Diff for 'CRISM'

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'''2)''' The targeted TRDR cube corrected for atmospheric absorption and incidence angle will then be processed through a custom pipeline to '''remove column-dependant noise''' and '''enhance spectral features of small spatial extent''': this pipeline basically divides the whole spectral data in the cube by a '''median spectrum''' computed from half of the lines (those in the middle) of the cube, on a column-by-column basis: a procedure we dub ‘ratioing’. The output ratioed cube is dubbed `medianratio`.  A by-product of the procedure is the creation of a transposed cube where columns and lines are switched, but which is only saved for the pipeline processing and should not be used as a standalone product. This procedure dramatically reduces detector noise (mostly column-dependant), corrects for most residual atmospheric absorptions (CO2 gas and/or water vapor/ice)and enhances small spectral features in ratioed spectra. However, there are also caveats to this ratioing procedure, such as the risk to introduce artifacts in ratioed spectra if the median spectra used for division itself was not blank but had spectral features: in such cases, the ratioed spectra will show inverted spectral features (eg., an absorption in median spectra will yield a positive peak in ratioed spectra) which will be artifacts and must not be interpreted as meaningful data. Still, for typical CRISM data, acquired over terrain with spectral features of low spatial extent (a few times smaller than the cube spatial extent), the median spectra will be nearly featureless and allow for reasonably straightforward detection of meaningful spectral features in ratioed spectra. '''2)''' The targeted TRDR cube corrected for atmospheric absorption and incidence angle will then be processed through a custom pipeline to '''remove column-dependant noise''' and '''enhance spectral features of small spatial extent''': this pipeline basically divides the whole spectral data in the cube by a '''median spectrum''' computed from half of the lines (those in the middle) of the cube, on a column-by-column basis: a procedure we dub ‘ratioing’. The output ratioed cube is dubbed `medianratio`. This procedure dramatically reduces detector noise (mostly column-dependant), corrects for most residual atmospheric absorptions (CO2 gas and/or water vapor/ice)and enhances small spectral features in ratioed spectra. However, there are also caveats to this ratioing procedure, such as the risk to introduce artifacts in ratioed spectra if the median spectra used for division itself was not blank but had spectral features: in such cases, the ratioed spectra will show inverted spectral features (eg., an absorption in median spectra will yield a positive peak in ratioed spectra) which will be artifacts and must not be interpreted as meaningful data. Still, for typical CRISM data, acquired over terrain with spectral features of low spatial extent (a few times smaller than the cube spatial extent), the median spectra will be nearly featureless and allow for reasonably straightforward detection of meaningful spectral features in ratioed spectra.
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=== Directory content === === Naming convention ===
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=== Directory content ===

The content of an CRISM product directory in MarsSI should look like:

 XXXXXXXXXXX_07_IF166S_TRR3.img::
 :: Short wavelength reflectance data, calibrated
 XXXXXXXXXXX_07_DE166S_DDR1.img::
 :: Short wavelength ancillary data
 XXXXXXXXXXX_07_IF166L_TRR3.img::
 :: Long wavelength reflectance data, calibrated
 XXXXXXXXXXX_07_DE166L_DDR1.img::
 :: Long wavelength ancillary data
 XXXXXXXXXXX_07_IF166L_TRR3_CAT.img::
 :: Long wavelength reflectance data, calibrated, converted to ENVI/CAT format
 XXXXXXXXXXX_07_IF166L_TRR3_CAT_corr.img::
 :: Long wavelength reflectance data with atmospheric correction
 XXXXXXXXXXX_07_IF166L_TRR3_CAT_corr_p.img::
 :: Map-projected long wavelength reflectance data with atmospheric correction
 XXXXXXXXXXX_07_IF166L_TRR3_CAT_corr_medianratioline.img::
 :: Values used to apply ratioing
 XXXXXXXXXXX_07_IF166L_TRR3_CAT_corr_medianratio.img::
 :: Ratioed long wavelength data (see Pipeline information)
 XXXXXXXXXXX_07_IF166L_TRR3_CAT_corr_medianratio_hyparam.img::
 :: Spectral parameter maps (map-projected)

The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) is a Visible and Near-Infrared (VNIR) imaging spectrometer onboard Mars Reconnaissance Orbiter (MRO), in orbit since 2006. It was built and tested by the Johns Hopkins University Applied Physics Laboratory under the supervision of principal investigator Scott Murchie. The observations enable to have mineralogy information of the martian surface at a spatial resolution of ~20 to ~200 m/px.

Instrument description

The CRISM instrument has two acquisition modes:

The targeted mode (multiangular pointing)

The instrument tracks the targets and takes 11 hyperspectral images (544 bands from 362 to 3920 nm) at different emission angles due to the rotation of the detector at ± 70°: 10 hyperspectral images taken at different emission angles before and after the central image corresponding to the close nadir image (image #07). The 10 hyperspectral multi-angular observations are reduced to a factor 10 compared to the spatial resolution of the central image. According to the spatial resolution of the central image, four product types are associated to this acquisition mode. If the central image is sampled at 20 m/px, the associated product is a Full Resolution Targeted observation (FRT). By reducing the spatial resolution of the central image by a factor 2, the spatial resolution is set at 40 m/px and the associated products are Half Resolution Short (HRS) and Half Resolution Long (HRL) observations. An HRL sampled surface is twice as long as an HRS observation. Only the central image #07 is processed by MarsSI for the mineralogy identification. ATO observations are Along-Track Oversampled products resulting in incresing of the resolution up to 3 m/px.

Types of targeted observations
FRT: 18 m/px HRS: 36 m/px HRL: 36 m/px ATO: 3-12 m/px
wiki/CRISM/FRT.png wiki/CRISM/HRS.png wiki/CRISM/HRL.png wiki/CRISM/ATO.png

The survey mode (nadir pointing)

This mode was designed to estimate key locations for further analysis with the targeted mode as it covers wider areas and produces lower spatial resolution data than the targeted mode. The instrument acquires multispectral images using fixed pointing where the emission angle is set at 0° (with specific bands chosen over the 544 spectral bands, in order to identify principal minerals). There are different types of observations using this acquisition mode:

  • Multispectral Survey (MSP): 200 m/px and 55 channels
  • Hyperspectral Survey (HSP): 200 m/px and 154 channels
  • Multispectral Window (MSW): 100 m/px

Downloading and processing CRISM data

Tutorial

From the “Maps” tab, zoom-in on your region of interest. You can swith to the THEMIS or CTX mosaic for more precision, and then display the CRISM layer corresponding either to the targeted or surveymode. You can see the CRISM product footprints that appear in different greens depending on their type. Use the “Select” button to choose the products you desire over an area. Use the right-click context menu to add your selection to your workspace.

wiki/CRISM/select_crism_targeted.jpg

In the "Workspace" tab, you will see your product selection. You can notice that different subproducts are present: the TRDR and DDR files in Short (VNIR) and Long (IR) wavelength ranges, “S” and “L”. Only the “L” cubes are used in the CRISM processing and are needed for further processing in MarsSI, but you can also download the “S” cubes for your own use.

Check the product status: if some data is not already done yet, select the rows you would like to request by ticking the input on the left column (you can use the "Select all" button to select all visible products) and click on the "Process" action on the top of the workspace table. You can check more information about the processing in the job tab if needed.

Once all the data you would like is done, select entries by ticking the input on the left column (you can use the "Select all" button to select all visible products) and click on the "Copy" action to request a copy of the data in your personal directory. You can then proceed to download products as described in the SFTP section.

Pipeline information

1) The TRDR cube containing the reflectance values in the infrared range will be processed using an implementation of the CAT pipeline (CRISM Analysis Tools, an add-on to IDL/ENVI available from the CRISM team (Murchie et al., 2007; Pelkey et al., 2007)). The cube will be corrected for the observation geometry (reflectance divided by the cosine of the incidence angle, available in the associated DDR cube) and for absorptions due to atmospheric CO2 using the CAT algorithm developed for CRISM based on the ‘volcano-scan’ approach (McGuire et al., 2009).

wiki/CRISM/corr.png

FRT00003E12_07_IF166L_TRR3_CAT_corr.img (false color composition)

2) The targeted TRDR cube corrected for atmospheric absorption and incidence angle will then be processed through a custom pipeline to remove column-dependant noise and enhance spectral features of small spatial extent: this pipeline basically divides the whole spectral data in the cube by a median spectrum computed from half of the lines (those in the middle) of the cube, on a column-by-column basis: a procedure we dub ‘ratioing’. The output ratioed cube is dubbed medianratio. This procedure dramatically reduces detector noise (mostly column-dependant), corrects for most residual atmospheric absorptions (CO2 gas and/or water vapor/ice)and enhances small spectral features in ratioed spectra. However, there are also caveats to this ratioing procedure, such as the risk to introduce artifacts in ratioed spectra if the median spectra used for division itself was not blank but had spectral features: in such cases, the ratioed spectra will show inverted spectral features (eg., an absorption in median spectra will yield a positive peak in ratioed spectra) which will be artifacts and must not be interpreted as meaningful data. Still, for typical CRISM data, acquired over terrain with spectral features of low spatial extent (a few times smaller than the cube spatial extent), the median spectra will be nearly featureless and allow for reasonably straightforward detection of meaningful spectral features in ratioed spectra.

wiki/CRISM/median.png

FRT00003E12_07_IF166L_TRR3_CAT_corr_medianratio.img (false color composition)

3) The penultimate step of the pipeline computes so-called ‘spectral parameters’ or ‘spectral criteria’ such as band depths or combination of band depths, as initially implemented in the CAT for multispectral CRISM data (Pelkey et al., 2007), or other parameters based on analysis of the shape of the spectra. We take advantage of the higher number of spectral channels in hyperspectral targeted CRISM observations compared to original CAT multispectral parameters: signal-to-noise is improved by using medians of spectral channels and specificity of criteria is improved by combining two or more criteria. The definition of a subset of the custom criteria available in MarsSI is given in Thollot et al. (2012) and the remaining can be made available on request (pending publication in a future paper). The resulting data cube, dubbed hyparam (for hyperspectral parameters), has the same spatial dimensions as the TRDR but each band in the spectral dimension contains the result of the computing of a spectral criterion designed for detection of one or several spectral features from the medianratio cube resulting from the previous step. The hyparam cube can be used in parallel with spectral data in IDL/ENVI to compare the spatial mapping of spectral criterion with actual spectra.

wiki/CRISM/hyp.png

FRT00003E12_07_IF166L_TRR3_CAT_corr_medianratio_hyparam.img (olivine index)

4) Finally, the pipeline projects the hyparam cube (adding the _p suffix) for use in a GIS in combination with other datasets (DTMs, CTX or HiRISE, etc.).

wiki/CRISM/p.png

FRT00003E12_07_IF166L_TRR3_CAT_corr_medianratio_hyparam_p_equir.img (olivine index)

Data description

Naming convention

The CRISM naming convention is the following:

(ClassType)(ObsID)_(Counter)_(Activity)(SensorID)_(Filetype).(EXT)
  • ClassType: FRT, HRS, HRL, ATO, MSP, HSP, MSW, ...
  • ObsID: observation ID
  • Counter: image number of the targeted sequence (only the n°7 is used in MarsSI). In the survey mode, this corresponds to 1
  • Activity: subtype of product: IF stands for reflectance data (I/F unit), DE for ancillary data (e.g. latitude, longitude, incidence, emission, phase angle
  • SensorID: S detector (Short wavelenghts) or L (Long wavelenghts)
  • Filetype: type of dataset: TRR3 are calibrated data cubes, DDR1 companion data cube containing the ancillary data
  • EXT: extension of the data (img, lbl, ...)

Ex: FRT000A82E_07_IF164L_TRR3.IMG correponds to calibrated data cube containing the reflectance data (I/F unit) in the IR range (from 1002 to 3920 nm) of the central image (corresponding to the “07” image of the targeted sequence) of an FRT observation.

Directory content

The content of an CRISM product directory in MarsSI should look like:

XXXXXXXXXXX_07_IF166S_TRR3.img
Short wavelength reflectance data, calibrated
XXXXXXXXXXX_07_DE166S_DDR1.img
Short wavelength ancillary data
XXXXXXXXXXX_07_IF166L_TRR3.img
Long wavelength reflectance data, calibrated
XXXXXXXXXXX_07_DE166L_DDR1.img
Long wavelength ancillary data
XXXXXXXXXXX_07_IF166L_TRR3_CAT.img
Long wavelength reflectance data, calibrated, converted to ENVI/CAT format
XXXXXXXXXXX_07_IF166L_TRR3_CAT_corr.img
Long wavelength reflectance data with atmospheric correction
XXXXXXXXXXX_07_IF166L_TRR3_CAT_corr_p.img
Map-projected long wavelength reflectance data with atmospheric correction
XXXXXXXXXXX_07_IF166L_TRR3_CAT_corr_medianratioline.img
Values used to apply ratioing
XXXXXXXXXXX_07_IF166L_TRR3_CAT_corr_medianratio.img
Ratioed long wavelength data (see Pipeline information)
XXXXXXXXXXX_07_IF166L_TRR3_CAT_corr_medianratio_hyparam.img
Spectral parameter maps (map-projected)

Working with CRISM targeted parameters

Please consider these products with a critical eye. Despite using labels describing specific mineral (or other) detection, please keep in mind that the spectral parameters mapping does not represent mineralogical maps. They are the result of spectral analysis results that are *USUALLY* typical of such minerals presence, and is presented as an evidence, but not a definitive proof of such.

To infer the true mineralogy of one location, the associated spectra (in corr or corr_medianratio cubes) should be studied carefully. Be cautious to not overinterpret instrument artefacts and other false positive as real results!

The hyparam cube produced by MarsSI contains computed spectral parameters. They account on each pixel for the likeness between the observation spectrum and the theoretical spectrum of a mineral specie, but can also give information on the position of absorption band, intensity of one particuliar band, etc. This cube is used to map spectral features.

The details of how the different parameters can be used are as follows (as in april 2018):

Band number Parameter Detections (non exhaustive) Details
1 OLINDEX2 Olivine, pyroxenes, FeMg clays Better identifies the 1 micron olivine absorption by accounting for spectral slope. Also corrects for the false identification of olivine due to high albedo. Incorrectly maps hydrated regions as olivine-rich due to the associated decrease in reflectance beyond 2-microns. Also, like OLINDEX, this parameter falsely identifies pyroxenes as olivine. future work will be done to correct both the false identifications of hydration and pyroxene as olivine-rich.
2 BD1900R H2O bound Find the 1.90 micron H2O band depth
3 BD1980 Sulfites Find the 1.98 micron sulfite band depth
4 BD2200 Al-OH bound Find the 2.20 micron Al-OH band depth
5 Doub2200 Find the 2.22 and 2.28 micron doublet band depth
6 BD2230 Find the 2.23 micron band depth (K. Lichtenberg)
7 BD2500 Carbonates Find the 2.50 micron band depth
8 Jar_index Jarosite Find the 2.205-2.272 micron 'W' exact shape
9 Kaol_index Kaolinite Find the 2.16-2.20 asymetric kaolinite band
10 Opal_index Opal Find the 2.20-2.26 asymetric Opal band
11 Fe_smec_index Fe clays Find the 2.29 and 2.40 Fe smectite band
12 Sulf_index Sulfates Find the 1.94-2.0 and 2.40-2.44 non-hydrates sulfates bands
13 BD2232m (Ferri)Copiapite / Fe sulfates Find the 2.232 band of part. dehydr.
14 Hydr-salt_index Bassanite, gypsum, carnallite Find the 1.77, 1.92-1.98, 2.49 bands
15 BD2205m Kaolinite, montmorillonite, opal Find the 2.205 band
16 BD2205Left Kaolinite Find the asymetric left 2.205 band
17 BD2205Right Opal Find the asymetric right 2.205 band
18 BD2285m Fe smectites Find the 2.285 band
19 BD1922m Hydrated minerals Find the 1.922 band
20 BD1849m Jarosite Find the 1.849 band
21 BD2106m Sulfates Find the 2.106 band
22 BD2268m Jarosite Find the 2.268 band
23 BD3837m Carbonates Find the 3.8-3.9 band
24 POS221 Find the exact wavelength of minimum of 2.21 band at 2.1855-2.2252
25 POS227 Find the exact wavelength of minimum of 2.27 band at 2.2583-2.3046
26 BD1047m Iron oxydes Find the 1.0472 band of iron oxides relative to linear fit 1.3423-2.1261
27 Hydr_FeMg_clay_index Hydrated FeMg TOT clays Find the 1.4; 1.9; 2.3; 2.4 bands
28 Si-OH_index Hydrated glass Find the 1.4; 1.9; 2.2 bands
29 BD2265narrow Jarosite even within mixtures Find the 2.265 band
30 2205to2278 Get 2205/2278 ratio in doublet when both bands present
31 BD1060poly2 Iron oxydes Find the 1.0603 band of iron oxides relative to 2nd order polynomial fit 1.3423-1.8292-2.6021
32 BD1080SEC Iron oxydes Find the 1.0800 band of iron oxides relative to 2nd order polynomial fit 1.3423,MAX(2.1525;2.2517)@2.203,2.6021
33 Chlor_index Chlorite Find the 2.25 and 2.34 bands
34 BD1380-1440 OH bound Find the 1.4 OH band
35 POS14xx Find the exact wavelength of minimum of 1.4 band at (1.3752)1.3818-1.4409(1.4474)
36 BD1908m Hydrated minerals Find the 1.91 band
37 BD1961m Hydrated minerals Find the 1.96 band
38 191to196 Si-OH hydrated minerals Find the 1.91/1.96 ratio in hydrated minerals, esp. Si-OH bearing
39 POS19xx Find the exact wavelength of minimum of 1.9 band at (1.895)1.902-1.981(1.987)
40 BD2272m_2179 Jarosite Find the 2.272 band of jarosite anchored at 2.18 instead of 2.09
41 Olivine_index Olivine Find the 1.080, 1.257, 1.369 and 1.467 bands
42 BD1760m Hydrated minerals Find the 1.76 band
43 FeMg-OH FeMg-OH bounds Find the 2.3 and 2.4 bands
44 BD2106+2139_poly2 Monohydrated sulfates Find the average of 2.106 & 2.139 band of monoh. sulf. relative to 2nd order polynomial fit 1.856-2.311-2.490

References

  • CRISM instrument description website: http://crism.jhuapl.edu/instrument/design/overview.php
  • McGuire P. C., e t al. (2009), An improvement to the volcano - scan algorithm for atmospheric correction of CRISM and OMEGA spectral data, Planet. Space Sci., 57(7), 809 - 815.
  • Murchie, S., et al. (2007), Compact reconnaissance Imaging Spectrometer for Mars (CRISM) on Mars Rec onnaissance Orbiter (MRO), J. Geophys. Res., 112(E5).