes that it is an image cube but does not provide the wavelengths for each band? ERDAS does not know that it is a multiband cube, or what? Ray Arvidson

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

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

Sehaj: Both of these apps are a out of date and are not needed with the TRR3 or MTRDR data sets. I suggest skipping their use. Do flatten your spectral parameter sensor space data before projecting. Ray Arvidson

I am passing your question about map projection issues onto Feng Zhou, who is our staff member working with maps and ENVI CRISM data. I will also have Feng take a look at the destriping issue with the HSP data. Ray Arvidson

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

I just searched the Mars Orbital Data Explorer and there are hundreds of FRT observation from 2012 until now. Look for TRR3 TRDRs and FRTs and/or ATOs. Please read the CRISM Software Specification Document to become familiar with CRISM products https://pds-geosciences.wustl.edu/mro/mro-m-crism-2-edr-v1/mrocr_0001/document/crism_dpsis.pdf

Hi: I would use the TRR3 data sets and the CRISM Analysis Tool that works with ENVI. Are you using ENVI? Ray Arvidson PDS Geosiences Node Manager CRISM Team Member

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

The conversion is likely included in the code used to generate the BR at JHU/APL. I am sure various languages have this utility. Why do you need to know how it was done? Ray