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MRO CRISM and HiRISE Example

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Leslie Keely edited this page May 17, 2017 · 7 revisions

The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) is part of the instrument suite of NASA's Mars Reconnaissance Orbiter (MRO). It is multispectral and has a resolution of about 18 meters/pixel.

Data Credit: NASA/JPL/University of Arizona/JHUAPL

Terra Cimmeria Inferred Chloride Deposits

1.) Download the following files:

DTEEC_021689_1475_020832_1475_A01.IMG

ESP_021689_1475_RED_A_01_ORTHO.JP2

ESP_021689_1475_RED_A_01_ORTHO.LBL

frt00008573_07_brchlj_mtr3.img

frt00008573_07_brchlj_mtr3.lbl

2.) Convert the orthoimage to GeoTiff (see Appendix D in the DERT user guide for further information).

gdal_translate ESP_021689_1475_RED_A_01_ORTHO.LBL ESP_021689_1475_RED_A_01_ORTHO.TIF

3.) Add some metadata to the CRISM image.

gdal_translate -mo "AREA_OR_POINT=Point" -a_nodata 255 frt00008573_07_brchlj_mtr3.lbl frt00008573_07_brchlj_mtr3.tif

4.) Create a projection file from the DEM by running gdalinfo and copying and pasting the projection into dem.prj. The file should contain the following.

PROJCS["EQUIRECTANGULAR MARS",
    GEOGCS["GCS_MARS",
        DATUM["D_MARS",
            SPHEROID["MARS_localRadius",3391160,0]],
        PRIMEM["Reference_Meridian",0],
        UNIT["degree",0.0174532925199433]],
    PROJECTION["Equirectangular"],
    PARAMETER["latitude_of_origin",0],
    PARAMETER["central_meridian",140.79],
    PARAMETER["standard_parallel_1",-30],
    PARAMETER["false_easting",0],
    PARAMETER["false_northing",0]]

5.) Project the CRISM image with the DEM projection. Add a nodata alpha band.

gdalwarp -t_srs dem.prj -r bilinear -dstalpha frt00008573_07_brchlj_mtr3.tif frt00008573_07_brchlj_mtr3_reprj.tif

6.) Crop the width of the CRISM image to that of the orthoimage (get the coordinates with gdalinfo).

gdal_translate -projwin -3248.149 -1891526.446 3555.773 -1902722.449 frt00008573_07_brchlj_mtr3_reprj.tif frt00008573_07_brchlj_mtr3_reprj_crop.tif

7.) Make the CRISM image the same resolution as the orthoimage and pad it. Run gdalinfo on the orthoimage to get coordinates and pixel size.

gdal_merge.py -o chlDeposit.tif -ps 0.251326883488790 -0.251326883488790 -ul_lr -3247.646 -1888177.407 3555.270 -1903535.490 -init 0 -v frt00008573_07_brchlj_mtr3_reprj_crop.tif

8.) Create a landscape directory called TerraCimmeria and create the layers.

layerfactory -type=elevation -file=DTEEC_021689_1475_020832_1475_A01.IMG -tilesize=128 -landscape=TerraCimmeria
layerfactory -type=grayimage -file=ESP_021689_1475_RED_A_01_ORTHO.TIF -tilesize=512 -landscape=TerraCimmeria
layerfactory -type=colorimage -file=chlDeposit.tif -tilesize=512 -landscape=TerraCimmeria

9.) View the landscape in DERT.

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