Now, for WOGE 525, we leave the desert behind. Your task is to find the location of this image, as well as to post a comment with a description of the important geology, hydrology, or other -ology shown in the image.
To encourage first-time players, I would ask that any previous winners wait until at least 20:00 1/15/2016 UTC before posting (roughly 24 hours). Rules, hints, and a .kml file with previous WOGE locations can be found here.
Update 0055 UTC 1/25/2016: In the east of the WOGE 525 scene is a reservoir. The next (downstream) widening of the waterway is here:
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.
* 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.
With 2016 now upon us, I felt it would be appropriate to think about what a new year means for uranium geochronology. What can we expect from the year ahead? Without getting into any of the active research going on, I felt it would be useful to address simply what is physically happening.
On Earth, there is roughly 1×1017 kg of uranium. The ratio of 238U:235U is about 137.8:1, and 238U has a mass of roughly 238 g/mol (=0.238 kg/mol). Looking only at 238U, that gives us 1x1017[kg]x(137.8/138.8)/0.238[kg/mol] = 4.17x1017 mol [238U]
Radioactive decay is exponential, with the surviving proportion given by e-λt where λ is the decay constant (in units of 1/time) and t is time, or alternatively, e-ln(2)/T1/2*t, where T1/2 is the half-life and t is time.
To find the proportion that decays, we subtract the surviving proportion from 1: (1-e-λt)
Multiplying this proportion by the number of moles of 238U will give us the moles of decay, and multiplying by the molar mass will give the mass lost to decay:
Plugging in numbers, with λ238 = 1.54*10-10 y-1, t = 1 y and the moles of 238U from above, we get:
That yields (with proper use of metric prefixes) roughly 64 Mmol U decay, or 15 Gg of U on Earth that will decay over the next year.
Although those numbers sound very large, they are much smaller than even the increase in US CO2 emissions from 2013 to 2014 (50 Tg, or 50,000 Gg); total US CO2 emissions in 2014 were estimated at 5.4 Pg (=5.4 million Gg).[US EIA]
As for what’s in store for geochronology as a field, I think there will be a lot of discussion and consideration regarding yet another analysis of the Bishop Tuff. Dating samples which are <1 Ma (refresher on geologic time and conventions) using U/Pb can be tricky, and Ickert et al. get into some of the issues when trying to get extremely high-precision dates from zircons. The paper is not open access, but the authors can be contacted for a copy (@cwmagee and @srmulcahy are active on Twitter, too!).
 J. L. Crowley, B. Schoene, S. A. Bowring. “U-Pb dating of zircon in the Bishop Tuff at the millennial scale” Geology2007, 35, p. 1123-1126. DOI: 10.1130/G24017A.1
 K. J. Chamberlain, C. J. N. Wilson, J. L. Wooden, B. L. A. Charlier, T. R. Ireland. “New Perspectives on the Bishop Tuff from Zircon Textures, Ages, and Trace Elements” Journal of Petrology2014, 55, p. 395-426. DOI: 10.1093/petrology/egt072
 G. Fiorentini, M. Lissia, F. Mantovani, R. Vannucci. “Geo-Neutrinos: a short review” Arxiv2004. arXiv:hep-ph/0409152 and final DOI: 10.1016/j.nuclphysbps.2005.01.087
 R. B. Ickert, R. Mundil, C. W. Magee, Jr., S. R. Mulcahy. “The U-Th-Pb systematics of zircon from the Bishop Tuff: A case study in challenges to high-precision Pb/U geochronology at the millennial scale” Geochimica et Cosmochimica Acta2015, 168, p. 88-110. DOI: 10.1016/j.gca.2015.07.018