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Category Archives: geologic mapping

For better context, here is a 1:1,000,000 map of Clark County showing where the area in the previous post is located. The map we are trying to complete as Phase 1 of the Nevada Digital Dirt Mapping Project will be approximately 1:150,000. The tiling evident in this image is because the data are divided into the appropriate 100k sheets. For more background on the project, check out the Nevada Digital Dirt Mapping blog. Yes, there is some cross-posting going on…how else could I manage all of this stuff?

I have a tendency to map in great detail…even when it is unwarranted or relates to a largely inconsequential stratigraphic situation. This problem is proportional to the quality of the base imagery that I have or the intrigue-level of the units in the field. However, in my quest to lead the effort to develop a surficial geologic map of 10,000 sq. km. of dirt in Clark County in a compressed time frame (see:, I am learning that it is ok not to sweat the details, as long as you explain what comprises the mapped units. One thing that we have learned is that it is essential to develop an agreed-upon minimum map unit area (mmu). That is, the smallest polygon that is mappable at the chosen scale.

As far as I can tell, geologists are not very keen on the mmu, whereas the dirt mappers in the NRCS have codified the concept in their considerably more standardized procedure.
We have adopted a visual approach that is based on the basic legibility of a polygon at a specific scale, and have concluded that 10 hectares is a good minimum value to start with. 10 ha is 100,000 square meters…or a square that is approximately 316 meters on a side. Sounds kinda big, looks quite big in the field, and certainly looks mappable at 1:24,000. However, if you zoom out to 1:100,000, the story changes.
The map below shows a random area in the county at 1:24,000. A selection of polygons is labeled with respect to size in hectares.

Sure, those all look totally mappable, right? Well, not so much. Check out the area when outlined in a 100k map:
Now the story is different. Not only are the small polygons bordering on illegible, the scale of the task of mapping such small polys consistently in a reasonable amount of time is impractical without a huge expenditure of time.
There are some side effects of eliminating units below a certain size threshold. One is data loss. That will be handled by preserving the small polys as points. Thus their locations will be stored as will their attributes. This solution can also facilitate the mapping process by flagging those polys that need to be absorbed into larger, surrounding or adjacent ones. One other problem is the case of high-standing inselbergs. Some of these are very tiny, but protrude several meters above the surrounding surficial deposits. Thus, their omission is particularly notable when in the field. For example, in the photo below, the fairly conspicuous cluster of red sandstone inselbergs has an areal extent of approximately 10 ha.
Not mapping such a feature may seem like a total affront to the sensibility of a geologist, but there will be a point there in the dataset that indicates an awareness of the feature’s existence.
What do you think? Do you know of a standard mmu? Does 10 ha look to big?

Posted via email from Fresh Geologic Froth

Yet another map for 2009…don’t get to excited, though. I won’t
subject you to my rant about how I get surprisingly little credit for
these gargantuan efforts until they are subjected to an external
review…that is for another day. Trust me, it will come. Probably in
mid January.

In any case, this new map includes a snippet of surficial mapping that
I and others did a few years ago in the entirety of Ivanpah Valley,
Nevada…’The Ivanpaviathan‘ with some minor changes.

The big story here is the huge amount of work that the first author
did in creating the bedrock mapping. This is a complicated area to say
the least (heard of the Keystone Thrust and its ilk?). Larry did a
fair amount of new mapping, but really went the extra mile in
compiling diverse scraps and swaths of mapping created over the years
by the other authors. No small task.

Now, about that missing cross section…

Kudos also to Irene for converting what was initially a ‘symphony in mustards’ to this nice map.

See also:

Posted via email from Fresh Geologic Froth

Recall when I went on ad nauseum about my struggles with the Lower
Walker River map as I was trying to document (in part) the struggles
that the lower Walker River has had in dealing with its shrinking
lake? If you missed that fun, experience it here:

Well, I hardly made a peep about this map…mainly because it
was finished earlier and was out of the ‘buffer’ at the time. But now,
it has reached a comparable state of completion.

The twist with this map (which is along the lower Colorado River
between Hoover and Davis Dams) is that the river has lost its battle
with a lake by virture of having been dammed downstream. Thus, all of
the bluish-greenish units are submerged under the lake.

I was able to map these features with reasonable confidence using
sonar data and large-scale, pre-dam topographic maps of the valley.

Interesting side note: Since getting the map to this point, I have
gotten my hot little hands on a pre-dam aerial photo mosaic of the map

Revision time!

Posted via email from Fresh Geologic Froth

It is tortured river season in my office. Lately, I have been tackling Nevada’s mighty Walker River and its shrinking terminal lake (new term is terminus lake…but that is a bit soft); and Oregon’s Owyhee River and its travails with lava and landslides; but now I am back on to the Mighty Bill Williams River of Arizona. You know, the Bill Williams River.

Included below is a snippet of the map I am working on. Shown are 6 generations of lines that document major changes in the channel, most since a dam was finished in the late 60s. One day soon, this map will actually make sense, I promise.


The BWR is a special case. It is a roughly 35 mi stretch of river that traverses the hot desert below the confluence of two rivers that collectively drain more than 5000 square miles of western Arizona. Alamo Dam sits just below the confluence and traps essentially all of the sediment that would otherwise have gone down the BWR and to the Colorado River (well, at least to Lake Havasu). Also important to note is that the pre-dam BWR could attain peak discharges ranging up to 100,000 cfs, whereas the post-dam BWR can hardly exceed 7000 cfs owing to the outlet works of the dam. Thus, large runoff events that would have otherwise blasted through the system in a week or less (Spikes) are now converted to protracted, flat-topped hydrographs that lumber through the channel for up to several weeks to months (Bricks). Recall that these bricks are also sediment-free except for the sed picked up in the channel below the dam.


The result is an interesting experiment in channel change, sediment budgeting, and inadvertent (or otherwise) tamarisk farming.


I won’t be posting daily updates of this map, so don’t worry. Be assured, however, that I will make a lot of noise when I finally finish it. This one is a long, long, long, time coming. Just ask the sponsors.


Some other BWR info:


Posted via email from Fresh Geologic Froth

Sure, I have gone on and on about the amazing visualizations you can get with some tweaking of LiDAR data; however, it turns out that a pretty basic representation is also quite useful…contours. Yes, contours. Sometimes smaller scale features remain somewhat ambiguous in hillshades or slopeshades, but high-res, short interval contours from the LiDAR data can eliminate most of the ambiguity. In this case, it is a tiny area that I have struggled with on the Owyhee River. Here, a large landslide entered from the north, shoved the river channel to the south, and the river eventually worked its way back to the north to some extent. The array of surficial deposits in the void that comprises the right hand side of the image south of the river record this sequence of events as well as subsequent sedimentation by tributary fans. The contours really highlight the fans, and in conjunction with discernible drainage patterns evident in the LiDAR, it is clear what is fan and what is river, right?

2-m Contours were generated in GlobalMapper and exported as shapefile to view in Arc.
Note, Ian Madin (at DOGAMI) gave me the tip on contours especially as they relate to resolving fan features. He was right…it works!

Posted via email from Fresh Geologic Froth

I created this lake by generating a contour from the LiDAR dataset at an elevation of 1046 m. GlobalMapper does this in about 1.5 minutes. Then, exported the vector as a shapefile, cut out the parts of the line that occur downstream from the dam, stitch the remaining loose ends, build a poly from the line and there it is.

This lake has an interesting topographic correspondence with the old landslides on the south side of the Hole in the Ground as well as the ancient fan remnants that come in from the north side. Don't forget that much of the topography you can see through the lake didn't exist at the time of the lava dam. The valley floor was probably formed on the Bogus Rim lava which forms the flat-topped features that flank the left and right banks of the river near the eastern end of the lake. The top of the Bogus Rim lava is only about 25 m below the surface of this lake. Thus, the link between this lake and the landslides is dubious as there was nowhere for the landslides to slide.

Posted via email from Fresh Geologic Froth

I’ve said it before, and I am sure I will say it again. But this time Google Earth is really making a major difference in my approach to making a geologic map.

My mapping project on the Lower Walker River and the piedmont of the Wassuk Range, NV is taxing my skills as a geologist and as a mapper. It is an extremely complicated setting with active tectonics, catastrophic debris flows, rock avalanches, a wildly fluctuating terminal lake, and a river madly scrambling to keep up with the lake’s rapid, historical decline (50 m in ~100 years). Documenting the ancient, historical, and recent shorelines along the lake is a key component of developing a fairly tight chronology of alluvial fans, abandoned delta lobes, and Quaternary fault activity. However, efficiently digesting all of this information is a far more laborious task with the 24k USGS base maps because the relief in the area is too extreme to accommodate small contour intervals. Air photos are certainly nice, and I do have access to some marginally good LiDAR data and scattered high-precision GPS points, but nothing brings the area into full focus as easily and as efficiently as Google Earth. On this project I have explicitly incorporated GE into my mapping and it has worked extremely well.

GE allows me to quickly and repeatedly pan and zoom my map area and evaluate all of these features of interest. With particular reference to the logistics of making a geologic map, I have used GE extensively to quickly trace mappable shorelines, tag key elevations, and decide how (or whether) to group them for mapping purposes. I have also marked some of the more flagrant fault traces to improve the frame of reference for the map. Of course, I have also linked my geotagged set of field photos so that I can get some clear reminders about key areas I am mapping. The map is being compiled in ArcGIS with good imagery (NAIP) and I can simply transfer my interpretations by visual inspection. Of course, I keep turning to GE to check things out in detail because, somehow, the clarity of the imagery far exceeds what I can force out of the NAIP. Likely I will turn the map of this intriguing area into a kml project. Best area yet for that.

Posted via email from Fresh Geologic Froth

I am late on reporting these useful tidbits and for that I apologize. I learned of these techniques from Ian Madin from DOGAMI while I was at the AASG meeting in Park City way back in June. Ian is my LiDAR hero for the time being. Basically, he showed me some simple tricks that make complete sense in hindsight but struck me as nothing short of revolutionary when I applied them to my data set. Before I get into it, I will say again that LiDAR changes everything. It is a truly revolutionary tool for geologic mapping of any kind, but particularly for surficial geologic mapping.

OK. So you have your LiDAR and you love the super neato hillshade images that it can be used to generate. But, hey, what about those damn shadows in areas of key interest? Well, you can apply a redundant brute force approach to making hillshade images with different solar geometries…but that would be downright nutty. You could crank it up a methodological notch and use GlobalMapper or Surfer to create these images far more quickly and choose your favorite to export…but that would be silly as well (but kind of fun…except for the exporting part).
Step back and think about what you are trying to visualize with the hillshade….wait for it….slopes, right?!. So, what you do is effectively create a universal \ isotropic (?) hillshade image by using the ‘slope’ tool in the ArcGIS toolbox (3D analyst\ raster surface\ slope). Trust me, it works. However, you can’t just go with the default settings. You have to stretch the resulting data (std dev works best for me), invert the grayscale ramp (important) and sit back and take it all in. Sweet! But wait, you need to overlay a slightly tranparensized color ramp of the elevation data (stretched as well for simplicity) to make it tasty. Now you have it all. For some real fun, change the n value in the standard deviation stretch and see what happens (maybe stay between 1 and 3).
Click through the photoset for some comparisons and you just may become a believer. Obviously, having all of these visualizations at your immediate disposal is the way to go…the beauty of GIS for geology, no?
Maybe you noticed that the last one has a comfortably smooth contour overlay…how the hell did that get there? Stay tuned for a tip that even took an ESRI LiDAR braniac by surprise at the Users Conference.

Posted via email from Fresh Geologic Froth

I recently acquired a Wacom Cintiq Interactive Pen Display and it was worth every penny of the $1999 that it cost me. Sure, that sounds like a lot. However, I work on a lot of maps. Without going into detail, I will just note that my commitment to over-commitment is a problem. I truly need to develop ways to more quickly and accurately compile my mapping in a digital form.

Nothing (aside from LiDAR, maybe) has streamlined my mapping workflow more than being able to map directly on the surface of a high-resolution monitor. It is one-step beyond my previous advice to run out and get yourself a wacom digitizing tablet because it removes the final level of abstraction that separated your eyes from your work. Since the monitor is quite pricey, it may be a stretch for the average ‘joe’ (you know who you are). The next best step, the digitizing tablet, is an excellent way to go if that is your limit. Put plainly, you are a pitiable fool for not using either of them. Sorry to say that, but it is true.  Deal with it.

I will admit that some of my colleagues that I have goaded into trying the tablet (haven’t let anyone touch the monitor yet) have had some issues and, unbelievably, returned to clicking their freaking mice for miles across the virtual landscape. As I have said in the past: can your write your name with your mouse…of course you can’t. Why then do you think you can map your favorite intricate contact with one better than you can with a pen? The digitizing tablet / monitor approach is far more efficient. You can program buttons on the pen and the tablet to substitute for frequent commands you use in the program of interest. In the case of the tablet, you can change its inclination to suit your ergonomic needs and can even freely rotate it through a large range of angles to get the perfect attack on the cryptic  contact you think is so important.

The Cintiq rocks for geologic mapping. Convince your boss to buy one, or write it into your next geologic mapping proposal. Don’t be a slave to a mouse…how embarrassing is that?

Disclosure: I am left-handed but also moderately ambidextrous. I use my mouse with my right hand. I use the pen in my left. I use them both when madly mapping in ArcGIS.

Dr. Jerque hard at work