Mars Surface Mineralogy from Hubble Space Telescope Imaging During 1994-1995: Observations, Calibration, and Initial Results

James F. Bell III¹, Michael J. Wolff², Philip B. James³, R. Todd Clancy²,
Steven W. Lee⁴, and Leonard J. Martin⁵

¹Cornell University, Department of Astronomy, Center for Radiophysics and Space Research, Ithaca, NY 14853.
²Space Science Institute, 1234 Innovation Drive, Suite 294, Boulder, CO 80303-7814
³Department of Physics and Astronomy, University of Toledo, Toledo, OH 43606
⁴LASP, University of Colorado, Boulder, CO 80309
⁵Lowell Observatory, Flagstaff AZ 86001

Submitted June 5, 1996 to J. Geophys. ResearchPlanets
Revised December 12, 1996

Accepted for publication December 22, 1996

Manuscript Pages: 22
Tables: 2
Figures: 6

Please address all correspondence to:

Jim Bell
Cornell University
Department of Astronomy
Center for Radiophysics and Space Research
424 Space Sciences Building
Ithaca, NY 14853-6801
phone: (607) 255-5911
fax: (607) 255-9002
email: jimbo@cuspif.tn.cornell.edu

Abstract
Visible to near-infrared observations of Mars were made with the Hubble Space Telescope during 1994-1995 with the goals of monitoring seasonal variability of the surface and atmosphere and mapping specific spectral units to constrain the planet's surface mineralogy. This paper presents the details of the collection and calibration of the data, concentrating specifically on the near-IR data that were obtained exclusively for the surface mineralogy aspect of our HST Mars observing program. We also present some initial results from the calibrated data set. Our calibration procedures included the standard "pipeline" processing steps, supplemented by special procedures required for use with the linear ramp filters on the Wide Field/Planetary Camera-2 instrument, and an additional point spread function deconvolution procedure applied in order to realize the full potential spatial resolution of the images (23 to 64 km/pixel between August 1994 and August 1995). The calibration results in a set of images projected onto a standard map grid and presented in radiance factor (I/F) units, having an estimated ‰5% photometric accuracy based on the performance of HST and comparisons with previous groundbased and spacecraft Mars spectra. Initial scientific analyses of these data reveal (1) Distinct red/blue color units within the classical bright regions, similar to those seen in Viking Orbiter images and possibly related to variations in nanophase and/or crystalline ferric mineral abundance; (2) Near-IR spectral slope variations correlated with albedo on a large scale (darker = "bluer" near-IR slope) but exhibiting wider variations among many of the small-scale features visible in the data; (3) An absorption at 860 nm that occurs in all regions but which is 3 to 5% stronger in many of the classical dark regions than in the bright regions, possibly because of a greater abundance of a well-crystalline ferric phase like hematite or a very low-Ca pyroxene; and (4) An absorption from pyroxene at 953 nm with a band depth that is inversely correlated with albedo (bright regions = 0 to 5% deep; dark regions = 7 to 15% deep) and which shows the highest band depth values in individual craters, calderas, and other small geologic units that are resolved in the images.

Introduction

The surface mineralogy of Mars provides a window into past and present geologic, geochemical, and hydrothermal processes on the planet. Surface minerals play an important role in the transport, storage, and processing of volatiles. For example, water can be stored either temporarily (adsorbed "surface" water) or semi-permanently (bound or "structural" water) on mineral surfaces and within mineral crystal lattices. Atmospheric gases such as CO2 or SO2 can be sequestered within minerals through aqueous or other processes, thus providing a sink for ancient atmospheric constituents (e.g., Fanale et al., 1992). The surface-atmospheric transport of volatiles on seasonal timescales is an important part of the Mars volatile cycle, and can substantially influence the climate and radiative behavior of the surface-atmosphere system (e.g., Jakosky and Haberle, 1992).

Many previous investigators have used a combination of groundbased and spacecraft observations to detect or infer the presence of many different minerals on the Martian surface or in the airborne dust [recent detailed reviews can be found in Soderblom (1992), Roush et al. (1993) and Bell (1996)]. Iron-bearing minerals make up the majority of these phases because of (a) the relatively high iron abundance of the Martian surface (Toulmin et al., 1977; Clark et al., 1982) and (b) the highly spectroscopically-active nature of iron in a variety of different oxides, oxyhydroxides, and silicates (e.g., Burns, 1993). In addition, observational detection of iron minerals is perhaps easier than of many other materials because most of the relevant mineral absorption features occur in the visible to short-wave near-IR (‰ 400 to 1200 nm) where the solar reflected flux is highest, and recent advances in telescopic and spacecraft instrumentation have allowed high quality CCD observations to be routinely obtained at these wavelengths.

We are attempting to provide additional, new information on the mineralogy of the Martian surface using multispectral observations with the Hubble Space Telescope (HST). Because the HST instrument suite currently covers only the UV to short-wave near-IR spectral region, the observations were optimized for the detection and characterization of iron-bearing oxide, oxyhydroxide, and silicate minerals. In this paper we discuss the details of the specific observations that were obtained during the 1994-95 apparition of Mars, the data reduction and calibration efforts, and some initial results of our mineralogic investigation.

Observations and Filter Selection

The data were obtained in 15 orbits of HST over 11 different Mars orbital positions between August 23, 1994 and August 21, 1995, using the Wide Field/Planetary Camera 2 (WFPC2) instrument. These dates corresponded to coverage between Mars areocentric longitudes of L_s=336° to L_s=145°, or late northern winter through mid northern summer. This time period allowed for excellent study of the north polar regions, as the sub-Earth latitude ranged up to 26° N; conversely, coverage of surface regions below about 60° S was not possible for most of our observations. The opposition was aphelic (Mars near aphelion at opposition) and the largest apparent angular diameter of Mars in our data set is 13.5 arcsec (roughly a factor of two worse than during a perihelic opposition). This corresponds to a best-case spatial resolution of 2Dsin(b/2) = 22.7 km/pixel, where D is the Earth-Mars distance in km (104 million km at closest approach in February 1995) and b is the angular resolution of the WFPC2 camera (0.045 arcsec/pixel for the Planetary Camera chip PC1). This is approximately the same spatial resolution that was obtained by the ISM imaging spectrometer instrument on the Phobos-2 mission in 1989 (Bibring et al., 1990), and is slightly better than the resolution obtained during the Mariner 6 and 7 mission far encounter phase (Leighton et al., 1969). The observational circumstances of our data set are summarized in Table 1, and Figure 1 provides an illustration of our image coverage and resolution.

Figure 1: Schematic representation of the 1994-95 Mars images obtained by HST. Shown are the seasonal date (L_s) of each set of multispectral observations, the relative size of the planet when it was observed, and the times when multiple central meridians were observed. The observations between L_s=335° and 104° are the HST Cycle 4 five-color imaging sets, and the observation taken from L_s=122° to 145° are the HST Cycle 5 nine-color imaging sets (Table 1).

WFPC2 has a variety of filters and observing modes available for HST observers (Burrows et al., 1995). Our program during HST observing cycle 4 (GO program 5493) utilized the PC1 chip and 5 filters from 255 to 673 nm (Table 2), specifically concentrating on monitoring of atmospheric activity and surface reflectivity and color changes (James et al., 1996). A limited amount of compositional/mineralogic information can also be extracted from these data (e.g., Bell et al., 1995; James et al., 1996), as described in more detail below.

With additional observing time granted to us in HST cycle 5, we were able to expand our Mars program (GO Program 5832) to include four more wavelengths from 740 to 1042 nm. Two of these wavelengths (740 and 860 nm) were obtained using the WFPC2 Linear Ramp Filters (LRFs) and the WF4 chip (Table 2). The LRFs are a set of continuously-variable narrow band-pass filters that allow imaging at ‰ 1.1 to 1.3% spectral resolution at almost any wavelength between 370 to 980 nm (Burrows et al., 1995). While it is a great advantage to be able to image at a precise wavelengths that are most diagnostic of the specific spectral features being sought, there are some important tradeoffs and disadvantages to using the LRFs. For example, images at different wavelengths are obtained by placing the object at specific parts of each of the four WFPC2 detector arrays; thus, obtaining images at a specific wavelength may mean the loss of a factor of two in spatial resolution (for example, using the WF4 chip instead of the PC1 chip results in a spatial scale of 0.0996 arcsec/pixel), or may result in vignetting problems if the object must be located close to the edge of a chip. Additionally, the calibration of images obtained with the LRF is still being developed, and thus users are forced to develop bootstrap calibration techniques (see Appendix A) for the images until the proper in-flight calibration data is obtained and processed by the Space Telescope Science Institute (STScI).

The four additional wavelengths obtained in Cycle 5 provide diagnostic information on Mars surface mineralogy. Specifically, 860 nm was chosen to detect and map the spatial extent of the 6A1Æ4T2(4G) electronic transition band of Fe3+ (ferric iron) that is primarily characteristic of the iron oxide mineral hematite (a-Fe2O3) (Sherman and Waite, 1985; Morris et al., 1985; Bell et al., 1990). Imaging at 953 nm was chosen in order to detect and map the spatial extent of the "1 micron" absorption feature in pyroxenes arising from Fe2+ (ferrous iron) ions primarily in M2 crystallographic sites (e.g., Burns, 1970, 1993; Adams, 1974). The images at 740 nm and 1042 nm provide continuum measurements for these Fe2+ and Fe3+ absorption bands, and the images at 1042 nm also provide additional characterization of the 1-micron band and a way to test for the possible presence of olivine on Mars (Burns, 1970; Huguenin, 1987). In combination with the images at 410, 502, and 673 nm that characterize the shape and curvature of the near-UV reflectance dropoff, the additional 4 filters obtained during HST cycle 5 provide an adequate set of wavelengths for the investigation of iron-bearing minerals on the surface of Mars.

Data Reduction and Calibration

Instrumental Corrections

Raw images were processed using standard HST data reduction procedures as outlined by Lauer (1989) and Holtzman et al. (1995a,b) and using calibration files produced by the WFPC2 Instrument Definition Team (IDT). The steps included correction for analog-to-digital conversion errors, subtraction of bias, superbias, and superdark frames, correction for shutter shading effects, correction for pixel-to-pixel sensitivity variations (flatfielding), and correction of bad pixels and cosmic ray hits. We remove cosmic rays through a combination of automated (low and high-pass filters) and manual processes. Individual and small groups of undefined pixels are repaired by performing an iterated fourth-order polynomial least-squares fit to the neighboring pixels. The high signal-to-noise ratio (SNR, see below) and extended nature of our target precludes the need for correction for charge transfer efficiency variations (Holtzman et al., 1995a).

The instrumental SNR of our short exposure time HST visible and near-IR Mars images is quite high and is limited, ultimately, by quantization of the 12-bit analog to digital electronics and by scattering of bright Mars light in the telescope and instrument optics. An estimate of the SNR in the raw data can be made by examining the standard deviation of sky pixels far from Mars in the images and of scattered-light pixels adjacent to the limb of Mars. The variation of the sky far from Mars and in all wavelengths is ±0.6 to ±0.8 raw data numbers (DN; the gain was 7 e-/DN for most of our images), and typical scattered sky variation is ±2.8 to ±7.5 DN. If we assume that the scattered light component also occurs over the disk of Mars itself, then it is this level of variation that governs the effective SNR of the final data. For example, in the July 1995 image data the scattering-limited SNR ranges from a low of 150-240 for dark surface regions at 740 nm and 1042 nm to a high of 740-880 for bright regions at 673 nm and 953 nm.

Absolute Photometric Calibration

The absolute photometric calibration of WFPC2 data must take into account both the time-variable nature of the system throughput, as well as the extended and inhomogeneous nature (surface albedo features) of Mars. For the first component, we rely on the analyses by Holtzman et al. (1995a,b) and Bagget et al. (1996) of the extensive standard star observation and monitoring programs carried out by STScI. The photometric calibration for the WFPC2 discrete filter observations was derived using the SYNPHOT reference files provided by STScI (July 1995 update; Bagget et al., 1996). These files allow a calibration to be determined that converts corrected DN to flux units (e.g., W cm-2 µm-1) for each filter in our observing program. More details on the derivation of the photometric calibration for the discrete filter observations can be found in Wolff et al. (1997).

The photometric calibration of the LRF has not yet been fully determined by the STScI calibration program. Thus, we devised a bootstrap calibration technique for these images that relies on calibrated groundbased and spacecraft spectra of Mars and the information from STScI that is available on the LRF system throughput. This LRF photometric calibration scheme is outlined in Appendix A.

The flux values for both the discrete filter images and the LRF images were then converted to radiance factor or I/F (I = the actual irradiance received from Mars within each HST pixel and pF = the theoretical irradiance received within each HST pixel from a perfectly diffusing Lambertian surface illuminated by the Sun and viewed at normal geometry at the heliocentric distance of Mars; Hapke, 1981) using the methods of Roush et al. (1992) and Bell et al. (1994). Details are presented in Appendix B.

The absolute photometric errors in this calibration process are conservatively estimated to be approximately 2 to 5% for the discrete filter observations (Holtzman et al., 1995b; Wolff et al., 1997), but are likely 5 to 10% for the LRF observations because of the additional assumptions and uncertainties discussed in Appendix A. We have not applied throughput corrections for UV contamination effects, thus worsening the photometric accuracy for the F255W filter data by possibly more than 5%. However, this filter is not critical for mineralogic studies, and flux values at 255 nm and 336 nm will vary by 5-10% or more anyway depending on the dust and cloud opacity and the Martian airmass (e.g., Clancy et al., 1996a, Wolff et al., 1997). The magnitude of the UV contamination effect is less than 1% for all of the other filters that we used (Holtzman et al., 1995b). Despite these uncertainties, at this current level of accuracy these data represent some of the best calibrated Mars observations ever obtained from Earth.

The second aspect of the absolute photometric calibration process requires a correction for the shape of the point spread function (PSF), which leads to "smoothing" of planetary albedo variations because of the telescope and instrument optics. For example, if uncorrected, this effect will result in dark regions on Mars being spectrally contaminated with light from adjacent bright regions or polar deposits. Similar effects occur in regions of the images around steep intensity gradients associated with clouds or other albedo features. It is often extremely difficult to account for this PSF effect in groundbased telescopic or spacecraft imaging instrumentation. However, one of the "advantages" of the HST primary's spherical aberration is that the PSF is now better characterized for HST and WFPC2 than for perhaps any other optical system ever constructed. The PSF deconvolutions of our HST images were performed using 40 iterations of the damped Richardson-Lucy algorithm with a threshold noise parameter of 3 (White, 1994a,b). Details and examples of this procedure are presented by Wolff et al. (1997).

Registration and Photometric Correction

Perhaps the most difficult aspect of dealing with Mars multispectral data is the fact that the planet rotates significantly during the time it takes to obtain a typical set of images. Thus, it is not possible to simply overlay images at different wavelengths to create ratios or band depth maps; the images must first be registered using map projection software. We performed the transformation from image (x,y) coordinates to projected latitude and longitude using automated software we developed in the IDL programming language. First, the central (sub-Earth) pixel is automatically found by iteratively searching for the limb of the planet and fitting an elliptical curve until a “2 fit parameter is minimized. Next, the date and time from the image headers are automatically used to determine planetary ephemeris information necessary for the map projection (i.e., sub-Earth and sub-Solar latitude and longitude, north polar angle, distance, etc.). Finally, the images can be projected to one of 14 types of cylindrical, equal-area, conic, or polar azimuthal projections. Our software uses fully ellipsoidal map projection formulae (Snyder, 1985; Bugayevskiy and Snyder, 1995), as HST images are sharp enough to detect the small but nonzero flattening of Mars, and spherical projection formulae would result in detectable mapping errors.

Our map projection software also outputs images of the incidence and emission angles for each pixel, thus allowing photometric corrections to be applied in order to properly interpret absolute reflectance levels in all regions within about 60° of the sub-Earth and sub-Solar points. For the photometrically-corrected images discussed here, we used a simple Minnaert correction with a constant "typical" k parameter of 0.6 (e.g., Harris, 1961; de Grenier and Pinet, 1995).

The end result of the data reduction and calibration process is a set of co-registered image cubes (spatial x spatial x spectral), calibrated to absolute I/F units, that can be analyzed using a variety of spectroscopic and imaging spectroscopy analysis tools.

Results and Interpretations

Spectra

Some representative spectra from our July 1995 9-color observations are shown in Figure 2. Figure 3 presents a comparison between the HST spectra and previous calibrated Mars reflectance spectra obtained by McCord and Westphal (1971) and Mustard and Bell (1994). The HST spectra are generally consistent with previous measurements. There is a systematic increase in the reflectivity of the HST spectra at the shortest wavelengths as compared to the 1969 and 1988-89 data. This is likely a manifestation of the increased cloudiness of Mars during the aphelic apparition of 1994-95 (e.g., Martin et al., 1995; Clancy et al., 1996b; James et al., 1996) relative to the earlier observations that were obtained closer to perihelion. The effect of clouds is to increase the reflectivity preferentially at the shortest wavelengths because of the increased Rayleigh scattering efficiency and also because the surface itself is extremely dark in the blue and near-UV.

Figure 2: Representative radiance factor (I/F) spectra extracted from the observations on July 6, 1995 at 1139 UT. (A) Spectra from bright regions: (1) Moab; (2) Xanthe; (3) Chryse; (4) Tempe; (5) North Polar Cap; (6) Ares/Tiu Valles (NASA Mars Pathfinder landing site). (B) Spectra from dark regions: (1) Northern Acidalia; (2) Southern Acidalia; (3) Sinus Meridiani; (4) Oxia Palus; (5) Margaritifer Sinus; (6) Mare Australe; (7) Western side of north polar sand sea; (8) Eastern side of north polar sand sea; (9) Sinus Sabaeus. Each spectrum is from a 3x3 pixel box and the error bar shown represents the variance of the spectra within that box. Each spectrum is offset by 0.05 units from the one below.

The HST 9-color spectra display interesting and diagnostic characteristics that are consistent with previous spectroscopic investigations (e.g., McCord and Westphal, 1971; McCord et al., 1977a; Singer et al., 1979; Bell et al., 1990): (1) The slope of the near-UV absorption edge that gives Mars its distinctive ruddy color varies with reflectivity such that bright regions are typically "redder" than dark regions; (2) There is a reflectivity maximum near 750 nm with a position that is not a function of absolute reflectivity; (3) There is a broad absorption band in the short-wave near IR between the reflectivity maximum near 750 nm and the long wavelength extent of our data at 1042 nm. The near-IR spectral slope between 750 nm and 1042 nm is "red" (reflectivity increasing at longer wavelength) for bright regions, but is neutral to "blue" for dark regions; (4) There is a weak absorption/inflection at 673 nm superimposed on the near-UV absorption edge in the HST spectra of bright regions that is usually absent in the spectra from dark regions [however, see spectrum 4 (Oxia Palus) in Fig. 3b]; (5) The reflectivity of the residual north polar cap is considerably higher than that of the surface at wavelengths shorter than 673 nm and is comparable to or slightly higher than that of the surface at 673 nm and longer. Despite the usual whitish/bluish appearance in typical images of Mars, the cap is in fact quite red.

Figure 3: Comparison of spectra extracted from our HST data set and previous groundbased and spacecraft calibrated spectra of Mars. The McCord and Westphal (1971) data are geometric albedo at 5° phase angle, the Mustard and Bell (1994) composite spectra are in reflectance, and the HST data are in I/F.

Similar overall spectral character is also observed in the other Cycle 5 9-color HST image sequences obtained in August 1995. The 5-color image sequences obtained between August 1994 and May 1995 (Cycle 4) are not able to detect spectral variations longward of 673 nm, but the spectra from 255 to 673 nm exhibit color variations consistent with the Cycle 5 data.

Global Color Variations

Rather than individually examine tens of thousands of spectra, a more fruitful way to explore spectral variations is through the use of color ratio images and similar image-oriented analysis techniques (see Appendix C). James et al. (1996) provided an initial analysis of red to blue (673 nm to 410 nm) color variations and spectral units from the HST Cycle 4 images obtained in February 1995. Analysis of 2-dimensional histogram scatter plots of 673 nm vs. 410 nm I/F values by James et al. (1996) revealed a number of distinct color units and showed that the ubiquitous cloud cover observed near aphelion can substantially influence the interpretation of multispectral images obtained in blue and near-UV wavelengths. Specifically, clouds produce elevated reflectance values shortward of 502 nm and thus frustrate efforts to derive the true surface color ratio values.

We present additional visible-wavelength color ratio data in Figure 4. Figs. 4a and 4b show the reflectances at 673 nm and 410 nm for the Syrtis Major-centered hemisphere as imaged in February 1995, and Fig. 4c shows the ratio of these two images. Fig. 4d presents a 2 dimensional histogram plot of the 673/410 nm color ratio (ordinate) vs. the reflectance at 673 nm (abscissa). The ratio image and histogram both reveal a number of distinct color units, delineated in Figs. 4d and 4e. The 2-D histogram shows a large and diffuse cluster corresponding to the dark, moderate 673/410 nm ratio regions Syrtis Major, Hesperia Planum, and Vastitas Borealis (blue in Figs. 4d and 4e); a compact cluster corresponding to the bright, very high 673/410 nm ratio region encompassing parts of Elysium and Utopia Planitia (magenta); and another rather diffuse cluster corresponding to the bright, high 673/410 nm ratio regions Arabia and Isidis Planitia (yellow). Fig. 4d also shows there to be a substantial amount of spectral mixing between these color units, and Fig. 4e demonstrates that the mixing occurs primarily along the boundaries between the individual units. Other outlier color units in the 2-D histogram correspond primarily to the polar cap and other bright condensate regions (green), and regions along the limb and at high emission angles where wavelength-dependent limb darkening accounts for most of the color variation (red and cyan).

Figure 4: Red/blue color ratio results from the February 1995 HST observations near opposition. All images are shown in a Molleweide projection of the Martian eastern hemisphere north of -60°, with grid lines at every 30° of longitude and 15° of latitude. (A) Map of calibrated I/F at 673 nm, showing prominent Syrtis Major dark albedo feature (center) as well as the bright regions Isidis and Arabia, the retreating north polar cap, and the Hellas Basin (-45°, 300°); (B) Map of calibrated I/F at 410 nm, showing the loss of surface albedo feature contrast in the blue, except for the north polar cap, clouds forming along the morning and evening limbs and in the south polar region, and a discrete cloud over the volcano Elysium (+20°, 220°); (C) Ratio of 673 nm (image A) to 410 nm (image B). The image has been enhanced so that black corresponds to a ratio value of 0.5 and white corresponds to a ratio value of 6.2; (D) Two-dimensional (2-D) histogram of the 673/410 nm ratio (Fig. 4c) vs. radiance factor at 673 nm (Fig. 4a). This and subsequent 2-D histograms are shown so that a higher frequency of occurrence is seen as a darker and denser cluster. Here, black corresponds to 5 or more occurrences of each data value in each particular (x,y) bin, and white corresponds to 0 occurrences. Different clusters of data have been grouped by color; (E) Spectral unit map derived from the histogram units in (D). This unit map provides a representative example of how spectral variations seen in ratio images can be correlated with specific surface regions or geologic/albedo units. See text for details.

These same general color ratio units can also be identified in our Cycle 5 HST images in the Syrtis region and in other parts of the planet not imaged in Cycle 4 (Figure 5a). The fine details are slightly different between the February 1995 Cycle 4 (L_s=63°) and July 1995 Cycle 5 data (L_s=122°) because of the different distribution of clouds at this later seasonal date. In general, our Cycle 5 HST images have the ability to extend previous groundbased and spacecraft color unit results into the short-wave near-IR, where additional mineralogic information can be obtained from the broad region of 750-1050 nm absorption that results from a combination of ferric and ferrous minerals. Figures 5b, 5c, and 5d show examples of three color ratio and 2-D histogram pairs from our near-IR data.

Figure 5: Initial color ratio results from the July 1995 HST observations. All of the ratio images presented here are stretched to encompass the same range as the y-axis of their corresponding histogram, and are shown on a Molleweide map projection centered on 30° W longitude, 0° latitude. Pixels having an incidence angle or emission angle greater than 60° were removed from both the maps and the histograms. An estimate of the 1-s x-axis and y-axis error bar is shown for each 2-D histogram (see Appendix C). (A) 673/410 nm color ratio image and 2-D histogram of 673/410 nm ratio vs. 673 nm radiance factor; (B) 740/1042 nm color ratio and histogram of ratio vs. 1042 nm radiance factor; (C) 860/953 nm color ratio and histogram of ratio vs. 953 nm radiance factor; (D) 953/1042 nm color ratio and histogram of ratio vs. 953 nm radiance factor.

The ratio between 740 nm and 1042 nm (Fig. 5b) is a measure of the overall near-IR spectral slope. The near-IR slope is sensitive to mineralogy (especially Fe2+-bearing minerals with a strong 1-µm absorption feature), the opacity and composition of Mars atmospheric aerosols, and the presence of particle coatings or rinds (e.g., Fischer and Pieters, 1993; Erard et al., 1994). Fig. 5b shows that the 740/1042 nm color units occur in two primary clusters (linked by a well-defined mixing trend), and that the low albedo regions have approximately 20% higher 740/1042 nm ratio values than the high albedo regions. This result can also be seen in the individual spectra of Fig. 2: darker regions have flat or negative near-IR spectral slopes while brighter regions have positive near-IR spectral slopes.

The ratio between 860 nm and 953 nm (Fig. 5c) is a measure of the relative strengths of the 860 nm ferric absorption band and the 953 nm ferrous absorption band. Fig. 5c (and Fig. 2) reveals that the low albedo regions generally exhibit flat spectra between 860 and 953 nm, although there is a roughly ±5% 860/953 nm color ratio value variation among dark regions. The brightest regions exhibit "red" 860/953 nm spectral slopes (860/953 ratio values < 1.0), and also show ±5% color ratio variations. There is a clear mixing trend between these endmember color ratio units.

The ratio between 953 nm and 1042 nm (Fig. 5d) provides a way to characterize the shape of the "1-µm" pyroxene absorption feature, which is centered near 920 to 950 nm for low-Ca orthopyroxenes and near 950-1000 nm for high-Ca clinopyroxenes (e.g., Adams, 1974; Pinet and Chevrel, 1990; Mustard et al., 1993). The global variation in the 953/1042 nm ratio is small (mean±1 sigma = 0.92±0.03) and there is only a weak correlation between albedo and 953/1042 nm ratio. However, Fig. 5d demonstrates a stunning example of one of the greatest assets of our data set: spatial resolution. A number of small surface regions (from 60-100 km in size) exhibit significantly lower 953/1042 nm ratio values than the rest of the planet, meaning that these regions have increased 953 nm absorption. These regions are associated with specific impact craters in the Acidalia hemisphere, with the Nili Patera and Meroe Patera calderae of Syrtis Major, and with the small dark teardrop-shaped feature to the northeast of Syrtis Major (referred to as Nubis Lacus in classical albedo maps; it does not appear to have any unique geologic characteristic).

Absorption Band Depth Variations

While color ratios provide diagnostic information on spectral slope variations, we chose our Cycle 5 imaging wavelengths to allow for the mapping of the actual absorption features associated with iron-bearing minerals on the Martian surface. Specifically, we can use the images at 740 nm and 1042 nm as continuum points and spatially map the strength of the 860 nm (ferric) and 953 nm (ferrous) absorption bands using the band depth mapping techniques defined by Clark and Roush (1984) and Bell and Crisp (1993). Details of the method and the technique used to estimate errors in the band depth maps are provided in Appendix C.

Figure 6a displays a map of the 953 nm pyroxene absorption feature relative to a linear continuum defined between 740 nm and 1042 nm. This map reveals the power of HST as a mineralogic mapping tool. It is apparent that the 953 nm band is much stronger in the dark regions than in the bright regions, consistent with the spectra of Fig. 2 and the color ratio data of Fig. 5. However, the strength of the 953 nm band varies within the dark regions: the band is strongest in Syrtis Major and other nearby equatorial dark regions, but it is weaker in the northern dark regions Acidalia and Utopia/Borealis.

Figure 6b shows a map of the 860 nm ferric oxide absorption feature relative to the same linear continuum between 740 nm and 1042 nm. This map reveals that the strength of the 860 nm band seen in our HST Mars spectra exhibits a weak inverse correlation with albedo: dark regions generally have a stronger 860 nm feature than bright regions by an average of 3 to 4%. This relationship is difficult to derive from examining just a few spectra (as in Fig. 2). This result is consistent with previous groundbased and Phobos-2 observations that showed evidence for increased "ferric" absorption in Mars dark regions (e.g., Bell, 1992; Murchie et al., 1993; Merényi et al., 1996).

Figure 6: Initial band depth mapping results from the July 1995 HST observations. All of the band depth images presented here are stretched to encompass the same range as the y-axis of their corresponding histogram, and are shown on a Molleweide map projection centered on 30° W longitude, 0° latitude. Pixels having an incidence angle or emission angle greater than 60° were removed from both the maps and the histograms. An estimate of the 1-s x-axis and y-axis error bar is shown for each 2-D histogram. See Appendix C for a discussion of the band depth mapping technique and error analysis method. (A) 953 nm band depth defined relative to a linear continuum between 740 nm and 1042 nm. There is a clear trend above the error indicating that the low albedo regions generally exhibit a 5-10% deeper 953 nm absorption than bright regions; (B) 860 nm band depth defined relative to a linear continuum between 740 nm and 1042 nm. There is a weak correlation above the 1-s level between 860 nm band depth and albedo such that low albedo regions exhibit a ‰3-5% deeper 860 nm band than high albedo regions; (C) 673 nm band depth defined relative to a linear continuum between 502 nm and 740 nm. There is no systematic correlation between 673 nm band depth and albedo, although the largest variation is seen among intermediate and low albedo regions.

Another interesting result is shown in Fig. 6c, which is a map of the depth of the 673 nm band seen in the spectra of Fig. 2 relative to a linear continuum defined between 502 nm and 740 nm. The map and the histogram reveal the curvature of the Martian spectrum between 502 and 740 nm, which may be related to the degree of crystallinity of surface iron mineralogy (e.g., Guinness et al., 1987; Morris and Lauer, 1990; Morris et al., 1997). While there is no systematic trend above the errors in 673 nm band depth vs. albedo, the 673 nm band varies such that the spectra of most surface regions are convex (negative band depth in Fig. 6c). Some bright regions and a smaller number of isolated intermediate and dark regions exhibit concave spectra (band depth > 0) between 502 and 740 nm (cf. Fig. 2), however.

Discussion

The results presented above provide new information on the spectroscopic variability of the Martian surface. For example, color ratio images and 2-D histogram analysis reveals that the classical bright regions can be subdivided into at least two distinct red/blue color units that occur in spatially distinct regions in Isidis and Utopia Planitia (Fig. 4d and Fig. 5a). This result is consistent with the color ratio and 2-D histogram analyses of Viking Orbiter imaging by Soderblom et al. (1978) and McCord et al. (1982). While the Viking data have higher spatial resolution and thus can reveal finer details associated with specific craters or other features, it was restricted in wavelength to only three bands between 450 nm and 590 nm. The HST images can thus extend the color ratio results into the near-IR and provide additional diagnostic information keyed to specific mineralogic variations.

Our HST near-IR color ratio results are consistent with previous groundbased near-IR imaging observations by McCord et al. (1977b) and Pinet and Chevrel (1990), and they extend these results by providing higher spatial resolution measurements that are free from the typical terrestrial atmospheric contamination problems encountered between 750 and 1050 nm (e.g., O2, H2O). For example, the overall appearance of the HST near-IR slope image (Fig. 5b) is similar to the ratio map of Pinet and Chevrel (1990): bright regions are spectrally flat in the near-IR while dark regions are "blue". However, Figs. 5d and 6a reveal individual craters and caldera with much stronger 953 nm pyroxene absorption features than typical dark regions. Comparison with the 953/1042 nm ratio image (Fig. 5d) indicates that these regions of increased 953 nm absorption are likely not caused by the presence of olivine or very high-Ca pyroxene, because there is no associated strong increase in the 953/1042 nm ratio value for these areas. The lack of atmospheric interference/turbulence and the exceptional ability to model and correct the HST PSF (see Wolff et al., 1997) allow this level of spatial detail to be obtained in the near-IR for the first time. The implication is that there are small regions of the Martian surface that exhibit a very strong pyroxene absorption band either because (a) there is simply a higher abundance of pyroxene in the rocks and soils of these regions; (b) the pyroxene in these regions is "fresher" or less altered to ferric phases than in other regions, and/or (c) the particle size of the pyroxene-bearing surface minerals is larger, thus leading to increased 953 nm absorption.

The ubiquity of the 860 nm absorption feature and its inverse correlation with albedo came as somewhat of a surprise, especially considering the well-known correlation between red/blue color ratio and albedo. However, the apparent increase in ferric mineral content in some dark regions has been noted by previous groundbased observers, and these HST data provide confirmation. How could dark regions have a stronger 860 nm absorption band yet a shallower visible spectral slope? One possible solution is that the visible spectral slope is dominated by poorly crystalline ferric-rich material similar to the nanophase ferric oxide pigments studied by Morris and Lauer (1990), Morris et al. (1993, 1997) and others. This pigmenting material does not have an 860 nm absorption feature but it does have a strong red spectral slope. The 860 nm band could then arise from a well-crystalline ferric oxide phase like hematite occurring preferentially in the lower albedo regions. The additional absorption at 860 nm in the dark regions may result from more of this ferric phase occurring in these regions. This possibility is supported by the observation of greater 673 nm band depth variability in low albedo regions (Fig. 6c), because many ferric oxides also exhibit an absorption in the 600-700 nm region as well as the stronger feature centered near 850 900 nm. Alternately, the additional 860 nm absorption in the dark regions may be caused by a band centered longward of 860 nm that has a broad wing extending down through 860 nm. In this case, the origin of the additional 860 nm absorption could be ascribed to a very low-Ca pyroxene or an iron oxyhydroxide phase like goethite. Given the coarse spectral sampling provided in our HST data set and the broad overlap in absorption bands possible for various ferric and ferrous phases (e.g., Morris et al., 1995), it is not possible to uniquely determine the origin of this additional 860 nm absorption. The optimal way to provide this discrimination would be with high spectral resolution and high spatial resolution observations.

Conclusions

This paper presents the details of the collection and calibration of images of Mars obtained by HST during 1994-1995, as well as some initial analyses. The images were obtained between 255 nm and 1042 nm as part of a long-term HST investigation of seasonal phenomena on Mars. The primary goal of obtaining the near-IR images discussed here is the study of Martian surface mineralogy. The calibration exercise performed on the data resulted in a spectacular set of images that exhibit ‰5% photometric accuracy from 410 nm to 1042 nm. Our initial scientific examination of these calibrated data shows the images to compare favorably with previous groundbased and spacecraft imaging and spectroscopic observations. Some of the most salient results found to date include:

(1) Discrimination of at least two distinct red/blue color units within the classical bright regions, with one unit having a 20-25% higher 673/410 nm ratio value than the other, possibly because of an increase in nanophase ferric iron abundance.

(2) Mapping of near-IR spectral variations on a scale unprecedented in previous Earth-based telescopic observations and covering many regions not yet imaged by spacecraft in the near-IR. The maps reveal general correlation between 1042/740 nm spectral ratio and albedo, and the increased spatial resolution allows the near-IR color properties of individual craters and small geologic units to be investigated.

(3) Mapping of the depth of the 860 nm ferric absorption band reveals that all surface regions exhibit a band ranging from 5% to 15% deep. The spatial distribution of this band is not a strong function of albedo, unlike the red/blue spectral slope. These HST data confirm previous groundbased observations indicating that many of the classical dark regions (including Acidalia and Syrtis) exhibit ‰3 to 5% deeper 860 nm absorption feature than the classical bright regions. The origin of this additional 860 nm absorption in the dark regions may be related to a greater abundance of a well-crystalline ferric phase or a very low-Ca pyroxene.

(4) Mapping of the depth of the 953 nm ferrous absorption band shows large variations in the depth of the "1-µm" feature. Bright regions typically have either no band or only a weak absorption, while dark regions exhibit a 953 nm band ranging from ‰7% to 15% deep. The increases in 953 nm band depth within individual craters, calderas, and other small geologic units in the dark regions are interpreted as indicating either an increase in the abundance, "immaturity", and/or particle size of pyroxene in these areas.

Appendix A: Photometric Calibration of LRF Images

The scheme that we developed to determine the LRF photometric calibration proceeded as follows: We used the STScI/WFPC2 Exposure Time Calculator (ETC) software for extended objects to estimate the expected Mars DN value for each LRF wavelength (at the appropriate gain and exposure time settings). The current version of the ETC uses pre-flight calibration data in order to provide an estimate of the photometric performance of the LRFs, and thus does not take into account the likely differences between pre-flight and in-flight performance and calibration. To estimate the photometric calibration of the LRF images, we input the appropriate Mars surface brightness (mag/arcsec2) and use a spectral type G5 stellar spectrum as the source to approximate reflected sunlight. An estimated photometric scale factor (in W cm-2 µm-1 DN-1) is then obtained to convert DN to flux by dividing the input Mars surface brightness by the DN value estimated by the ETC.

In comparison with calibrated groundbased spectra of Mars, the ETC-based LRF calibration scheme yields 740 and 860 nm flux values that are systematically approximately 20% too high. This is likely the result of compounding errors from the various system throughput estimates made by STScI in developing the ETC in the absence of a completely characterized LRF in-flight calibration, and from the derivation of the solar flux convolved through the LRF bandpasses (the transmission functions of the LRF filters were only approximated and the in-flight system efficiency of the WFPC2-LRF combination has not yet been determined; see Appendix B). Given the various uncertainties involved, a 20% absolute error appears thoroughly reasonable.

In order to correct for this systematic offset as best we can, we used the groundbased/ISM composite reflectance spectra of Mustard and Bell (1994) to help determine a correction factor for the 740 and 860 nm LRF data. This was a two-step process: First we used the LRF photometric calibration values derived above and the solar flux values determined in Appendix B to calibrate the data to I/F, and then we extracted a typical bright region spectrum from the Isidis region in the 6 July 1995 image cube from 0336 UT (Table 1). We then examined the Mars bright region composite spectrum of Spot 41 (Olympus-Amazonis) from Mustard and Bell (1994) and determined the ratios of the composite spectrum's reflectances to the HST I/F values at 740 and 860 nm. The average of these ratios was found to be 0.80. Thus, the LRF photometric calibration values derived above are multiplied by 0.8 to yield a more accurate estimate of the actual I/F values of the HST data. Scaling both of the LRF images in this way by the same amount also preserves the value of the ratio between these wavelengths. We note that it is not critical that the exact same region of the planet is used for this scaling technique: what really matters is that two spectra are chosen that are both from "typical" bright regions (thus likely having similar mineralogy) and that both have similar reflectance levels. The Olympus-Amazonis spectrum of Mustard and Bell (1994) and the HST Isidis spectrum satisfy these criteria.

Appendix B: Determination of I/F Values

The flux values for both the discrete filter images and the LRF images were converted to radiance factor or I/F using the methods of Roush et al. (1992) and Bell et al. (1994) modified for the square pixels of HST (as opposed to circular apertures). This modification results in the expression for FM,the theoretical irradiance received within each HST pixel from a perfectly diffusing Lambertian surface illuminated by the Sun and viewed at normal geometry at the heliocentric distance of Mars [equation 8 from Roush et al. (1992)] becoming:

where is the solar irradiance at 1 AU, ‡ is the angular size of an HST pixel in arcsec, and D is the heliocentric distance of Mars in AU. Values of at each of our HST wavelengths (Table 2) were obtained by using the World Meteorological Organization (WMO) solar flux spectrum of Wehrli (1985, 1986). For the discrete HST filters, the WMO solar spectral data was convolved with the system efficiency function for each WFPC2 filter as described in Wolff et al. (1997). For the LRFs, the system efficiency of the filters in flight has not yet been provided by STScI or the WFPC2 IDT, so we estimated by simply convolving a gaussian filter transmission profile having a center at each of the LRF wavelengths and a FWHM appropriate for each wavelength (Burrows et al., 1995) with the full-resolution WMO solar flux spectrum. There is obviously much uncertainty in this determination of for the LRFs (see Appendix A), but the values can be refined once the results of the ongoing STScI LRF calibration program are completed.

Final calibrated I/F values were derived by dividing the Mars flux values determined using the photometric calibrations defined by Wolff et al. (1997) and in Appendix A above (IM) by the values of FM determined using equation B1.

Appendix C: Color Ratios, Band Depth Maps, and Error Analysis

Color ratios are formed by simple coregistration and division of two images. Band depth maps are calculated using three coregistered images and a technique based on Bell and Crisp (1993): images on the short wavelength side (IS, wavelength = lS) and long wavelength side

(IL, wavelength = lL) of an absorption band at wavelength lB are used to construct a continuum image (IC) that represents the value of each pixel at lB along a line defined by the pixel values at lS and lL. The fractional distance, f, between the absorption band wavelength and the short wavelength continuum point is (lB - lS) / (lL - lS), and thus the continuum image IC is simply equal to (1 - f)IS + fIL. The band depth is then defined as 1 - (IB / IC), where IB is the image at lB. This definition of band depth allows for an intuitive display of results: areas of an image having more absorption appear brighter.

Error propagation using standard derivative-based error formulae (e.g., Bevington, 1969) yields the following equations for calculating errors in ratios (IR) and band depth maps (IBD):

Knowledge of the errors on each of the images (sS, sB, sL) should come from a rigorous formal propagation of errors along the data reduction pipeline. However, this is not possible for our HST data because the errors on many of the standard STScI calibration products and reduction algorithms used in the pipeline are unknown or indeterminate. Instead, for our analysis (Figs. 5 and 6) we rely on a more empirical approach by adopting the error bars in the representative bright and dark region spectra of Fig. 3 as the "typical" errors for our HST data. These are not true instrumental errors, per se, but are measures of the variation of homogeneous surface units over a 3x3 or 5x5 pixel surface region. These errors are used as the [sS, sB, sL] values in equations C1b and C2b and sR and sBD are calculated separately for bright (Fig. 3a) and dark (Fig. 3b) regions for each ratio image or band depth map. The larger of the calculated errors for bright and dark regions is shown as the vertical error bar in Figs. 5 and 6; the horizontal error bar on the I/F values comes directly from the data in Fig. 2.

Acknowledgements. We are extremely grateful to WFPC2 IDT members David Crisp and Karl Stapelfeldt for their assistance with determining the best possible flatfields for the LRF images. We thank Andy Switala and Tom Daley for crucial help in developing the automated map projection and data analysis software, and Paul Helfenstein for assistance with the voodoo art of photometric calibration. We thank B. Ray Hawke and a mystery reviewer for providing a careful review of the initial manuscript. Funding for this research was provided by grants from the NASA Planetary Geology and Geophysics Program (NAGW-5062) and the Space Telescope Science Institute. This research was based on observations with the NASA/ESA Hubble Space Telescope obtained at the Space Telescope Science Institute, which is operated by Association of Universities for Research in Astronomy under NASA contract NAS5-26555.
References

Adams, J.B., Visible and near-infrared diffuse reflectance spectra of pyroxenes as applied to remote sensing of solid objects in the solar system. J. Geophys. Res., 79, 4829-4836, 1974.

Bagget, S., W. Sparks, C. Ritchie, and J. MacKenty, Contamination correction in SYNPHOT for WFPC-2 and WF/PC-1, WFPC2 Instrument Science Report 96-02, Space Telescope Science Institute, Baltimore, 1996.

Bell, J.F., III, Charge-Coupled Device Imaging Spectroscopy of Mars. 2. Results and Implications for Martian Ferric Mineralogy, Icarus, 100, 575-597, 1992.

Bell, J.F., III, Iron, sulfate, carbonate, and hydrated minerals on Mars, in "Mineral Spectroscopy: A Tribute to Roger G. Burns," Geochemical Society Special Publication 5 (M.D. Dyar, C. McCammon, and M.W. Schaefer, eds.), 359-380, 1996.

Bell, J.F., III, and D. Crisp, Groundbased Imaging Spectroscopy of Mars in the Near-Infrared: Preliminary Results, Icarus, 104, 2-19, 1993.

Bell, J.F., III, T.B. McCord, and P.D. Owensby, Observational Evidence of crystalline iron oxides on Mars, J. Geophys. Res., 95, 14447-14461, 1990.

Bell, J.F., III, J.B. Pollack, T.R. Geballe, D.P. Cruikshank, and R. Freedman, Spectroscopy of Mars from 2.04 to 2.44 µm during the 1993 opposition: Absolute calibration and atmospheric vs. mineralogic origin of narrow absorption features, Icarus, 111, 106-123, 1994.

Bell, J.F. III, P.B. James, L.J. Martin, R.T. Clancy, S.W. Lee, and D. Crisp, Mars surface mineralogy from Hubble Space Telescope multispectral imaging: 1994 pre-opposition data, Lunar Planet. Sci. Conf. XXVI, 95-96, 1995.

Bevington, P.R., Data Reduction and Error Analysis for the Physical Sciences. 336 pp., McGraw-Hill, New York, 1969.

Bibring, J.-P., Combes, M., Langevin, Y., Cara, C., Drossart, P., Encrenaz,T., Erard, S., Forni, O., Gondet, B., Ksanfomality, L.V., Lellouch, E., Masson, P., Moroz, V.I., Rocard, F., Rosenqvist, J., Sotin, C., and Soufflot, A. ISM observations of Mars and Phobos: First results. Proc. Lunar Planet. Sci. Conf. 20th, 461-471, 1990.

Bugayevskiy, L.M., and J.P. Snyder, Map Projections: A Reference Manual, Taylor and Francis Ltd., 1995.

Burns, R.G., Mineralogical Applications of Crystal Field Theory, Cambridge Univ. Press, New York, 224 pp., 1970.

Burns, R.G., Origin of Electronic Spectra of Minerals in the Visible-Near Infrared Region. In Remote Geochemical Analysis: Elemental and Mineralogical Composition , ed. C. Pieters and P. Englert, pp. 3-29. Cambridge: Cambridge Univ. Press, 1993.

Burrows, C.J. (editor) Wide Field and Planetary Camera 2 Instrument Handbook, version 3.0, Space Telescope Science Institute Publication, STScI, Baltimore MD, June 1995.

Clancy, R. T., M. J. Wolff, P. B. James, E. Smith, Y. N. Billawala, S. W. Lee, and M. Callan, Mars ozone measurements near the 1995 aphelion: Hubble Space Telescope ultraviolet spectroscopy with the Faint Object Spectrograph, J. Geophys. Res., 101, 12,777-12,784, 1996a.

Clancy, R. T., A. W. Grossman, M. J. Wolff, P. B. James, D. J. Rudy, Y. N. Billawala, B. J. Sandor, S. W. Lee, and D. O. Muhleman, Water vapor saturation at low altitudes around aphelion: A key to Mars climate?, Icarus, 122, 36-62, 1996b.

Clark, R.N., and T.L. Roush, Reflectance spectroscopy: Quantitative analysis techniques for remote sensing applications. J. Geophys. Res., 89, 6329-6240, 1984.

Clark, B.C., A.K. Baird, R.J. Weldon, D.M. Tsusaki, L. Schnabel, and M.P. Candelaria, Chemical composition of Martian fines, J. Geophys. Res., 87, 1005910067, 1982.

de Grenier, M., and P.C. Pinet, Near-opposition Martian limb darkening: Quantification and implication for visiblenear-infrared bidirectional reflectance studies, Icarus, 115, 354-368, 1995.

Erard, S., J. Mustard, S. Murchie, J.-P. Bibring, P. Cerroni, and A. Coradini, Martian aerosols: Near-infrared spectral properties and effects on the observation of the surface, Icarus, 111, 317-334, 1994.

Fanale, F.P., S.E. Postawko, J.B. Pollack, M.H. Carr, and R.O. Pepin, Mars: Epochal climate change and volatile history, in Mars, edited by H.H. Kieffer, B.M. Jakosky, and M.S. Matthews, pp. 1135-1179, Univ. of Ariz. Press, Tucson, 1992.

Fischer, E.M., and C.M. Pieters, The continuum slope of Mars: Bidirectional reflectance investigations and applications to Olympus Mons, Icarus, 102, 185-202, 1993.

Guinness, E.A., R.E. Arvidson, M.A. Dale-Bannister, R.B. Singer, and E.A. Bruckenthal, On the spectral reflectance properties of materials exposed at the Viking landing sites. J. Geophys. Res., 92, E575-E587, 1987.

Hapke, B., Bidirectional reflectance spectroscopy, 1, Theory, J. Geophys. Res., 86, 3039-3054, 1981.

Harris, D.L., Photometry and colorimetry of planets and satellites, in The Solar System. III. Planets and Satellites, pp. 272-342. (G.P. Kuiper and B. Middlehurst, eds.), Univ. of Chicago Press, Chicago, 1961.

Holtzman, J. A., J. J. Hester, S. Casertano, J. T. Trauger, A. M. Watson, G. E. Ballester, C. J. Burrows, J. T. Clarke, D. Crisp, and E. Evans, The performance and calibration of WFPC2 on the Hubble Space Telescope, Pub. Astron. Soc. Pac., 107, 156-178, 1995a.

Holtzman, J.A., C.J. Burrows, S. Casertano, J.J. Hester, J.T. Trauger, A.M. Watson, and G. Worthey, The photometric performance and calibration of WFPC2, Pub. Astron. Soc. Pac., 107, 1065-1093, 1995b.

Huguenin, R.L., The silicate component of martian dust. Icarus, 70, 162-168, 1987.

Jakosky, B.M., and R.M. Haberle, The seasonal behavior of water on Mars, in Mars, ed. H.H. Kieffer, B.M. Jakosky, and M.S. Matthews, pp. 969-1016, Univ. Arizona Press, Tucson, 1992.

James, P.B., J.F. Bell, III, R.T. Clancy, S.W. Lee, L.J. Martin, and M.J. Wolff, Global imaging of Mars by Hubble Space Telescope during the 1995 opposition, J. Geophys. Res., 101, 18,883-18,890, 1996.

Lauer, T.R., The reduction of Wide Field/Planetary Camera images, Pub. Astron. Soc. Pac., 101, 445-469, 1989.

Leighton, R.B., N.H. Horowitz, B.C. Murray, R.P. Sharp, A.G. Herriman, A.T. Young, B.A. Smith, M.E. Davies, and C.B. Leovy, Television observations from Mariners 6 and 7, in Mariner-Mars 1969: A Preliminary Report, NASA Special Publication 225, pp. 37-82, U.S. Government Printing Office, Washington DC, 1969.

Martin, L.J., J.F. Bell, III, P.B. James, S.W. Lee, and D. Thompson, "Mars Watch" observations from the Lowell Observatory, and observed cloudiness in 1994-95: Possible implications for dust activity Mars Telescopic Observations Workshop, LPI Tech. Rtp. 95-04, pp. 19-20, 1995.

McCord, T.B. and J.A. Westphal, Mars: Narrowband photometry, from 0.3 to 2.5 microns, of surface regions during the 1969 apparition. Astrophys. J., 168, 141-153, 1971.

McCord, T.B., R.L. Huguenin, D. Mink, and C. Pieters, Spectral reflectance of Martian areas during the 1973 opposition: Photoelectric filter photometry, 0.33-1.10 µm., Icarus, 31, 25-39, 1977a.

McCord, T.B., R.L. Huguenin, and G.L. Johnson, Photometric imaging of Mars during the 1973 opposition. Icarus, 31, 293-314, 1977b.

McCord, T.B., R.B. Singer, B.R. Hawke, J.B. Adams, D.L. Evans, J.W. Head, P.J. Mouginis-Mark, C.M. Pieters, R.L. Huguenin, and S.H. Zisk, Mars: Definition and characterization of global surface units with emphasis on composition. J. Geophys. Res., 87, 10,129-10,148, 1982.

Merényi, E., R.B. Singer, and J.S. Miller, Mapping of spectral variations on the surface of Mars from high spectral resolution telescopic images, Icarus, 124, 280-295, 1996.

Morris, R.V., and H.V. Lauer, Jr., Matrix effects for reflectivity spectra of dispersed nanophase (superparamagnetic) hematite with application to martian spectral data. J. Geophys. Res., 95, 5101-5109, 1990.

Morris, R.V., H.V. Lauer, Jr., C.A. Lawson, E.K. Gibson, Jr., G.A. Nace, and C. Stewart, Spectral and other physicochemical properties of submicron powders of hematite (ÿ-Fe2O3), maghemite (M-Fe2O3), magnetite (Fe3O4), goethite (ÿ-FeOOH), and lepidocrocite (M-FeOOH), J. Geophys. Res., 90, 3126-3144, 1985.

Morris, R.V., D.C. Golden, J.F. Bell, III, H.V. Lauer, Jr., and J.B. Adams, Pigmenting agents in Martian soils: Inferences from spectral, Mössbauer, and magnetic properties of nanophase and other iron oxides in Hawaiian palagonitic soil PN-9, Geochim. Cosmochim. Acta, 57, 4597-4609, 1993.

Morris, R.V., D.C. Golden, J.F. Bell, III, and H.V. Lauer, Jr., Hematite, pyroxene, and phyllosilicates on Mars: Implications from oxidized impact melt rocks from Manicouagan Crater, Quebec, Canada, J. Geophys. Res., 100, 5319-5329, 1995.

Morris, R.V., D.C. Golden, and J.F. Bell, III, Low-temperature reflectivity spectra of red hematite and the color of Mars, J. Geophys. Res., this issue, 1997.

Murchie, S., J. Mustard, J. Bishop, J. Head, C. Pieters, and S. Erard, Spatial variations in the spectral properties of bright regions on Mars. Icarus, 105, 454-468, 1993.

Mustard, J.F., and J.F. Bell, III, New composite reflectance spectra of Mars from 0.4 to 3.14 µm, Geophys. Res. Lett., 21, 353-356, 1994.

Mustard, J.F., S. Erard, J.-P. Bibring, J.W. Head, S. Hurtrez, Y. Langevin, C.M. Pieters, and C.J. Sotin, The surface of Syrtis Major: Composition of the volcanic substrate and mixing with altered dust and soil, J. Geophys. Res., 98, 3387-3400, 1993.

Pinet, P., and S. Chevrel, Spectral identification of geological units on the surface of Mars related to the presence of silicates from Earth-based near-infrared telescopic charge-coupled device imaging. J. Geophys. Res., 95, 14435-14446, 1990.

Roush, T.L., E.A. Roush, R.B. Singer, and P.G. Lucey, Estimates of absolute flux and radiance factor of localized regions on Mars in the 2-4 µm wavelength region, Icarus, 99, 42-50, 1992.

Roush, T.L., D.L. Blaney, and R.B. Singer, The surface composition of Mars as inferred from spectroscopic observations. In Remote Geochemical Analysis: Elemental and Mineralogical Composition, ed. C. Pieters and P. Englert, pp. 367-393. Cambridge: Cambridge Univ. Press, 1993.

Sherman, D.M., and T.D. Waite, Electronic spectra of Fe3+ oxides and oxide hydroxides in the near-IR to near-UV. Amer. Mineral., 70, 1262-1269, 1985.

Singer, R.B., T.B. McCord, R.N. Clark, J.B. Adams, and R.L. Huguenin, Mars surface composition from reflectance spectroscopy: A summary. J. Geophys. Res., 84, 8415-8426, 1979.

Snyder, J.P., Map Projections Used by the U.S.G.S., U.S. Geol. Surv. Bulletin 1532, 1985.

Soderblom, L.A., The composition and mineralogy of the martian surface from spectroscopic observations: 0.3-50 µm. In Mars, ed. H.H. Kieffer, B.M. Jakosky, and M.S. Matthews, pp. 557-593. Tucson: Univ. Arizona Press, 1992.

Soderblom, L.A., K. Edwards, E.M. Eliason, E.M. Sanchez, and M.P. Charette, Global color variations on the martian surface, Icarus, 34, 446-464, 1978.

Toulmin, P., III, A.K. Baird, B.C. Clark, K. Keil, H.J. Rose, Jr., R.P. Christian, P.H. Evans, and W.C. Kelliher, Geochemical and Mineralogical Interpretation of the Viking inorganic chemical results, J. Geophys. Res., 82, 4625-4634, 1977.

Wehrli, C. (Ed.) World Radiation Center Publication No. 615, July 1985.

Wehrli, C. (Ed.) World Climate Research Programme Publication Series, No. 7, WMO ITD-No. 149, 119-126, October 1986.

White, R. L., Image restoration using the Damped Richardson-Lucy method, in Astronomical Data Analysis Software and Systems III, edited by D. R. Crabtree, R. J. Hanisch, and J. Barnes, ASP Conference Series,v . 61, 292-295, 1994a.

White, R. L., Image restoration using the Damped Richardson-Lucy method, in The Restoration of HST Images and Spectra II, edited by R. J. Hanisch, and R. L. White, Space Telescope Science Institute, 104-110, 1994b.

Wolff, M.J., S.W. Lee, R.T. Clancy, L.J. Martin, P.B. James, and J.F. Bell, III, 1995 observations of Martian dust storms using the Hubble Space Telescope, J. Geophys. Res., this issue, 1997.

Table 1. 1994-1995 HST Mars Images from GO Program 5493 and 5832
UT Date (YYMMDD)	Time^a (UT)	Wavelengths (nm)	Diameter (arcsec)	SE Lat (š)	Phase (š)	L_s	Resolution^b
HST Cycle 4 Data
940823	2311	255, 336, 410, 502, 673	5.2	5.1	34.4	335.7	59.1
940919	1526	255, 336, 410, 502, 673	5.7	11.8	36.5	349.7	54.0
941020	1154	255, 336, 410, 502, 673	6.5	17.7	38.3	5.3	46.8
941118	0546	255, 336, 410, 502, 673	7.8	21.0	38.0	19.1	39.3
950102	1007	255, 336, 410, 502, 673	11.2	21.8	28.0	39.7	27.3
950224	1711	255, 336, 410, 502, 673	13.5	17.3	10.0	63.1	22.7
950225	0117	255, 336, 410, 502, 673	13.5	17.2	10.3	63.6	22.7
950225	0918	255, 336, 410, 502, 673	13.4	17.2	10.5	63.7	22.7
950408	1933	255, 336, 410, 502, 673	9.8	18.1	32.6	81.9	31.4
950528	0157	255, 336, 410, 502, 673	6.8	23.0	41.7	104.1	45.2
HST Cycle 5 Data
950706	0336	255, 336, 410, 502, 673, 740, 860, 953, 1042	5.6	25.7	38.9	122.1	55.1
950706	1139	255, 336, 410, 502, 673, 740, 860, 953, 1042	5.5	25.8	38.9	122.2	55.2
950711	2335	255, 336, 410, 502, 673, 740, 860, 953, 1042	5.4	25.8	38.1	124.8	54.0
950802	2137	255, 336, 410, 502, 673, 740, 860, 953, 1042	5.0	25.3	34.4	135.4	61.0
950821	0937	255, 336, 410, 502, 673, 740, 860, 953, 1042	4.8	23.5	30.8	144.6	64.4
^aTime given is the approximate middle of the 20 to 35 minute total observing sequence ^bResolution is the maximum spatial resolution at the sub-Earth point for images obtained on the PC chip

Go back to text

Table 2. HST WFPC2 Filters and Exposure Times Used for These Observations^a

			Exposure Times (sec)		F_sun^c
Filter	center (nm)	FWHM (nm)	Cycle 4	Cycle 5	(Wcm^-2µm^-1)
F255W	256	41	350.0	180.0	0.01553
F336W	333	37	6.0	3.0	0.08667
F410M	409	15	4.0	2.0	0.16822
F502N	501	3	7.0	4.0	0.18775
F673N	673	5	0.7	0.6	0.15185
FR680N^b	740	10	--	0.11	0.12919
FR868N^b	860	11	--	0.12	0.09746
F953N	955	5	--	4.0	0.07696
F1042M	1044	61	--	3.0	0.07125
^aFilter data from Burrows (1995) ^bLinear Ramp Filter ^cSee Appendix B

Go back to text