Recomputation and Updating of MOLA Geolocation

Xiao, Hu; Stark, Alexander; Chen, Hao; Oberst, J.

doi:10.3390/rs14092201

Cited by 3 publications

(5 citation statements)

References 51 publications

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“…The PEDR data set was geolocated using a MGS trajectory and a Mars rotational model dating back to 2003. Therefore, we have incorporated an updated orbit model from Konopliv et al (2006) and IAU2015 Mars rotational model as in Archinal et al (2018) to update the MOLA geolocation (Xiao, Stark, Chen, & Oberst, 2022, Xiao, Stark, Steinbrügge, et al, 2022. The motion of the spacecraft during laser time-of-flight has been considered.…”

Section: Reprocessed Mola Data Setmentioning

confidence: 99%

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Spatio‐Temporal Level Variations of the Martian Seasonal South Polar Cap From Co‐Registration of MOLA Profiles

et al. 2022

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Each Martian year, approximately 30% of the atmosphere's CO 2 mass is in exchange with the polar surfaces through deposition/sublimation (Leighton & Murray, 1966). The seasonal CO 2 polar caps resulting from repeated depositions of snow/ice can extend down to 50°S/N (Piqueux et al., 2015). Temporal variations of the level and volume of snow/ice associated with the deposition/sublimation process can put crucial constraints on the Mars climate system and volatile circulation models. Additionally, this amount of snow and ice is significant enough to cause seasonal deflection of the lithosphere (Wagner et al., 2022). Constraining the level and mass of the seasonal portion of the polar cap is essential in properly modeling this deflection. Measurements of the level of snow/ice of the seasonal polar caps have been made by the Mars Orbiter Laser Altimeter (MOLA) onboard the Mars Global Surveyor (MGS, Smith et al., 2001;Aharonson et al., 2004;, measuring rock shadow lengths in high-resolution images to deduce the seasonal changes in rock heights on the surface (Mount & Titus, 2015), and precise radiative transfer models using imaging spectroscopy (Andrieu et al., 2018). Compared with the latter two that are spatially and temporally limited due to data availability, MOLA data cover the entire polar regions. Based on profile analysis at different latitudina annuli, Smith et al. ( 2001) measured the maximum seasonal level of snow/ice to be ∼1 m at both poles. In a different approach, Aharonson et al. ( 2004) fitted sinusoidal functions with annual and semi-annual terms to MOLA cross-over height residuals and estimated the maximum level to reach ∼1.5 m at the north pole and ∼2.5 m at the south pole.The "cryptic region" at Martian south pole during the southern spring is roughly located from 50° to 210°E and poleward of 70°S (see also Figure 1 of Hansen et al. (2010)). It is so described as it possesses low temperatures

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Section: Reprocessed Mola Data Setmentioning

confidence: 99%

“…(2006) and IAU2015 Mars rotational model as in Archinal et al. (2018) to update the MOLA geolocation (Xiao, Stark, Chen, & Oberst, 2022, Xiao, Stark, Steinbrügge, et al., 2022). The motion of the spacecraft during laser time‐of‐flight has been considered.…”

Section: Datamentioning

confidence: 99%

Spatio‐Temporal Level Variations of the Martian Seasonal South Polar Cap From Co‐Registration of MOLA Profiles

et al. 2022

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“…(2006) and IAU2015 Mars rotational model as in Archinal et al. (2018) to update the MOLA geolocation (Xiao, Stark, Chen, & Oberst, 2022; Xiao, Stark, Steinbrügge, et al., 2022). Meanwhile, a pointing aberration correction, which the PEDR processing ignored, has been added during the reprocessing to account for the special relativity effects (Xiao, Stark, Steinbrügge, et al., 2021).…”

Section: Reprocessed Mola Data Setmentioning

confidence: 99%

“…But, there still remain significant profile shifts, including a global systematic temporal bias in height (see also Section 3; Xiao, Stark, Steinbrügge, et al., 2022), due to timing, pointing and other unidentified errors. These error sources need to be taken care of in order to accurately and precisely obtain the seasonal level variations at the polar regions (Xiao, Stark, Chen, & Oberst, 2022; Xiao, Stark, Steinbrügge, et al., 2022).…”

Section: Reprocessed Mola Data Setmentioning

confidence: 99%

Spatio‐Temporal Level Variations of the Martian Seasonal North Polar Cap From Co‐Registration of MOLA Profiles

et al. 2022

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The seasonal deposition and sublimation of CO2 constitute a major element in Martian volatile cycles. We reprocess the Mars Orbiter Laser Altimeter (MOLA) data and apply co‐registration procedures to obtain spatio‐temporal variations in levels of the Seasonal North Polar Cap (SNPC). The maximum level over the Residual North Polar Cap (RNPC) is 1.3 m, approximately half of that at the south pole (2.5 m). However, the maximum level in the dune fields at Olympia Undae can be up to 3.8 m. Furthermore, off‐season decreases up to 3 m during the northern winter at Olympia Undae are observed. These are likely due to metamorphism effects accentuated by the reduced snowfall at this period. Meanwhile, off‐season increases of up to 2 m during the northern spring are noted, the cause of which remains to be explored. The volume of the SNPC peaks at the end of northern winter and is estimated to be approximately 9.6 × 1012 m3, which is 2% more than that of the Seasonal South Polar Cap. The bulk density of the SNPC can go through phased decreases in accordance with phased accumulation at northern high‐latitudes. These findings can put important constraints on the Martian volatile cycling models.

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“…This process takes into account the motion of the spacecraft during the laser pulse ToFs and the pointing aberration due to the relative velocity of the spacecraft with respect to the observer. Precise geolocation requires accurate modeling of these effects [229,230]. When a laser altimeter operates close to the Sun, for example, MLA and BELA at Mercury, general relativistic effects such as the Shapiro delay should also be incorporated to correct the ranging distance.…”

Section: Lidar Altimetrymentioning

confidence: 99%

Remote Sensing and Data Analyses on Planetary Topography

2023

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Planetary mapping product established by topographic remote sensing is one of the most significant achievements of contemporary technology. Modern planetary remote sensing technology now measures the topography of familiar solid planets/satellites such as Mars and the Moon with sub-meter precision, and its applications extend to the Kuiper Belt of the Solar System. However, due to a lack of fundamental knowledge of planetary remote sensing technology, the general public and even the scientific community often misunderstand these astounding accomplishments. Because of this technical gap, the information that reaches the public is sometimes misleading and makes it difficult for the scientific community to effectively respond to and address this misinformation. Furthermore, the potential for incorrect interpretation of the scientific analysis might increase as planetary research itself increasingly relies on publicly accessible tools and data without a sufficient understanding of the underlying technology. This review intends to provide the research community and personnel involved in planetary geologic and geomorphic studies with the technical foundation of planetary topographic remote sensing. To achieve this, we reviewed the scientific results established over centuries for the topography of each planet/satellite in the Solar System and concisely presented their technical bases. To bridge the interdisciplinary gap in planetary science research, a special emphasis was placed on providing photogrammetric techniques, a key component of remote sensing of planetary topographic remote sensing.

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Recomputation and Updating of MOLA Geolocation

Cited by 3 publications

References 51 publications

Spatio‐Temporal Level Variations of the Martian Seasonal South Polar Cap From Co‐Registration of MOLA Profiles

Spatio‐Temporal Level Variations of the Martian Seasonal South Polar Cap From Co‐Registration of MOLA Profiles

Spatio‐Temporal Level Variations of the Martian Seasonal North Polar Cap From Co‐Registration of MOLA Profiles

Remote Sensing and Data Analyses on Planetary Topography

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