Tag Archives: Geography

Cloud-Free Heard Island

Composite, cloud-free satellite imagery of Heard Island, being produced in QGIS.  Image credit: Bill Mitchell (CC-BY), using USGS (Landsat 8, EO-1) data (public domain).
Composite, cloud-free satellite imagery of Heard Island, being produced in QGIS. Image credit: Bill Mitchell (CC-BY), using USGS (Landsat 8, EO-1) data (public domain).

Heard Island is a pretty cloudy place most of the time. However, there are occasional times when the weather clears, particularly on the southeastern (leeward) side of the island. On rare occasions, the northwest and southwest sides of the island come out from the clouds as a satellite passes over.

For the past two years, I have been watching Heard Island using true-color imagery from four satellites: Terra, Aqua, Landsat 8, and EO-1. I have posted previously about satellite imagery from these instruments. Although every image of the Island I have seen has clouds in it covering a portion of the island, I was curious whether or not I had accumulated clear imagery of the entirety of Heard Island.

In part, this question was spurred by a follower on Twitter asking about eruptive activity at Heard. I had to admit I didn’t really know whether the activity was low-level and continuous (like Kilauea) or more intermittent. Given that our knowledge of its eruptive activity is primarily from satellite observations, do the satellite “thermal anomalies” correspond to short eruptive events, or simply a cloud-free view of the volcano?

For high-resolution imagery of Heard Island, the datasets of interest are from EO-1 ALI, and Landsat 8 OLI. The two MODIS instruments (one on Aqua, one on Terra) are moderate-resolution, and while 250-m resolution is sufficient for some purposes, this one needs more. Looking through the archives, I was able to find EO-1 ALI data primarily for Mawson Peak and points southeast, and Landsat 8 OLI covered much of the island, particularly the northwest.

Not only is having cloud-free, high-resolution data important for me, but I want the data to be recent. There has been a retreat of up to 5.5 km for some of the glaciers since 1947, and the Google Maps imagery of that area (Stephenson Lagoon) is horribly outdated. Fortunately, I found most of the island covered in large swaths with images from 2014 onward, and mostly 2016. There was even good imagery from when I was on Heard Island! Our ship, the Braveheart, is visible as a few white pixels in Atlas Roads (just north of Atlas Cove), slightly closer to the Azorella Peninsula than to the Laurens Peninsula. The tents and campsite are too small and darkly colored to be visible on this image.

Braveheart in Atlas Roads and the campsite (non-contrasting) at Atlas Cove, Heard Island.  Satellite image pixels are 15 m across, and the Azorella Peninsula isthmus (along Campsite label) is 1 km wide.  Image credit: Bill Mitchell (CC-BY), using USGS (Landsat 8 OLI) data (public domain).
Braveheart in Atlas Roads and the campsite (non-contrasting) at Atlas Cove, Heard Island. Satellite image pixels are 15 m across, and the Azorella Peninsula isthmus (along Campsite label) is 1 km wide. Image credit: Bill Mitchell (CC-BY), using USGS (Landsat 8 OLI) data (public domain).

A small portion of the island between Atlas Cove and Mawson Peak was the most difficult to find. With the topography of the island, the steady stream of wind, and the humid air, the 2.5 km by 2.5 km region was cloudy pretty much all the time. Eventually, using the EO-1 ALI instrument and going back to early 2010, I found a reasonably clear image of it.

Once I had the images (after combining true-color and panchromatic brightness data in QGIS), I needed to stitch them together. Thanks to the wonderful QGIS training manual, I was able to create vector (polygon) layers which corresponded to the clear region of each image (plus some surrounding ocean). At this point the troublesome mostly-cloudy spot became evident, and the search was on for imagery to fill the void.

Creating polygons for clipping the satellite imagery using QGIS.  Four polygons are shown here, including the small polygon of much cloudiness.  A fifth dataset was subsequently incorporated.
Creating polygons for clipping the satellite imagery using QGIS. Four polygons are shown here, including the small polygon of much cloudiness. A fifth dataset was subsequently incorporated.

Finally, I tried to put them together. This turned out to be more trouble than it was worth for my purposes, having only five images. Several of the images had differing resolutions (10 m/pixel for EO-1 ALI, 15 m/pixel for Landsat 8 OLI). Additionally, since I was handling these in their raw format, color balances/exposures were not consistent across images. I decided it best, then, to leave them separate, and sent them around to the Heard Island Expedition team.

Soon I had an email from the expedition leader: he was very interested in the imagery, but it wasn’t opening in Google Earth. Some searching later, I found that Google Earth works best with a certain map projection (EPSG:4326), and when exporting the GeoTIFF, I needed to select “rendered image” rather than “raw data”. I re-exported the images, zipped them up, and tested it out on another computer: success! This Google Earth friendly imagery is now available here (17 MB zip).

One continuation of this project would be to keep looking through the documentation on GeoTiffs to find out how to make the rendered images use a transparent, not white, border where there is no data. That would likely let me create a virtual raster catalog to load all of them in one go, rather than having to load them separately.

Satellite Image Processing Revisited

Heard Island on Nov. 20, 2015, with image processing underway in QGIS.  Image credit: Bill Mitchell (CC-BY) with satellite imagery from USGS (EO-1 satellite, ALI instrument).
Heard Island on Nov. 20, 2015, with image processing underway in QGIS. Image credit: Bill Mitchell (CC-BY) with satellite imagery from USGS (EO-1 satellite, ALI instrument).

Following up on my earlier post about satellite image processing, I am happy to report that I have made progress in being able to process images myself! Through a fortunate combination of search terms, timing, and luck, I managed to come across two key pieces of information that I needed.

First, I found out how to make RGB images from raster data layers, such as different spectral bands on a satellite, fairly easily with QGIS. That was a big step forward from how I had been doing it previously, which was inelegant, inefficient, and only mostly worked. Stacking three layers (one each for red, green, and blue) into a virtual raster catalog was just a few clicks away (Raster | Miscellaneous | Build Virtual Raster (Catalog)).

Encouraged by the success with that project, I continued clicking around and stumbled across some mention of pan-sharpening (also pan sharpening), where a panchromatic (all-color) detector at high resolution is used to enhance the resolution of a colored image (sharpen). Alternately, you can think of it in the complementary way, where lower-resolution color data is added to a high-resolution greyscale image. So thanks to this blog post, I was able to find out what I needed to do to make that happen in QGIS (and Orfeo Toolbox).

Of course, it would be too easy for that to work. I didn’t have the Orfeo Toolbox installed which that needed, and ended up having to compile that from source code.* When the compiler finished and the program was installed, I went to tell QGIS where it was—but a bug in QGIS prevented me from entering the folder location. First, having just installed and compiled stuff, I attempted to get the latest version of QGIS and many of the tools on which QGIS relies. Being unsuccessful in making all of those and some of the compiler configuration software play nicely with each other, I eventually remembered I could get updated packages through apt-get, which gets pre-compiled binary files put out by the maintainers of Debian Linux. That solution worked, I added the folder location, and now I can have my pan-sharpened images.

Here for your viewing pleasure is my first properly pan-sharpened image: Heard Island on Nov. 20, 2015, seen in “true color” by the Advanced Land Imager (ALI) on the EO-1 satellite.** I’m not convinced it’s right, and I think the contrast needs to be brought down a bit, but I think it’s close.

Heard Island in true color on Nov. 20, 2015.  Image processing: Bill Mitchell (CC-BY) using data from USGS/EO-1.
Heard Island in true color on Nov. 20, 2015. Image processing: Bill Mitchell (CC-BY) using data from USGS (EO-1/ALI).

* Knowing how to compile software from source code is a rather handy skill.
** Emily Lakdawalla has written a great explanation of what “true color” means.

Geoscientist’s Toolkit: Terra MODIS

Terra satellite being prepared for placement in the payload fairing.  Image credit: NASA (public domain).
Terra satellite being prepared for placement in the payload fairing. Image credit: NASA (public domain).

In my previous post on satellite communications, I discussed two types of satellites: geostationary and low-Earth-orbit. One of NASA’s low-Earth-orbit satellites, orbiting at an altitude of 705 km (438 mi), is Terra.

Launched in December of 1999, Terra is in a polar orbit, and is sun-synchronous—it makes its north-to-south pass on the daylight side of Earth, crossing the equator around 10:30 AM in the local time zone. As 10:30 AM moves around the Earth, so too does Terra, with each orbit taking 99 minutes.

Aboard Terra is one of my favorite instruments: the MODerate resolution Imaging Spectroradiometer, or MODIS. Unpacking the name, we find that MODIS has moderate resolution: its best resolution is about 250 m/pixel. It is an imaging instrument (i.e. it sends back pretty pictures), and it is a spectroradiometer, meaning that it measures the amount of light (radiometer) across a spectrum of wavelengths (visible and infrared, in this case). Most of my use of the instrument is for its true-color imagery, or “Bands 1-4-3” (corresponding to red, green and blue). An example image is shown below.

Minneapolis area seen by NASA's Terra satellite Sept. 30, 2015.  The Minneapolis and St. Paul airport is the concrete-colored smudge just left of center; St. Cloud is in the upper left, Winona toward the bottom right, and at furthest bottom right is La Crosse, WI.  Image credit: NASA (public domain).
Minneapolis area seen by NASA’s Terra satellite Sept. 30, 2015. The Minneapolis and St. Paul airport is the concrete-colored smudge just left of center; St. Cloud is in the upper left, Winona toward the bottom right, and at furthest bottom right is La Crosse, WI. Image credit: excerpt from NASA imagery (public domain).

MODIS is a push-broom type imager. It takes one very wide “picture” (2,330 km East-West), and splits that into 36 spectral bands. As the spacecraft flies (North-to-South), those wide “pictures” are put together along the track of the satellite to create a swath image. The instrument’s resolution is highest at the center of the image.

One great thing about MODIS is that it has pretty good spatial coverage (that’s the advantage of the moderate resolution). In 24 hours, it will get images of most of the Earth, but with a few gaps between swaths at the equator. Orbits are offset day-to-day (with a 16-day cycle), so it takes two days to get full global coverage. Global maps are produced daily (give or take) by NASA Earth Observations, and tend to have a day or two of lag behind real-time.

Terra MODIS image of Earth, Oct. 7, 2015.  The tan-grey streaks in the center of the swath over some equatorial regions is caused by glare from the sun reflecting off the ocean surface.  Image credit: NASA Earth Observations (public domain).
Terra MODIS image of Earth, Oct. 7, 2015. The tan-grey streaks in the center of the swath over some equatorial regions is caused by glare from the sun reflecting off the ocean surface. Image credit: NASA Earth Observations (public domain).

You may notice that in the picture of the whole world, Antarctica is nicely lit up, but the data for the North pole is missing? What’s up with that? Is NASA taking part in a conspiracy with Santa to hide his gift-production and distribution facilities?

In a word: no.

In more words, having recently passed the September equinox (autumnal equinox to folks in the northern hemisphere), the North pole is now in darkness at 10:30 AM “local time”. It doesn’t really matter what you choose as local time, because it’s dark regardless. With it being dark, the instrument is off.

Beyond pretty pictures, Terra MODIS is used for scientific purposes. Its images can detect wildfires,[1] be used to estimate area burned by fires, monitor drought severity and snow cover, study aerosols and atmospheric pollutants, and even chlorophyll (phytoplankton) concentrations in the ocean.

Using the images to understand the productivity of plants can in turn influence the estimates for how much carbon is being removed from the atmosphere, and can serve as a gauge of ecosystem health in remote areas. Volcanic eruptions, major wildfire events, and even thick pollution from human sources can be seen in these images. By analyzing MODIS data, scientists can gauge how much of various types of atmospheric gases are being emitted by wildfires.[2, 3]

***
[1] Near-real-time swath data are available from the Rapid Response website.

[2] Mebust, A. K., Russell, A. R., Hudman, R. C., Valin, L. C., and Cohen, R. C.: Characterization of wildfire NOx emissions using MODIS fire radiative power and OMI tropospheric NO2 columns, Atmos. Chem. Phys., 11, 5839-5851, doi:10.5194/acp-11-5839-2011, 2011. [Open access]

[3] Mebust, A. K. and Cohen, R. C.: Space-based observations of fire NOx emission coefficients: a global biome-scale comparison, Atmos. Chem. Phys., 14, 2509-2524, doi:10.5194/acp-14-2509-2014, 2014. [Open access]

Geoscientist’s Toolkit: QGIS

QGIS screenshot, showing Heard Island.  Brown is land/rock, blue are lagoons, and the dotted white is glacier.
QGIS screenshot, showing Heard Island. Brown is land/rock, blue are lagoons, and the dotted white is glacier.

One of a geoscientist’s most useful tools is a geographic information system, or GIS. This is a computer program which allows the creation and analysis of maps and spatial data. Perhaps the most widely used in academia is ArcGIS, from ESRI. However, as a student and hobbyist who likes to support the open-source software ecosystem, I use the free/open-source QGIS.

QGIS can be used to make geologic maps of an area, chart streams, and note where certain geologic features (e.g. volcanic cones) are present. For instance, at the top of this post is a map of Heard Island that I’ve been playing with, from the Australian Antarctic Division. It is composed of three different layers, each published in 2009: an island layer (base, brown), a lagoon layer (middle, blue), and a glacier layer (top, dotted bluish-white).

I believe I have mentioned here previously that one interesting thing about working with Heard Island is that with major surface changes underway (glacial retreat, erosion, minor volcanic activity), the maps become obsolete fairly quickly. This week I have been learning about creating polygons in a layer, so that I can recreate a geologic map from Barling et al. 1994.[1] One issue I’ve come up against, though, is that the 1994 paper has some areas covered in glacier (from 1986/7 field work), whereas my 2009 glacier extent map shows them to be presently uncovered. In fact, even the 2009 map shows a tongue of glacier protruding into Stephenson Lagoon (in the southeast corner), while recent satellite imagery shows no such tongue.

During the Heard Island Expedition in March and April, 2016, I hope that we will have time to go do a little geologic mapping. Creating some datasets showing the extent of glaciation (particularly along the eastern half of the island) and vegetation, as well as updating the geologic map to include portions which were glaciated in 1986/7, would be a worthwhile and seemingly straightforward project.

QGIS itself is much more than a mapping tool (not that I know how to use it), and can analyze numeric data which is spatially distributed, like the concentration of chromium in soil or water samples from different places on a study site. QGIS provides a free way to get your hands dirty with spatial data and mapping, and is powerful enough to use professionally. Users around the globe share information on how to use it, and contribute to its development.

For those looking to go into geoscience as a career, I would strongly recommend learning how to use it. I didn’t learn GIS in college (chemists don’t use it much), and somehow avoided it in grad school. But I regret not having put time in to learn it sooner. There’s all kinds of interesting spatial data, and a good job market for people with a GIS skillset (or so I hear). I have only scratched the surface of QGIS’s capabilities with my use of it, but I definitely intend to keep learning. You can probably follow the day-to-day frustrations and victories on my Twitter account (@i_rockhopper).

***

[1] Barling, J.; Goldstein, S. L.; Nicholls, I. A. 1994 “Geochemistry of Heard Island (Southern Indian Ocean): Characterization of an Enriched Mantle Component and Implications for Enrichment of the Sub-Indian Ocean Mantle” Journal of Petrology 35, p. 1017–1053. doi: 10.1093/petrology/35.4.1017

Compton Glacier Calving Seen from Space

Heard Island on a clear morning, seen by the MODIS instrument on NASA's Terra satellite.  July 31, 2015.  Image credit: NASA GSFC (Terra/MODIS).
Heard Island on a clear morning, seen by the MODIS instrument on NASA’s Terra satellite. July 31, 2015. Image credit: NASA GSFC (Terra/MODIS).

July 31st was a remarkable day on Heard Island, for several reasons. First, the weather was clear—a rare event in itself. Second, both NASA’s Terra and Aqua satellites had Heard Island reasonably near the center of their swath images. That’s not super-rare, but it’s probably <25%. Third, not only was the weather clear, but it was clear for both satellite overpasses, so both Terra and Aqua had good views of the island.

Many days, as I check the satellite images to see if Heard Island is visible, I end up playing “where in this image is Heard Island”. Imagine my surprise when I saw the Terra MODIS preview image from the morning pass, and there was a nice, bright white spot with some swirling grey vortices pointing toward it. The full-resolution image is shown above (cropped). It’s exactly the charismatic image I watch for, even though the resolution is moderate.*

I scrolled down the page to the Aqua MODIS images, which come from the early afternoon. Although Heard Island was a little off to the side of the image, leading to some artifacts, it was still free of the usual obscuring clouds. What a day! Two great images from when the island was within the usable part of the MODIS swaths.

Heard Island, standing in stark contrast to the dark blue waters of the Indian Ocean, July 31, 2015.  Image credit: NASA GSFC (Aqua/MODIS).
Heard Island, standing in stark contrast to the dark blue waters of the Indian Ocean, on the afternoon of July 31, 2015 as seen by NASA’s Aqua satellite. Image credit: NASA GSFC (Aqua/MODIS).

As I looked more closely, I noticed something odd about the afternoon image: Compton Lagoon, in the northeast corner of the island, had a very odd shape. Usually it looks rather like it does in this map from the Australian Antarctic Division:

Topographic map of Heard Island, published July, 1999.  Compton Lagoon is prominent in the northeast.  Image Credit: Australian Antarctic Division.
Topographic map of Heard Island, published July, 1999. Compton Lagoon is prominent in the northeast. Image Credit: Australian Antarctic Division.

Let’s look more closely at the satellite images.

Heard Island, morning of July 31, 2015. (Terra MODIS, as above; annotations mine).
Heard Island, morning of July 31, 2015. (Terra MODIS, as above; annotations mine).
Heard Island, afternoon of July 31, 2015.  (Image from Aqua MODIS, as above; annotations mine).
Heard Island, afternoon of July 31, 2015. (Image from Aqua MODIS, as above; annotations mine).

Some of the difference between images comes from the North Barrier ridge, which runs from high up the volcano down to the west of Compton Lagoon, bounding the Compton Glacier to the northwest. With the sun in the northeast in the morning and northwest in the afternoon, the ridge stands out much more in the afternoon when it casts a shadow on the light glacier.

The lagoon, however, is quite different. Much of what was blue lagoon in the morning is grey in the afternoon, and the glacier seems to be a bit darker grey near its toe. I interpret that as evidence for a significant calving event, where ice, snow, and rocks from the glacier break off and slide/fall into the lagoon. A wind from the northeast (evidenced by the clouds) helps to keep the floating ice toward the west end of the lagoon.

Of course, it would be nice to have a second image showing the ice floating around in the lagoon, or a higher resolution image of the glacier. Unfortunately, since these images were taken, the images have been cloudy and/or off to the side of the field where distortion and artifacts are at their worst. I was hoping that the EO-1 satellite or Landsat 8 would get a good image with their 30 m resolution, but that doesn’t seem to be the case. That just goes to highlight how incredible these images are!

***

* That’s the MOD in MODIS, the MODerate resolution Imaging Spectroradiometer; at its best (directly beneath the satellite) the resolution is 250 m/pixel.

Geoscientist’s Toolkit: New Horizons

Artist’s rendering of the New Horizons probe. Image credit: NASA.

This week, NASA’s New Horizons spacecraft flew past Pluto.

Pluto, full-disk in true color, as seen by the New Horizons probe, July 14, 2015.  Image credit: NASA/Johns Hopkins University Applied Physics Laboratory/Southwest Research Institute.
Pluto, full-disk in true color, as seen by the New Horizons probe, July 14, 2015. Image credit: NASA/Johns Hopkins University Applied Physics Laboratory/Southwest Research Institute.

Exploring other worlds up close, and which are different from our own, can be very informative. We may have theories about the composition of worlds like Pluto, of how it formed, how it behaves, and what its surface is like. However, it is not until we go there that we can truly test those hypotheses. In many cases, when we are dealing with worlds vastly different from our own, what we find is surprising, mysterious, and awe-inspiring.

For instance, most pre-New Horizons models would have made Pluto out to be a fairly heavily cratered object, not unlike the Moon. However, that was not at all what was found. The first high-resolution picture released during the flyby, part of a mosaic which is still being put together, had no craters visible. None.

High-resolution image of Pluto's surface, near Tombaugh Regio, taken from 77,000 km above the surface.  Notice the lack of craters in this image.  Image credit: NASA/Johns Hopkins University Applied Physics Laboratory/Southwest Research Institute.
High-resolution image of Pluto’s surface, near Tombaugh Regio, taken from 77,000 km above the surface. Notice the lack of craters in this image. Image credit: NASA/Johns Hopkins University Applied Physics Laboratory/Southwest Research Institute.

Given that the history of Pluto is likely to have included significant bombardment by smaller objects, this result makes us rethink our model of the processes happening on Pluto’s surface. From what we know of the frequency of impacts, these surfaces would need to have been recently (geologically speaking, so in the last ~100 Ma) formed, eroded, or otherwise modified.

It is encounters like this which help us understand and consider our models, and to recognize which properties of large rocky bodies are important under which circumstances. What is reshaping Pluto’s surface? How did the various terrains form? Do they happen elsewhere? Where does the energy for these processes come from?

Exploring other worlds keeps our thinking fresh, challenges our assumptions, and inspires us to create new models and experiments to better understand our solar system and our own Earth.

Exploring Capitol Rock, MT

Wide-angle view of Capitol Rock, MT.  Image credit: Bill Mitchell (CC-BY)
Wide-angle view of Capitol Rock, MT. Image credit: Bill Mitchell (CC-BY)

Several weeks ago, I took a road trip with some friends across the northern part of South Dakota as part of a ham radio adventure. When we reached northwestern South Dakota, we were having so much fun that we decided to continue into just across the border into Montana.

At the state line between South Dakota and Montana, we found that there was a relatively high point (Capitol Rock) which we could probably access with our vehicle. Capitol Rock is in a national forest, so no permission would be needed to go there. It would be a good place to do ham radio (primary goal), and it would get me close to some rocks (bonus)!

As we drew closer to the summit of the hills, I couldn’t help but think that the rocks looked a lot like the ones in my research area in northeastern Montana, in the Hell Creek region (Hell Creek and Tullock/Fort Union Formations).[1]

Sadly, I didn’t get quite as close to the outcrops as I would have liked (we were on a bit of a schedule), but I did get some pictures and made a few observations.

North half of Capitol Rock.  Image credit: Bill Mitchell (CC-BY).
North half of Capitol Rock. Image credit: Bill Mitchell (CC-BY).

Here we had flat-lying sedimentary strata, presumably of roughly Cretaceous-Paleogene age (somewhere around 80-50 million years ago, Ma) (introduction to geologic time). These would have been shallow marine or terrestrial sediments from along the western interior seaway, which was on its way out at the end of the Cretaceous (66 Ma, [1]). I would expect to find some fossils preserved in the sediments, and from those, a fairly accurate date on the strata could be obtained. There may even be some volcanic ash deposits which would allow for direct dating using the U-Pb system or the K-Ar system (Ar/Ar dating) .

At the top of Capitol Rock were several massive units with a slight orange color (probably from oxidized iron). Beneath those were some more finely bedded strata, with bed thicknesses probably around 3-10 cm (eyeball estimation), and displaying some rough texture (popcorn texture?). Underneath those were some fairly easily eroded strata of generally uniform grey color. The image below has these observations annotated.

Northern portion of Capitol Rock, annotated.  Image credit: Bill Mitchell (CC-BY)
Northern portion of Capitol Rock, annotated. Image credit: Bill Mitchell (CC-BY)

The ground under my feet for that previous picture was still above average terrain. Here is an additional picture, taken from the south (looking north), which shows that the light-grey sediments are underlain by more yellow-orange units.

Distant photograph of the lower portion of stratigraphy underlying Capitol Rock.  Image credit: Bill Mitchell (CC-BY).
Distant photograph of the lower portion of stratigraphy underlying Capitol Rock. Image credit: Bill Mitchell (CC-BY).

Upon returning home, I decided to see what description I could find online of Capitol Rock’s geology. It seems there are a number of different descriptions of it.

Capitol Rock, located in the Long Pines Unit in Montana, is a massive white limestone uplift that resembles the Nation’s capitol building.
Montana Office of Tourism

Capitol Rock, located in the Long Pines land unit in Montana, is a massive white sandstone remnant which originated as a volcanic ash deposit. This unique formation resembles the Nation’s Capitol Building in Washington, DC.
US Forest Service

The Bureau of Land Management (BLM) has an interesting discussion of the geology of this area from the perspective of firefighting, specifically in the avoidance of fibrous or asbestos-like minerals which are present in some of the formations in the area:

Brule Member, White River Formation [ed: Formations are a larger stratigraphic unit, and can include multiple Members] – may only be present at Capitol Rock (SE 1/4 sec. 17; T3S; R.62 E) in the Montana portion of the Sioux District. Located at the base of the Arikaree Formation. Massive pinkish gray, calcium containing, clayey siltstone: nodular claystone: and channel sandstone. Contains abundant vertebrate fossils. Thickness 0-30 ft. The member is composed of massive pink clay, exposed in the badlands just Southeast of Reva Gap, well-bedded, hard pale green sandstones alternation with very pale brownish gray clay.
Weathering causes a tread and riser affect much like a staircase. Both the sandstone and the clay are generally calcareous and Bentonitic. The lower portion of the vertical cliffs in Slim Buttes is generally Brule.

Chadron Member, White River Formation – only located in the southern Long Pines within Montana. Found at the base of the Arikaree formation and beneath the Brule Formation at Capitol [R]ock (SE 1/4 sec. 17 T, 3 S., R. 62 E). Basal conglomerate sandstone overlain by beds 10 to 15 ft
thick of dark gray bentonite and cream colored siltstone. Thickness 0-100 ft.
Bureau of Land Management

Well, that’s a puzzling bunch of information, isn’t it! Various sources are suggesting limestone, sandstone from volcanic ash, and a mix of sandstone and siltstone. There’s one more source to check, too: the geologic map. Specifically, we’re interested in the Ekalaka 30’x60′ quadrangle from the Montana Bureau of Mines and Geology!

In the geologic map (look along the right [eastern] edge, near the “T 19N” mark; Capitol Rock is ~1 km NE of the “Tar” label] we see the Fort Union Formation (informal Ekalaka member) at the base of the hills (i.e., under my feet), which is consistent with observations and the relatively detailed presentation from the BLM. It is also consistent with my experience that the Fort Union Formation is generally yellow-orange (in contrast to the drab, grey of the Hell Creek Formation). Then things get trickier. The rocks right at Capitol Rock are mapped as “Tar”, which is the Tertiary Arikaree Formation.

So, what is the Arikaree Formation? Well, the USGS has this to say:

Arikaree formation: gray sandstone with layers of concretions; contains volcanic ash and, locally, channels filled with conglomerate; known only in southeastern Montana.

On the other hand, the North Dakota Department of Mineral Resources breaks the Chadron, Brule, and Arikaree into distinct formations unto themselves.

I suspect this is all hitting at an important point: mapping is really hard, as is saying the rocks over here are the same as the rocks 40 km away. These difficulties are compounded when different scientists use different terminology, such as when the mapping is done by state geological surveys. The same rocks may change names when a state boundary is passed. Sometimes researchers will use the terminology from one state to apply to the rocks on both sides of the boundary, and then the literature is filled with multiple terminologies for the same rocks. It can also be very difficult to correlate rocks laterally over large distances, especially when there is poor outcrop over those distances (i.e. between buttes).

Here’s my interpretation of what’s going on at Capitol Rock: it is composed of siltstone, sandstone, and altered volcanic ash [still good for U-Pb dating!]. This volcanic ash is high in erionite, an asbestos-like mineral. Naming of the unit could include either the Arikaree Formation, or the Brule Member of the White River Formation. An age of 37–30 Ma seems reasonable.

***

[1] Renne, P. R., Deino, A. L., Hilgen, F. J., Kuiper, K. F., Mark, D. F., Mitchell, W. S., III, Morgan, L. E., Mundil, R., Smit, J. (2013) Time Scales of Critical Events Around the Cretaceous-Paleogene Boundary. Science 339: 684-687, doi: 10.1126/science.1230492.