Hello,

I downloaded three different types of datasets of the same observation FRT00013d75_07_if163j. Then, I used the CAT tool in ENVI to produce the ICE summary product. Before projecting, the summary products were flattened (of course, flattening was not done with the MTRDR summary product). I was expecting Green (indicating surface rich in H2O ice) and magenta region (mix of CO2 ice, H2O ice, and dust).

Following image shows ICE summary product using TER dataset (leftmost), TRDR dataset (middle) and MTRDR dataset (rightmost).

1. While the MTRDR dataset shows a large area represented by light pink(shade of magenta, TER and TRDR datasets fail to do so. Seems like a scanning line error right in the middle of the TER and TRDR summary products (as you can see, the magenta region is getting vanished in the left half of the images, typically like a scanned effect).

2. While TER and TRDR show correct coordinates with the south polar stereographic projection (as I projected them using ddr file), the MTRDR product (already projected by the team) seems not to display correctly. ENVI is showing error as shown in the right side (Unsupported MAP_PROJECTION_TYPE). Also, the MTRDR product seems to be rotated by about 45 degrees in the display.

Can someone explain these two anomalies?

 

Thanks in anticipation!

 

 

Hello Sehaj,

 

I've taken a look into the first anomaly that you see, and I think I have an explanation.

 

What's happening here is actually an artifact of the summary product flattening that was applied to the TER and TRDR datasets. For each parameter, the flattening algorithm is designed to adjust the median values of each column in sensor space to match the median value of the parameter across the entire scene, in order to minimize the effects of column-dependent noise. However, this scene has three distinct regions (CO2 ice, magenta in the MTRDR, H2O ice, green in the MTRDR, and ice-free, black in the MTRDR), which causes this algorithm to break.

 

In this scene, it looks to me like the flattening algorithm generally adjusted all columns to have the same median parameter values as the CO2 ice region, which is why most of it appears black in the default color stretch. The magenta "wedges" you see in the projected TER/TRDR images are pixels viewing CO2 ice, but where most of the column has ice-free pixels, so the parameter values in these wedges were significantly elevated above the rest of the scene. The magenta band appears to be the columns which have a similar number of CO2 ice and ice-free pixels, so the median value (and adjustment due to flattening) is actually controlled by the H2O ice pixels.

 

Here's a quick comparison I put together showing the ICE summary product for the TER version of this scene in sensor space. The image on the left is with no flattening applied, and the image on the right is after flattening. It's a little easier to see how the amount of CO2 ice vs. ice-free pixels in each column controls the overall color in the flattened version.

 

I recommend skipping the flattening step while processing this particular scene. This will make the data a little noisier, but will fix the issue you see here with significant banding in the summary products.

 

Unfortunately, I am unable to help with the second anomaly you reported. A few other people in our group are taking a look into it, and will hopefully report back soon with what they discover.

 

Best,

John

Okay, understood. Many thanks @John Christian!

 

Hello Sehaj,

I want to follow up with you about the polar stereographic map projection issue. Frank Morgan from CRISM team is still looking into this issue. We will keep you posted once I have update. 

Thanks,

Feng

@Feng Thank you for your message. Looking forward to hearing from the team. Cheers!