Volume 7, Issue 2
Research Article
Open Access

Quantified Aeolian Dune Changes on Mars Derived From Repeat Context Camera Images

Joel M. Davis

Corresponding Author

E-mail address: joel.davis@nhm.ac.uk

Department of Earth Sciences, Natural History Museum, London, UK

Correspondence to: J. M. Davis,

E-mail address: joel.davis@nhm.ac.uk

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Peter M. Grindrod

Department of Earth Sciences, Natural History Museum, London, UK

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Sarah J. Boazman

Department of Earth Sciences, Natural History Museum, London, UK

Department of Earth Sciences, University College London, London, UK

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Pieter Vermeesch

Department of Earth Sciences, University College London, London, UK

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Thomas Baird

Department of Earth Sciences, University College London, London, UK

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First published: 11 December 2019

Abstract

Aeolian systems are active across much of the surface of Mars and quantifying the activity of bedforms is important for understanding the modern and recent Martian environment. Recently, the migration rates and sand fluxes of dunes and ripples have been precisely measured using repeat High Resolution Imaging Science Experiment (HiRISE) images. However, the limited areal extent of HiRISE coverage means that only a small area can be targeted for repeat coverage. Context Camera (CTX) images, although lower in spatial resolution, have wider spatial coverage, meaning that dune migration can potentially be monitored over larger areas. We used time series, coregistered CTX images and digital elevation models to measure dune migration rates and sand fluxes at six sites: Nili Patera, Meroe Patera, two sites at Herschel crater, McLaughlin crater, and Hellespontus Montes. We observed dune displacement in the CTX images over long‐term baselines (7.5–11 Earth years; 4–6 Mars years). Bedform activity has previously been measured at all these sites using HiRISE, which we used to validate our results. Our dune migration rates (0.2–1.1 m/EY) and sand fluxes (2.4–11.6 m3 m−1 EY−1) compare well to measurements made with HiRISE. The use of CTX in monitoring dune migration has advantages (wider spatial coverage, faster processing time) and disadvantages (ripples not resolved, digital elevation model dune heights may be underestimates); the future combined use of HiRISE and CTX is likely to be beneficial.

Plain Language Summary

Sand dunes and ripples are present across much of the surface of Mars. The motion of both dunes and ripples has been observed from orbital satellite images and rovers on the surface, which shows that the environment is constantly changing. Previously, high‐resolution (submeter scale) satellite images have been used to track the movement of dunes and ripples across the surface, which generally move at rates of up to several meters per year. However, the limited coverage of high‐resolution images means that only select sites can be monitored. Here we use medium resolution (meter scale) satellite images, which covers a much wider area, as a test case to see if we can accurately measure the movement of dunes, which are typically several hundred meters in length. We chose six sites that have previously been measured using high‐resolution images to monitor of over periods of ~10 Earth years. Our results show that our dune migration rates generally compare well to the high‐resolution measurements. The combined future use of medium and high‐resolution images for monitoring dunes on Mars is likely to be beneficial.

1 Introduction

Aeolian processes are active across much of the surface of Mars (e.g., Bourke et al., 2008; Bridges, Ayoub, et al., 2012) and are considered one of the predominant agents for landscape modification in nonpolar regions, under the current climate conditions (e.g., Bridges et al., 2013). This is evident from the movement of aeolian bedforms (dunes and ripples) observed in high‐resolution orbital images (e.g., Fenton, 2006; Bridges, Bourke, et al., 2012; Silvestro et al., 2013; Banks et al., 2018; Cardinale et al., 2016; Runyon et al., 2017; Chojnacki et al., 2018; Chojnacki et al., 2019) and from landers and rovers on the Martian surface (e.g., Sullivan et al., 2008; Bridges & Ehlmann, 2018). These bedforms are the result of the interaction between the surface and atmosphere and act as a record for wind regime, past and current climate, sediment availability, and erosion rates (e.g., Bridges, Bourke, et al., 2012; Runyon et al., 2017; Banham et al., 2018; Chojnacki et al., 2018; Chojnacki et al., 2019; Day & Catling, 2019). Quantifying the activity of bedforms is therefore important for understanding the recent and modern Martian environment.

Since 2006, the High Resolution Imaging Science Experiment (HiRISE) onboard the Mars Reconnaissance Orbiter has been imaging Mars at 0.25 m/pixel (McEwen et al., 2007); the acquisition of high‐resolution, multitemporal orbital data sets means that bedform motion can now be monitored in numerous locations across Mars (e.g., Bridges, Ayoub et al., 2012; Cardinale et al., 2016; Chojnacki et al., 2018; Chojnacki et al., 2019; Runyon et al., 2017; Silvestro et al., 2013). Dune sand fluxes of ~10 m3 m−1 EY−1 are observed in HiRISE images (e.g., Bridges et al., 2013; Chojnacki et al., 2019), comparable to some terrestrial aeolian systems (e.g., Antarctic Dry Valleys; Bridges, Bourke, et al., 2012).

One method to quantitatively measure bedform displacement is to use precisely orthorectified, coregistered, and correlated time series HiRISE images using the COSI‐Corr (“Co‐registration of Optically Sensed Images and Correlation”; Leprince et al., 2007) add‐in to the ENVI (ENvironment for Visualising Images) tool suite. COSI‐Corr has previously been used to monitor glacial movement on Earth (e.g., Herman et al., 2011; Heid & Kääb, 2012), fault displacement on the Earth and Mars (e.g., Grindrod et al., 2018; Hollingsworth et al., 2012), as well as bedform motion on both the Earth and Mars (e.g., Bridges, Ayuob, et al., 2012; Cardinale et al., 2016; Runyon et al., 2017; Scheidt & Lancaster, 2013; Silvestro et al., 2013; Vermeesch & Drake, 2008; Vermeesch & Leprince, 2012).

However, the relatively small image footprint of HiRISE (~5 km) when compared to the size of most Martian dune fields (typically tens of kilometers), and the need for stationary interdune areas within the image for coregistration, often means that only a small area can be targeted for repeated coverage. HiRISE currently covers ~2% total area of the Martian surface (as of early 2018; McEwen et al., 2018). While this areal coverage is a considerable achievement, the use of widely available lower spatial resolution images may complement HiRISE by providing wider context to aeolian studies. Tornabene et al. (2018) used repeat Context Camera (CTX; 6 m/pixel; Malin et al., 2007) images, oversampled to 4.6 m/pixel as a simulated product for the Color and Stereo Surface Imaging System (CaSSIS; Thomas et al., 2017) onboard the Trace Gas Orbiter, to examine dune migration in part of the Nili Patera dune field over 7.5 Earth years. Tornebene et al. observed displacement on both the lee and stoss sides of several dunes. This suggests that some dune migration can be measured in meter‐scale images over long temporal baselines.

In this study, we build on the work of Tornabene et al. (2018), by using precisely orthorectified, coregistered, and correlated time series CTX images and digital elevation models (DEMs) as a test case for quantifying dune migration and sand fluxes. We selected six dune fields that are known to be active from previous measurements in HiRISE and have moderate to high dune migration rates and fluxes (~0.2–1 m/EY; 1–15 m3 m−1 EY−1; Bridges, Ayuob, et al., 2012; Cardinale et al., 2016; Chojnacki et al., 2018; Chojnacki et al., 2019; Runyon et al., 2017): Nili Patera, Meroe Patera, two sites at Herschel crater, McLaughlin crater, and Hellespontus Montes. To validate our results, we compared our CTX measurements to HiRISE measurements from previous studies which used similar techniques. Finally, we considered the future applications of CTX in aeolian studies of Mars.

2 Study Areas

Six dune fields (Figure 1) were selected that (1) contain bedforms known to be active from previous studies in HiRISE; (2) experience moderate to high migration rates (>0.2 m/EY) with well‐defined slip faces; (3) are covered by repeat, long temporal baseline (generally >8 Earth years) CTX images acquired under similar imaging conditions; and (4) exhibit strong contrast between the dune and interdune (i.e., bedrock) areas. All our study sites are within the low to middle latitudes (~21.6°N–44.5°S) and mostly comprise barchan or barchanoid dunes. All the dune fields we investigated are classified as unconsolidated and mobile (i.e., they have crisp slip face brinks) on the dune stability index of Banks et al. (2018) and Fenton and Hayward (2010).

2.1 Nili and Meroe Patera

Our main study area is the Nili Patera dune field (8.7°N, 67.3°E; Figure 1b), which contains some of the fastest known moving bedforms on Mars (~0.5–0.8 m/EY; 5–16 m3 m−1 EY−1; e.g., Bridges, Ayuob, et al., 2012; Chojnacki et al., 2018). The Nili Patera dune field is found in the southwest quadrant of Nili Patera, a ~50 km wide caldera, part of the Hesperian‐aged Syrtis Major Planum volcanic complex (e.g., Fawdon et al., 2015). Discrete, symmetric barchan dunes (typically 200–400 m in length) with southwest trending slip faces transition into barchanoid dunes and an eventual sand sheet across the ~15 km long dune field (~425 km2). This transition is likely driven by a decrease in downwind sand flux (Bridges, Ayoub, et al., 2012; Runyon et al., 2017).

image
(a) Mars Orbital Laser Altimeter topographic map showing the locations of the six study areas. (b) CTX mosaic showing southwest trending barchan dunes within the caldera at Nili Patera; (c) CTX image showing southwest trending barchan dunes on the plains outside Meroe Patera; (d) CTX image showing south trending barchan dunes near the west rim of Herschel crater; (e) CTX image showing south trending barchan dunes near the east rim of Herschel crater; (f) CTX image showing south trending barchan dunes in McLaughlin crater; (g) CTX image showing west trending barchan and seif dunes in Hellespontus Montes.
image
CTX (orange outline; P17_007754_1873_XI_07N292W) and HiRISE (red outline; PSP_007754_1875; as previously studied by Chojnacki et al., 2018) images of the Meroe Patera dune field. The CTX image covers a greater width of the dune field. The white circles show the measured dunes in this study.

We also examined the nearby Meroe Patera dune field (~7. 3°N, 67.7°E; Figure 1c). Meroe Patera is another volcanic caldera, ~50 km wide, and situated ~100 km southeast of Nili Patera. The Meroe Patera dune field is found on the plains outside the western boundary of the caldera and covers a larger area than the Nili Patera dune field (~905 km2). The dune field mostly comprises active (~0.5 m/EY; 17 m3 m−1 EY−1; Chojnacki et al., 2018) asymmetric barchan and barchanoid dunes (both typically 200–400 m in length) which trend to the southwest and have been deflected around local impact craters. Both the Nili and Meroe Patera dune fields are thought to be particularly active due to regional western wind regimes associated with the Isidis basin slopes (Chojnacki et al., 2019).

2.2 Herschel Crater

Herschel crater is a ~300 km Noachian impact basin (14.2°S, 129.8°E), which contains several large (~10–50 km long) active dune fields and sand sheets. We investigated two of the dune fields (14.7°S, 127.9°E and 15.1°S, 131.9°E) within Herschel crater near its west and southeast rims (herein referred to as West Herschel [~600 km2; Figure 1d] and East Herschel [~100 km2; Figure 1e], respectively). These sites are ~225 km apart and both comprise active, south trending, asymmetric barchan and barchanoid dunes (both typically 100–300 m in length) with elongated horns which transition into sand sheets (~0.1–0.6 m/EY; 1–15 m3 m−1 EY−1; Cardinale et al., 2016; Runyon et al., 2017). At West Herschel, dunes are being funneled through a ~2 km valley bound by crater ejecta and a wrinkle ridge, before they broaden out into a ~20 km wide dune field. The sand flux of the dunes at both sites decreases downwind, which may be influenced by the regional and local topography and changes in surface roughness (Cardinale et al., 2016; Runyon et al., 2017).

2.3 McLaughlin Crater

McLaughlin crater is a ~90 km Noachian impact crater in the Mawrth Vallis region of northwest Arabia Terra. We investigated the dune field (~160 km2) near its south rim (21.6°N, 22.6°W; Figure 1f), which is associated with a steep increase in topography and change in surface roughness caused by the impact ejecta from another nearby ~25 km crater, which overlies McLaughlin. The dunes comprise active, south trending, asymmetric barchans and barchanoids (both typically 100–300 m in length), which all overlie bedrock (~0.8 m/EY; 12 m3 m−1 EY−1; Chojnacki et al., 2018).

2.4 Hellespontus Montes

Our final study site was a dune field (~35 km2; Figure 1g) comprising a series of westward trending barchan, barchanoid (both typically 100–250 m in length), and seif dunes (typically 5–15 km) on the eastern slopes of Hellespontus Montes, on the west margin of Hellas Planitia (44.45°S, 44.58°E). High dune migration rates here (~0.9 m/EY; 14 m3 m−1 EY−1) are associated with the Hellas basin slope winds, midlatitude westerlies, and locally rugged terrain (Chojnacki et al., 2019). Like McLaughlin, the dunes here also all overlie bedrock.

3 Methods

We used a combination of stereo topographic data and long baseline, repeat CTX images to derive and quantify dune migration and sand fluxes following previously established methods (e.g., Ayoub et al., 2014; Bridges, Bourke, et al., 2012; Chojnacki et al., 2018) in SOCET SET and COSI‐Corr.

3.1 SOCET SET: DEM Production and Image Coregistration

DEMs were produced from CTX stereo images using the USGS Integrated Software for Imagers and Spectrometers software and the BAE photogrammetric package SOCET SET according to the method of Kirk et al. (2008). CTX image pairs were selected such that the stereo convergence angle was ≥15° (defined as the difference in emission angle, taking into account the pointing direction of the spacecraft) and that images were acquired in close succession, under similar imaging conditions, and with the fewest shadows associated with the dunes. Tie points were automatically populated in SOCET SET between the two images and those occurring on dune surfaces were removed. We ran a series of bundle adjustments, removing erroneous tie points until the remaining points had an RMS pixel matching error of ≤0.6 pixels. The resultant DEM was then tied to Mars Orbital Laser Altimeter (Zuber et al., 1992) topography and exported with a horizontal post spacing of 20 m/pixel and a vertical precision of ~1.5–5 m (Kirk et al., 2008; Okubo et al., 2008; Sutton et al., 2015; see supporting information Table S2 for calculation).

After the production of the DEM, we imported our before and after CTX images in SOCET SET (T12008 and T2; assuming these were different from the S1 and S2 DEM images). Following previously established practices (e.g., Chojnacki et al., 2018), T 1 and T2 images were selected to have the maximum temporal baseline available acquired under imaging conditions optimized for change detection (taken ≤0.1 Mars years apart and ≤15° difference in incidence angle; Table S1). The T 1 and T2 images were then coregistered to the DEM and exported as orthorectified images with a pixel size of 6 m. The use of SOCET SET in the coregistration and orthorectification process is a departure from previous methods which used COSI‐Corr for this process (e.g., Bridges, Bourke, et al., 2012; Ayoub et al., 2014), and our technique is similar to HiRISE methods which do not use COSI‐Corr (e.g., Chojnacki et al., 2018). During trial runs, we found that SOCET SET achieved higher quality coregistration of CTX images than coregistering the images in COSI‐Corr.

Table 1. Summary Table Showing the Mean Dune Heights, Migration Rates, and Sand Fluxes for the Six Study Sites
Location T1 image central Lat. Lon. EY MY Number of dunes Dune height (m) Migration rate (m/EY) Sand flux (m3 m−1 EY−1)
Nili Patera 8.7°N, 67.32°E 9.2 4.9 79 22.4 ± 8.8 0.5 ± 0.3 11.6 ± 7.2
Meroe Patera 7.28°N, 67.75°E 9.5 5.1 50 17.5 ± 6.9 0.5 ± 0.2 9.5 ± 3.6
West Herschel 15.26°S, 127.92°E 9.2 4.9 42 12.5 ± 5.4 0.3 ± 0.1 3.6 ± 1.6
East Herschel 15.59°S, 131.88°E 7.8 3.9 12 7.7 ± 3.1 0.5 ± 0.2 4.4 ± 1.5
McLaughlin crater 21.57°N, 22.55°W 7.6 4 26 11.2 ± 5.1 0.2 ± 0.1 2.4 ± 1.4
Hellespontus 44.45°S, 44.58°E 11.3 6 30 9.7 ± 4.9 1.1 ± 0.4 10.2 ± 6.55
  • Note. EY and MY show the time difference between the before and after images (T1 and T2) in Earth years and Mars years, respectively. The T1 and T2 images were chosen to be less than ≤0.1 Mars years apart, assuring the best results.

3.2 COSI‐Corr: Image Correlation and Analysis

The CTX orthoimages were then imported into COSI‐Corr, where we ran correlations using a window size of 64 × 64 pixels and a step size of 2 pixels (12 m). We found that using smaller window sizes produced noisier results (e.g., high rates of bedrock correlation misregistration). We followed standard practices by filtering our results for the effects of spacecraft jitter and low signal to noise values (Leprince et al., 2007). The two component displacement directions (north‐south and east‐west) were then combined to produce a magnitude value following the robust migration direction (vector averaged) method of Necsoiu et al. (2009). We then measured the displacement of select dunes along the perceived center of the dune crest (away from any horns), which we used to calculate a migration rate (Figure 2). We avoided measuring dune crests that form due to a secondary wind direction, such as on the elongated horns of barchans. We then manually inspected the dune crests, lee front base and the base of the stoss for signs of change in the T1 and T2 images, as an approximate quality check to confirm displacement was occurring between the images. Manual inspection was possible for at least some of the dunes measured in COSI‐Corr at each site as the changes were suprapixel. We only measured dunes that were well resolved in the DEM and avoided measuring areas adjacent to (1) significant changes in topography or shadow and (2) bedrock correlation misregistration. We also measured the average displacement of obviously static bedrock in large areas away from the dunes to determine average misregistration values as a further threshold for noise. We discarded any dunes with measured displacements below this value. Finally, we extracted elevation values from the CTX DEM to derive dune heights and therefore sand fluxes (whereby migration rate in m/EY multiplied by the dune height gives the sand flux in m3 m−1 EY−1). We report our sand fluxes as the sand flux at the dune crest as is typical for other planetary aeolian studies (e.g., Bridges, Bourke, et al., 2012; Chojnacki et al., 2018, 2019). Where HiRISE DEMs were available, we also extracted elevation values along the same dune profile to compare to our CTX values.

4 Results

We measured a total of 239 dunes across the six sites (Figures 3 and 4). In many examples, suprapixel displacement is clearly visible between the coregistered images at the lee front and stoss sides of the dunes (for clarity, see animations in the supporting information: Movies S1S6). As expected, no dune ripples were large enough to be resolved at any of the sites. Our displacement values of the dunes extracted from the COSI‐Corr correlation contain a range of both subpixel and suprapixel values (~2–15 m). These values are all significantly higher than the mean misregistration values of the adjacent interdune bedrock (~0.5–1 m). In all sites, most of the measured dunes came from the upwind part of the dune field. This is because the correlation tended to break down in the downwind sections of the dune fields, where interdune bedrock was less clearly exposed and dunes were overlying sand patches. We also note that many smaller dunes were not resolved in the CTX DEM, although their displacement is clearly visible between the coregistered images (e.g., Movie S5) and in the COSI‐Corr correlation.

image
(a) CTX image showing part of the Nili Patera dune field, which comprises southwest trending barchan and barchanoid dunes. (b) Dune displacement values between 2007 and 2016 extracted from COSI‐Corr correlation overlaid on a CTX image. (c) All measured dune migration rates for the Nili Patera dune field (mean migration rate is ~0.5 m/EY). Dunes are moving faster in the northern and upwind parts of the dune field. The white arrows show the dune migration direction and their size represents the migration rates of the dunes.
image
Log‐log plot showing dune height versus migration rates for our six study sites. The solid black lines show different sand fluxes at 1, 10, and 50 m3 m−1 EY−1, respectively.

4.1 Nili and Meroe Patera

We measured the displacement of 79 dunes across the Nili Patera dune field over a period of 9.2 Earth years (4.9 Mars years; Figures 3, 4a, and S1). The measured dunes span ~20 km width of the dune field (approximately two thirds of the total width) and extend up to ~ 5 km downwind from the most upwind dune. The mean dune displacement measured was 4.8 ± 2.4 (1σ) m. (Note that our reported mean values are given as geometric means). This mean displacement value is significantly higher than the mean bedrock misregistration value of 0.6 ± 0.5 m (approximately one tenth of a CTX pixel), which was measured over an area of ~200 km2, away from the dunes. The mean dune migration rate is therefore 0.5 ± 0.3 (1σ) m/EY WSW. Extracting the dune heights from the CTX DTM (mean height 22.4 ± 8.8 (1σ) m) gives a mean sand flux at the dune crests of 11.6 ± 7.2 (1σ) m3 m−1 EY−1. There is significant variation in migration rates throughout the dune field. Dunes are generally migrating at faster rates (>0.6 m/EY) in the northern and upwind areas of the dune field than the southern and downwind areas (Figure 3c).

At the nearby Meroe Patera dune field, we measured the displacement of 50 dunes over 9.5 Earth years (5.1 Mars years; Figure 4b). The measured dunes span ~30 km width of the dune field and extend up to ~3–4 km downwind from the most upwind dune. The results are generally similar to the dunes at Nili Patera: the mean measured displacement was 5.2 ± 2.2 m (mean bedrock misregistration 0.5 ± 0.5 m), giving a mean migration rate of 0.5 ± 0.2 m/EY SW. The mean measured dune height was 17.5 ± 6.9 m, which gives a mean crest sand flux of 9.5 ± 3.6 m3 m−1 EY−1. Like at Nili Patera, the Meroe Patera dunes are generally migrating at faster rates in the northern and upwind areas (>0.6 m/EY).

4.2 Herschel Crater

We measured the displacement of 42 dunes at the West Herschel crater site over 9.3 Earth years (4.9 Mars years; Figure 4c). At West Herschel, the measured dunes span ~15 km of the 20 km wide dune field and extend approximately ~15 km downwind from the most upwind dune measured. The mean measured displacement was 2.6 ± 0.8 m (mean bedrock misregistration 1.1 ± 0.8 m). The mean dune migration is therefore 0.3 ± 0.1 m/EY. Extracting the dune height values from the CTX DEM gives a mean height of 12.5 ± 5.1 m, which gives a mean crest sand flux of 3.6 ± 1.6 m3 m−1 EY−1. The migration rate at West Herschel generally decreases in the downwind direction and the fastest moving dunes are those being funneled through the valley.

On the other side of Herschel crater, we measured the displacement of 12 dunes at the East Hershel crater dune field over a period of 7.8 Earth years (3.9 Mars years; Figure 4d). The measured dunes are all at the upwind end of the dune field, spanning ~7 km in width and extending 3 km downwind. The mean measured displacement was 4.2 ± 1.4 m (mean bedrock misregistration 0.9 ± 0.8 m). The mean dune migration is therefore 0.5 ± 0.2 m/EY SSW. This is around twice the rate of the West Herschel site. The mean measured dune height was 7.7 ± 3.1 m, which gives a mean crest sand flux of 4.2 ± 1.3 m3 m−1 EY−1. The upwind dunes are generally moving faster, however this is only from a small sample size (12 dunes). Both sites at Herschel have similar sand fluxes at their crests: ~4 m3 m−1 EY−1.

4.3 McLaughlin Crater

At McLaughlin crater, we measured the displacement of 26 dunes over 7.6 Earth years (4 Mars years; Figure 4e). Here, the measured dunes span ~15 km of the 20 km wide dune field. Like the other sites, the majority of measured dunes are at the upwind end of dune field. The mean measured displacement was 1.6 ± 0.6 m (mean bedrock misregistration 0.6 ± 0.4 m). This gives a mean migration rate of 0.2 ± 0.1 m/EY S, making the McLaughlin dunes the slowest moving of all the study sites. The mean measured dune height was 11.2 ± 5.1 m, which gives a mean crest sand flux of 2.4 ± 1.4 m3 m−1 EY−1. However, we also note that some of the smaller dunes that were not resolved in the CTX DEM (and as such were not included in our results) are moving at faster rates than our mean measured value: ~0.5 m/EY (Movie S5).

4.4 Hellespontus Montes

Lastly, we measured the displacement of 30 dunes at Hellespontus Montes over a period of 11.3 Earth years (6 Mars years; Figure 4f). The measured dunes span ~5 km in width, nearly the total width of the dune field and extend the near full length of the dune field too (bedrock is exposed throughout the entire dune field). The mean measured displacement was 11.9 ± 4.3 m (mean bedrock misregistration 1.7 ± 2.1 m). These values give a mean migration rate of 1.1 ± 0.4 m/EY, making these the fastest dunes of all six study sites. All but one of the 30 dunes measured have migration rates higher than 0.8 m/EY. The mean measured dune height was 9.7 ± 4.5 m, which gives a mean crest sand flux of 10.2 ± 6.6 m3 m−1 EY−1. The high sand fluxes at the Hellespontus site are comparable to the Nili and Meroe Patera sites. There does not seem to be a trend between distance downwind and migration rates and sand fluxes.

5 Discussion

5.1 Comparison to HiRISE Dune Migration Rates and Sand Fluxes

In order to validate our approach, we first compare our mean migration rates and dune heights to previous studies that used higher spatial resolution HiRISE images (Figure 5). Our CTX‐derived results generally compare well to previous measurements of the same dune fields that used similar techniques with HiRISE data. Note that as the results of previous studies were not available for individual dunes, a like‐for‐like comparison is not possible and some intradune variation is expected.

image
Log‐log plot showing the mean dune height versus migration rates for our six study sites and other select studies which used HiRISE data at the same sites. The HiRISE measurements are from Bridges, Ayoub, et al. (2012, Nili Patera), Runyon et al. (2017, Upwind and Downwind Herschel crater), Chojnacki et al. (2018, Nili Patera, Meroe Patera, McLaughlin crater), and Chojnacki et al. (2019, Hellespontus). The solid black lines show the sand flux at different rates (1, 10, and 5 m3 m−1 EY−1).

Our dune migration rates at Nili Patera (mean: 0.5 ± 0.3 m/EY) are similar to previous HiRISE measurements (0.5 m/EY and 0.8 ± 0.2 m/EY) by Bridges, Ayoub et al. (2012) and Chojnacki et al. (2018), who measured migration rates over 1.5 and 2 Mars years, respectively. Our derivation of similar results over ~5 Mars years suggests that dune migration rates may be relatively constant over longer periods of time. Moreover, our dune migration rates at Meroe Patera (0.5 ± 0.2 m/EY) also compare favorably to HiRISE measurements (0.5 ± 0.2 m/EY) by Chojnacki et al. (2018). We note that the mean crest sand fluxes for Nili Patera (11.6 ± 7.2 m3 m−1 EY−1) and Meroe Patera (9.5 ± 3.6 m3 m−1 EY−1) are smaller than mean measurements from HiRISE (16 ± 4.9 and 16 ± 4.5 m3 m−1 EY−1 for Nili and Meroe, respectively; Chojnacki et al., 2018). We address this slight discrepancy in section 5.2.

Our migration rates at West and East Herschel crater also compare favorably to HiRISE studies (Cardinale et al., 2016; Runyon et al., 217). At the West Herschel dune field, our CTX measured migration rates (mean: 0.3 ± 0.1 m/EY) over ~5 Mars years are similar to HiRISE measurements (mean: 0.2 m/EY) by Cardinale et al. (2016) made over 2 Mars years. Runyon et al. (2017) measured dune migration rates at both the West and East Herschel sites, finding that the upwind dunes were moving at ~0.5 m/EY decreasing downwind to ~0.2 m/EY. These measurements are also generally similar to our CTX measurements for West and East Herschel: 0.3 ± 0.1 and 0.5 ± 0.2 m/EY, respectively. The upwind and downwind sand fluxes as measured by Runyon et al. (2017) are ~10 and 2 m3 m−1 EY−1, respectively. These values are similar to our mean CTX measurements West and East Herschel: 3.6 ± 1.6 and 4.4 ± 1.5 m3 m−1 EY−1, respectively.

Our migration rates for McLaughlin crater (mean: 0.2 ± 0.1 m/EY) are significantly less than HiRISE measurements (0.8 ± 0.3 m/EY) by Chojnacki et al. (2018). This difference could be explained by several factors. Dunes moving at different rates may have been measured; indeed, some of the smaller dunes not resolved in the CTX DEM (likely <5 m in height) were moving at faster rates than 0.2 m/EY in the COSI‐Corr correlation, and we did not include these in our results. Additionally, most of our measurements were concentrated up at the upwind margins of the dune field, away from the some of the larger, downwind dunes. Varying rates in intradune field migration may have been caused by local variations in surface roughness or topography. The dune field at McLaughlin is found at the boundary between the McLaughlin crater floor material and impact ejecta from a superposing crater, which causes an increase in both surface roughness and topography. Furthermore, with dunes measured at similar intervals over much of the same periods (2006–2017 vs. 2008–2016), such a discrepancy is unlikely to be due to a change in sand mobility. One final possibility to explain the discrepancies in results at this site is that different methods may produce different results. Consequently, our mean crest sand flux at McLaughlin of 2.4 ± 1.4 m3 m−1 EY−1 is significantly lower than the mean sand flux of 11.5 m3 m−1 EY−1 by Chojnacki et al. (2018).

Our migration rates for Hellespontus (mean: 1.1 ± 0.3 m/EY) compare favorably to HiRISE measurements (0.9 m/EY) by Chojnacki et al. (2019). These measurements were taken over 6 and 4.3 Mars years, respectively, suggesting that as at Nili and Meroe Patera, dune migration rates at Hellespontus may be relatively steady in the medium term. Our mean crest sand flux at Hellespontus of 10.2 ± 6.55 m3 m−1 EY−1 is slightly lower than the mean sand flux of 16.8 m3 m−1 EY−1 by Chojnacki et al. (2019). Importantly, our results show that our CTX dune displacement measurements generally compare favorably to HiRISE measurements over a range of different scales.

5.2 CTX vs. HiRISE‐Derived Dune Heights

In order to verify our CTX‐derived dune heights, we compared them to HiRISE‐derived heights on a per dune basis. HiRISE DEMs were publicly available (via the HiRISE PDS node) for all of our six study sites, which we manually georeferenced to the CTX DEMs. The HiRISE images used to produce the DEM were all acquired either simultaneously with the CTX images or within 0.5 Mars years, so changes in dune topography over the time in which the DEM images were acquired are unlikely to affect this comparison (Bridges, Bourke, et al., 2012; Table S3). Only part of the HiRISE DEMs overlapped with the CTX measurements (34 dunes at Nili Patera; 20 dunes at West Herschel; eight dunes at Meroe Patera; eight dunes at Hellespontus; and four from each East Herschel and McLaughlin crater), but this nevertheless provided a useful comparison. Extracting the same elevation profiles from the HiRISE DEMs as we did for the CTX DEMs showed that generally the CTX values underestimated the dune height (Figure 6). On average, a CTX DEM measurement was 67% of a HiRISE DEM measurement. The East Herschel and McLaughlin sites compare particularly poorly, where the site average CTX DEM measurement is only ~40% of the HiRISE DEM measurement. However, this is only from sample size of four dunes per site. One explanation for the lower CTX height values is the resolution of the DEM: the slip faces of dunes at most sites are several tens of meters, which is only ~2–3 DEM pixels. The sudden change in height might lead to a “smoothing” effect in the DEM, meaning that the measured dune heights are less than their true values. This comparison means that our sand fluxes for the dune crests are likely underestimates of the true crest sand flux. For example, our mean crest sand flux at Nili Patera (11.6 ± 7.2 m) is less than the mean sand flux from HiRISE measurements (16 ± 4.5 m; Chojnacki et al., 2018).

image
Comparison of dune heights extracted from HiRISE‐ and CTX‐derived DEMs. The heights extracted from the CTX DEMs are typically less than the HiRISE heights.

5.3 Benefits, Caveats, and Considerations of Using CTX

The use of CTX in monitoring dune migration and sand fluxes has advantages, despite the lower image resolution when compared to HiRISE (typically 6 vs. 0.25 m). The larger areal footprint of CTX and the potential for more repeat coverage affords a larger study area providing scope into investigating lateral and downwind variations (Figure 2). Figure 3 demonstrates that clear displacement maps of dune fields can be produced from CTX images with very low background noise. Additionally, CTX has a faster processing time in both SOCET SET and COSI‐Corr, allowing large areas to be investigated relatively quickly. The use of CTX could be applied to investigations into temporal dune sand flux changes, the characterization of future landing sites (Chojnacki et al., 2018), or to compare with mesoscale models of the Martian climate (e.g., Hayward et al., 2009).

One limitation of our results was that measuring dunes that were well resolved in both the CTX DEM and the COSI‐Corr correlation required careful consideration. We found that dunes greater than ~200 m (10 DEM pixels) across were generally well resolved in the DEM. However, the displacement of smaller dunes (~100 m) that were not resolved in the DEM was still visible between the coregistered images and in the COSI‐Corr correlation (e.g., Movie S5). Using alternative image pairs acquired at different times to produce the DEMs sometimes better resolved the topography of smaller dunes. Comparing to HiRISE DEMs also suggests that our CTX DEM heights may be underestimating the true height of the dune (Figure 6). Manual inspection of the DEMs is also important for quality checking as errors in the DEM could introduce false movement in the orthorectification process. Another factor is that both CTX and HiRISE COSI‐Corr results can be noisy because of jitter and along the CCD seams (Ayoub et al., 2014), although this may be less of an issue for CTX because of the lower image resolution. Filtering our CTX COSI‐Corr results for jitter and other forms of noise managed to remove most of these effects. We also note that the sites with strong dune‐substrate albedo contrast (Nili, Meroe) produced the least noisy COSI‐Corr results, whereas the sites with poor dune‐substrate albedo contrast (Hellespontus) produced the noisiest results. Additionally, as the COSI‐Corr correlation tended to break down in the downwind section of the dune fields because of the lack of bedrock, measuring dunes in areas where there is appropriate interdune bedrock exposure is important. Future tests of CTX could investigate dune fields with sand‐starved downwind areas, such as those dune fields in Oyama and Capen craters, to produce a more representative picture of intradune field sand flux variations. Thus, our mean dune migration rates and sand fluxes may not be entirely representative of the variation across entire dune field, although they still provide a useful first order comparison between different sites.

The future combined use of HiRISE and CTX in dune monitoring and in COSI‐Corr will likely be complementary and avoid the potential trade‐offs of only using one data set: HiRISE can quantitatively measure dune and dune ripple movement, whereas CTX can provide wider context and examine regional variation, where HiRISE coverage is unavailable. This has the advantage in that CTX is generally acquired alongside HiRISE now (often under appropriate conditions for change detection), allowing migration rates and sand fluxes to be monitored over the same time period using different data sets. In the future, the CaSSIS camera onboard Trace Gas Orbiter, which has a similar resolution to CTX (nominally 4.6 vs. 6 m), is likely to be used to monitor bedform displacement (Tornabene et al., 2018). The application of the CaSSIS's four color channels (Thomas et al., 2017) may have the potential to improve the coregistration between before and after images. We also note that the use of SOCET SET is a well‐validated and mature method of image coregistration (e.g., HiRISE; Chojnacki et al., 2018) that can cope with the effects of illumination changes, which could be applied to monitoring changes in other landforms with CTX images as well (e.g., gullies, polar processes).

6 Conclusions

We used time series, coregistered CTX images and DEMs to measure dune migration and sand fluxes at six dune fields across Mars in SOCET SET and COSI‐Corr: Nili Patera, Meroe Patera, West and East Herschel crater, McLaughlin crater, and Hellespontus Montes. We observed dune displacement in the CTX images over long‐term baselines (7.5–11 Earth years; 4–6 Mars years), giving migration rates of 0.2–1.1 m/EY. Extracting the dune crest heights from the CTX DEMs gives crest sand fluxes of 2.4–11.6 m3 m−1 EY−1. The fastest moving dunes were Hellespontus Montes, whereas those with the largest sand fluxes were Nili Patera, Meroe Patera, and Hellespontus Montes. We find that our migration rates generally compare well to previous measurements made using HiRISE, although our CTX DEM dune heights are likely to be an underestimate (and thus sand fluxes). We have shown that CTX has the potential to expand the coverage area for dune field monitoring where HiRISE is unavailable. The combined future use of both CTX and HiRISE in measuring dune changes is likely to be beneficial. Our results demonstrate that meter‐scale orbital images can be used to quantify changes in aeolian systems on Mars.

Acknowledgments

JMD gratefully acknowledges UK Space Agency (UK SA) funding (ST/R002355/1). PMG acknowledges UK SA funding (ST/L00254X/1). We thank Matt Balme for reviewing a draft version of this manuscript. We thank the various Mars instrument teams for their consistent and dedicated work. We thank Matthew Chojnacki and Simone Silvestro for thorough and constructive reviews. The standard data products used here are available from the NASA PDS (https://pds.jpl.nasa.gov/). The CTX DEMs and coregistered time series images are available for download online (https://doi.org/10.6084/m9.figshare.c.4649537.v1).