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Northern: Composite
Product Name
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Description PNG TIFF GeoTIFF Anc. Data
Combined Ice Consistency Map

Last Updated: 2019-05-08 08:37:36

The ice consistency map is generated by combining all the individual consistency maps through the "SWIM Equation", i.e. Neutron; Thermal; Radar Surface Power; Geomorphology and Radar Dielectric Estimates. The ice consistency map is designed to show where all data sets are consistent or inconsistent with the presence of ice over a combined sensing depth of ~5m, indicating the likely presence of ice or lack thereof in that location.
Combined Ice Consistency Map with Ice Exposing Impacts

Last Updated: 2019-05-08 09:58:04

Same as the Combined Ice Consistency map but with locations of ice exposing impacts from Dundas et al. (2014) shown
Northern: Individual Data Sets
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Description PNG TIFF GeoTIFF Anc. Data
Geomorphology

Last Updated: 2019-05-08 08:45:46

The geomorphology ice consistency map was generated using new and previous mapping of periglacial and glacial features. For the new mapping, a number of periglacial and glacial features were systematically surveyed between 0-60°N. A sampling of 4x4° CTX image mosaics (beta01 from the CalTech Murray Lab) within previously mapped geologic units (Tanaka et al., 2005, USGS SIM 2888) was used to tally the number of observed periglacial and glacial landforms and to extrapolate the observations to the mapped unit boundaries. The number of landforms was then normalized with equal weighting to yield ice consistency values between 0 and 1. Areas <27°N with no observed periglacial or glacial features were assigned a value of -1 and areas from 30° to 27°N were assigned an equatorward Gaussian decay in values from 0.1 to 0. Areas of more detailed mapping of scallop terrain in Acidalia (0-70°W) were assigned a value of 0.75. Previous mapping was also used as input, including glacial features (lobate debris aprons, lineated valley fill, and concentric crater fill; Levy et al., 2014) and pedestal craters (Kadish et al., 2009). Where mapped, glacial features were assigned a value of 1 and pedestal craters a value of 0.75.
Neutron Dataset

Last Updated: 2019-05-08 08:45:46

Pathare et al. [2018] produced the most definitive global maps to date of near-surface water-equivalent hydrogen in an upper layer (W_up), lower layer (W_dn), and depth (D) to the lower layer. They refined the cross-over technique developed by Feldman et al. [2011] to produce the first maps of self-consistent W_up, W_dn, and D. These W_dn results (expressed in terms of WEH as percentages) were then scaled to fit into the SWIM equation. If W_dn ≥ 25% -> 1, 10% ≤ W_dn < 25% scaled between 0 and 1, 5% ≤ W_dn < 10% scaled between -1 and 0, and W_dn < 5% -> 0.
Est. Dielectric Properties

Last Updated: 2019-05-08 08:45:46

To estimate the dielectric properties we found locations where the approximate depth of a subsurface reflector can be estimated based on the surrounding topography then based on that depth and the two-way travel time we calculate the real dielectric permittivity (ε’) of the unit above the reflector. In regions where this can be done readily, primarily around Lobate Debris Aprons, we simply took these estimates for the whole region. In regions where the dielectric cannot be found as easily we estimate the dielectric at as many points as possible then interpolate between those points across the extent of the reflector. To generate the estimated dielectric properties ice consistency map we applied equation C_rd = ε’x*0.5+2.5 to our estimates of the dielectric, effectively mapping lower dielectric to being more consistent with ice. Super-resolution products used in this analysis may be found by following this link.
Radar Surface Power Return

Last Updated: 2019-05-08 08:45:46

The SHARAD surface power was measured and corrected for surface topography using a combination of MOLA and SHARAD surface roughness data. Low power values provide a proxy for the bulk density of the upper ~ 5m. Due to the low density of ice relative to other martian near surface materials, lower power returns are assumed to be consistent with the presence of ice. Consistency values were assigned according to the global power distribution: < -1σ = 1; -1σ - -0.5σ = 0.5; -0.5σ - 0.5σ = 0; 0.5σ = 1σ = 0.5; >1σ = -1
Thermal Analysis

Last Updated: 2019-05-08 08:45:46

TES and THEMIS were integrated into a single thermal consistency map, with TES providing near-global coverage and THEMIS contributing at select locations. For regions where only TES data were considered, matches to models of low ATI units over high ATI units were assigned values of +1 and matches to models of high ATI units over low ATI units were assigned values of -1. If no good match to models was found or the top layer thickness of the matched model had a diurnal skin depth of d <1, we assigned a value of 0. At locations where THEMIS data was considered, it was compared directly to TES and we applied equivalent criteria when assigning consistency values. In the LPSC products, consideration of THEMIS data did not modify results derived from TES products only.
Est. Depth to Subsurface Interface

Last Updated: 2019-05-08 08:45:46

For this step we prescribe the median real dielectric permittivity estimated for individual classes of features. These classes include lobate debris aprons/lineated valley fill, Onilus upper plains mantle, Utopia mantle, and Acidalia mantle. The median dielectric permittivities are then used to calculate the depth at each point for which a subsurface reflector is mapped.