Radar imagery of Mercury’s putative polar ice: 1999–2005 Arecibo results

Harmon, J. K.; Slade, M. A.; Rice, M. S.

doi:10.1016/j.icarus.2010.08.007

Cited by 97 publications

(176 citation statements)

References 26 publications

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“…Root mean square measurement uncertainties on the individual pixel σSC values are ∼ 0.014 and a threshold of 0.1 was adopted by default to separate radar-bright (σSC > 0.1) pixels from radar-dark ones. This is somewhat larger than the 4 σSC level advocated by Harmon et al (2011), and should correspond to regions with thicker water ice deposits. Bilinear interpolation is used to associate a same-sense radar backscatter cross-section with each MLA pixel.…”

Section: Radar Datamentioning

confidence: 66%

“…These pixels slightly oversample the instrumental resolution of ∼ 1.5 km, and there may be systematic location mismatches on the order of ∼ 2 km between this radar grid and the MLA DEM (Harmon et al 2011;Chabot et al 2013;Deutsch et al 2016). Root mean square measurement uncertainties on the individual pixel σSC values are ∼ 0.014 and a threshold of 0.1 was adopted by default to separate radar-bright (σSC > 0.1) pixels from radar-dark ones.…”

Section: Radar Datamentioning

confidence: 99%

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How thick are Mercury’s polar water ice deposits?

Eke

Lawrence

Teodoro

2017

Icarus

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An estimate is made of the thickness of the radar-bright deposits in craters near to Mercury's north pole. To construct an objective set of craters for this measurement, an automated crater finding algorithm is developed and applied to a digital elevation model based on data from the Mercury Laser Altimeter onboard the MESSENGER spacecraft. This produces a catalogue of 663 craters with diameters exceeding 4 km, northwards of latitude +55• . A subset of 12 larger, well-sampled and fresh polar craters are selected to search for correlations between topography and radar same-sense backscatter cross-section. It is found that the typical excess height associated with the radar-bright regions within these fresh polar craters is (50 ± 35) m. This puts an approximate upper limit on the total polar water ice deposits on Mercury of ∼ 3 × 10 15 kg.

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Section: Radar Datamentioning

confidence: 66%

Section: Radar Datamentioning

confidence: 99%

How thick are Mercury’s polar water ice deposits?

Eke

Lawrence

Teodoro

2017

Icarus

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“…Observations at Mercury show that there are significant amounts of water ice and other volatiles that are closely correlated with spatial and depth locations of volatile thermal stability [6,7,[10][11][12]. In contrast, the spatial distribution and depth dependence of lunar polar hydrogen concentrations are not well correlated with locations of volatile thermal stability.…”

Section: Introductionmentioning

confidence: 94%

“…Predictions dating back to the 1960s and 1970s proposed that lunar PSRs would have enhanced water concentrations [1,2]. Subsequent spacecraft and Earth-based measurements using various techniques (radar, neutron spectroscopy, spectral reflectance) have provided abundant evidence to support these predictions at both the Moon and Mercury [3][4][5][6][7]. The characteristics of PSRs and the processes that take place within them have implications for a variety of topics such as the origin and history of solar system volatiles [8], synthesis of organic materials [9], and in-situ resources for human exploration.…”

Section: Introductionmentioning

confidence: 99%

High-resolution mapping of lunar polar hydrogen with a low-resource orbital mission

et al. 2015

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a b s t r a c tLunar permanently shaded regions (PSRs) are unique solar-system environments. Their low temperatures ( o 100 K) facilitate cold trapping of volatile materials over timescales comparable to the lifetime of the solar system. While much has been learned about these regions from orbital spacecraft, important missing information includes the spatial and depth-dependent distribution of bulk hydrogen concentrations in and around PSRs. We present two complementary mission scenarios where orbital neutron spectroscopy will provide significantly improved understanding of lunar polar bulk hydrogen concentrations. In the first mission concept, a six-month orbital mission will measure bulk hydrogen concentrations with sensitivity better than 50 ppm and a spatial resolution of order 20 km over the entire lunar South Polar region (poleward of 80ºS). Spatial reconstruction analyses of the returned data will improve the final spatial resolution to better than 10 km. The presence and burial depth (o 25 cm) of subsurface deposits will be quantified with latitude-dependent sensitivities ranging from 50 to 350 ppm. The second concept envisions a few, very low altitude ( $ 5 km) flyovers of one or more PSRs to quantify the hydrogen concentrations and spatial heterogeneities with a hydrogen sensitivity less than 200 and spatial scale size of 5 km. Both concepts can be combined in a single mission where full-coverage polar measurements are made with a hydrogen spatial resolution of 20 km, and higher spatial resolution measurements are made for a few strategically selected PSRs at the end of the mission. & 2015 IAA. Published by Elsevier Ltd. on behalf of IAA. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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“…The global shape or figure of a body depends on its mass, size, rotational and tidal state, and material strength. Detailed topographic maps of Mercury, Venus, the Moon, and Mars have been obtained by using Earth-based radar observations (Harmon, 2007;Harmon et al, 2001Harmon et al, , 2011Margot et al, 1999;Muhleman et al, 1995), radio occultation data, and radar and laser altimetry from orbiting spacecraft (Rappaport et al, 1999;Smith et al, 1999a;Zuber et al, 1992Zuber et al, , 1994Zuber et al, , 2008Zuber et al, , 2012. Though the masses of planets and satellites have been known from astronomical observations for a long time, the most current and accurate values are based on measurements of spacecraft that landed, orbited, or flew by.…”

Section: Geodesymentioning

confidence: 99%