##############   KNOWN ISSUES   ################################################

ALL RESULTS SHOULD BE CHECKED FOR ACCURACY as calibration can throw off
identifications, and check that the Tetracorder expert system adequately
covered the environment.   Either condition (error in calibration to
reflectance, or minerals or other materials in the environment that
are not covered by the expert system used) can cause misidentification.
Thus, spectral features should be extracted from the image cube(s) for
each identified component that is important to your study and checked
that the spectral features in that unit are consistent with known spectral
properties for that material.  Ideally, important identified components
are verified by field work collecting samples when possible.

Please understand the diagnostic nature of absorption features in minerals.
Broad electronic absorptions have a lot of similarities between minerals,
especially Fe2+ bearing minerals.  Therefore many tetracorder output files 
include generic in the file names.  The specific mineral in the name is 
so you know the reference spectrum used, not that that specific mineral
was identified.

A good example of diagnostic nature of absorption features is illustrated
in the organics confusion below.


ISSUES for: cmd.lib.setup.t5.2e1 +

#########################################################################################
######  Color map products

Color output products in directories color.results+labels and color.results+labels-jpegs
include experimental results.  For example, minerals assigned mineral IDs are EXPERIMENTAL
and should be checked for accuracy.  While minerals have varying positions of the 1.9-micron
water band, it is not known how unique these positions are for specific mineralogy,
and many absorptions broadly overlap.  Some positions may indicate classes, for
example, sulfate 1.9 absorption positions tend to be longer than phyllosilicates.
More research in this area is needed to understand how diagnostic these positions are.

For terrestrial data made with the Sun (e.g. aircraft or orbital imaging spectrometers
or field spectrometers) with have strong atmospheric absorptions that are opaque or
mostly so, then any absorptions in the terrestrial water bands, especially 1.3 to 1.5
microns and 1.9 micron regions are compromised and likely lead to false IDs.  Best
to avoid any IDs in this situation.

#########################################################################################
###### Spectra of shallow water can mimic broad electronic absorptions, commonly Olivine

Water has multiple absorptions in the near infrared and in shallow
water, the absorptions overlap such that there is a broad decrease in
reflectance from the visible to IR and when the continuum is removed,
mimics the broad absorption like that seen in olivine.  If tetracorder
maps olivine near lake shores or shallow streams, it is likely that this
condition is giving a false positive.


#########################################################################################
###### Clouds and cloud shadows

Clouds and cloud shadows can result in false IDs.  Sometimes the signatures result
in various minerals that are probably not real.  Land can reflect into clouds
and induce absorptions in the cloud spectra, so the materials are not actually in the
clouds.  Cloud shadows often map as water when light is transmitted through the cloud
and onto the land.  Technically, the water signature is correct, just not on the surface.


#####################################################################################
###### Organics Confusion

The spectral signatures of organics are similar and telling organics apart
at the typical spectral resolutions of imaging spectrometers is difficult.
While separating aliphatic from aromatic hydrocarbons or organics with
single, double or triple bonded carbons atoms is possible at spectral
resolution typical of imaging spectrometer (e.g. AVIRIS, CRISM, VIMS),
identifying specific organics is not possible.  For example, one AVIRIS
scene mapped clay minerals + gasoline along a portion of a highway.
Was raw gasoline spilled in that area?  No.  Trash, which contains
plastics, are mainly aliphatics hydrocarbon and have absorptions close
to the aliphatic hydrocarbons in gasoline at AVIRIS spectral range
and resolution.  A higher spectral resolution spectrometer and/or
ground checking would be necessary to distinguish the possibilities.
Understanding such limitations of spectroscopy and the Tetracorder
identified results is important.

Perhaps entries like clay minerals + gasoline should be renamed
clay minerals + aliphatic hydrocarbon.  


#####################################################################################
######  High-iron olivine and magnetite absorptions are similar in the near-IR

High-iron olivine and magnetite have broad electronic absorptions that
can appear similar and make it difficult to distinguish between the
two in the near-infrared.  To better aid in separation, more high iron
olivines as a function of grain size and magnetites as a function
of grain size are needed to distinguish between these two minerals.


#####################################################################################
###### Prehnite - Chlorite confused with kaolinite + calcite + dry vegetation mixture

prehnite+chlorite can map with a kaolinite + calcite + dry vegetation mixture
           - observed in Arches 1995 Aviris data

this is mitigated to some degree in cmd.lib.setup.t5.2+ series, but not completely.

#####################################################################################
###### Snow detected in some vegetation:

One of the expert system known deficiencies is desert types of vegetation
which have broad water bands that are shifted to longer wavelengths
than typical vegetation, and the closest match is ice and melting snow.
More vegetation spectra need to be added to the expert system.  
Mitigation: if you knew the temperatures were above freezing everywhere in
your data, snow/ice could be rejected.  Thus, if your imaging spectroscopy
data are in warm environments, set the temperature above 0 C.  This can
be difficult if in mountainous terrain.

Vegetation in shallow water can also mimic the broader water features
of liquid water plus snow and vegetation.  The only way to reliably separate
these is to include temperature and if above 0 C, snow can be rejected.

#####################################################################################
######  Sphalerite

Sphalerite is not a diagnostic detection, only a general shape match so could
be other things.

#####################################################################################
######  Azurite.

If there are Fe2+ absorptions along with a carbonate band, it can be
misidentified as azurite.  Fe2+ bands are very similar over a wide
variety of Fe-bearing minerals, and can be similar to the Cu absorption
in azurite.  Detections of azurite should be field checked if important.

#####################################################################################
######   Epidote

Epidote is usually identified well.  If you see it mapping over broad areas,
it may indicate a calibration error, or another compound is causing confusion.

#####################################################################################
###### Areas where no minerals map

Check the vegetation maps to see if vegetation was thick in the areas
where no minerals mapped.  Tetracorder will try and detect minerals
when the vegetation is sparse enough, but as the vegetation thickens,
it gets more difficult.  If there is little vegetation in the areas where no
minerals mapped, it is likely due to 1) the minerals covered by the spectrometer
used do not have absorptions in that wavelength region, or 2) the surface is wet.
Water is very absorbing in the near infrared and will suppress photon path
length into the ground, making mineral detection difficult.

#####################################################################################
######  Sericite

Sericite is a fine grains muscovite/illite/paragonite, so check those three minerals. 

#####################################################################################
######  Magnetite

Magnetite is very dark with a broad iron absorption that is not terribly diagnostic
and can be confused with the broad iron absorption in a high iron olivine.
Look in the group.1.5um-broad and results.group.1.5um-broad directories.


#####################################################################################
###### Rhodochrosite, Strontianite, Siderite

It is unclear how easily these carbonates can be distinguished from other carbonates
at spectral resolution like that in AVIRIS.  Confirm that these identifications are
correct and that it is not another carbonate.  In particular, a carbonate
mixed with an Fe2+-bearing mineral may be misidentified as rhodochrosite or siderite.

#####################################################################################
###### Chert, Opal and hydrated_basaltic_glass

Chert, Opal and hydrated_basaltic_glass are all cryptocrystalline silica with OH.
Report as: Si-OH glass/chert/opal.   It is not clear how well we can tell these
apart with spectroscopy without more research.

#####################################################################################
######  group 2: nacrite, kaolinite group 

Starting with 5.27c1, nacrite was added to complete the kaolinite dioctahedral group.
Nacrite is hydrothermal origin, and it shows mapping in sedimentary environments.
Thus actual identification of nacrite needs investigation, as it my be getting
confused by kaolinite, possibly when other minerals are present.  However, with
the nacrite addition, more kaolinite group seems to map, with less noise in the color
map images.   More research is needed to understand this problem.

#####################################################################################
######  group 13: 1.3-1.4 micron OH narrow 
######  group 14: 1.4-1.5 micron OH
######  group 15: 1.5 micron OH

Many minerals have OH absorptions close to the same wavelength and with similar
widths.  How diagnostic any one feature identification is needs more research.
So these entries, if found by tetracorder, should be treated as indication
of an OH-feature at that wavelength, but the specific mineralogy can not
be relied on.  The spectrum would have to be examined for other features
to verify specific mineralogy.

#####################################################################################
######  group 19: 1.9-2 micron water and ice

Ice is usually diagnostic, and there are observed general trends of mineral groups
with wavelength of this water combination band.  But beyond ice, specific
mineralogy can not be certain.  However, for example, if the feature matches
a sulfate, there is a good probability that a sulfate may be present, but
not necessarily that specific mineral identification.

#####################################################################################
###### group 7:  2.7 to 3-micron OH region
###### group 8:  2.7 - 2.8-micron OH region narrow bands

There are only a few entries in these groups, generally just to detect a feature
here.  Many OH and all the broader water absorptions overlap, so specific
mineralogy is not possible now.  So only report detection of a feature
(and its wavelength), but not specific mineralogy.

#####################################################################################
######  group 10: testing 3.5 um curved continua
######  3.5-micron region linear continua

Hydrogen peroxide detection on Earth is probably a carbonate that we do not
have in the spectral library for these wavelengths. 
Check also group 24: 4-micron region


#####################################################################################
###### group 24: 4-micron region

This is one of the most sensitive regions for detecting carbonates.
But we do need to add more carbonates at low abundances.
So report carbonates, but not the specific mineralogy.

#####################################################################################
###### group 26: 4.25 micron CO2 trapped, ice 

Trapped CO2 absorptions are not known at this time to be indicative of the host
mineralogy.  So do not report specific mineral detection using this feature.
Currently it only indicates the presence of trapped CO2.

#####################################################################################
###### group 27 ###### 4.5-micron region  includes sulfates

There are 47 entries in 5.27b1, but more are needed, so only broad classes 
of minerals should be recorded, not individual IDs.


#####################################################################################
###### methane and CO2

group  2: group.2um/methane-gas-2.37um-experimental
group 38: group.ch4gas-2.3um/methane-gas-2.37um_g37-experimental
group 38: group.co2gas-2um/co2-gas-2um_g38-experimental

These are very experimental to see if residual gas signatures might be detected.
Note that this depends on the atmospheric removal algorithm not adjusting for
pixel to pixel changes.

Multiple path lengths can increase gas signatures, e.g., cloud-land reflections,
land-land reflections (mountains), so there are a lot of false positives.
Any signature needs to be checked.

#####################################################################################
###### CRISM data and mapping vegetation on Mars

Ideally, spectroscopy would be robust for detecting all kinds of
compounds, regardless of the environment.  This is likely true in
general, depending on the diagnostic nature of the absorption bands and
the capability of the spectrometer and its calibration.  The tetracorder
expert system is designed to work in multiple environments, including
the Earth, Moon, Mars, etc, and including detection of vegetation with
the chlorophyll absorption.  However, the CRISM instrument has a large
gap in spectral coverage right in the critically diagnostic chlorophyll
absorption in the visible.  This leads to a lot of false identifications
of vegetation in CRISM data.  However, it may be possible that
somewhere on Mars there might, in theory, be some chlorophyll, e.g. in
cyanobacteria.  For that possibility, all tetracorder detections of
chlorophyll in CRISM data must be thoroughly checked and confirmed before
claiming an identification.


