Sunday, March 17, 2019

From crashing kites and Frankenmodels to efficient large-scale UAV acquisitions and beautiful shared 3D models (2018 GSA talk)

I was invited to give a presentation in a session at the Fall 2018 Geological Society of America session T60. Revolutions in Remote Sensing: Applications of UAVs to Field Mapping and Surface Analytics (organized by Dylan Blumentritt--Winona State University and Toby Dogwiler--Missouri State University). I decided to make a my presentation a bit of a reflection of how my own obsession with low altitude imaging had evolved and how far we had come. After all, I started in college working in the Fairchild Aerial Photography Collection when it was at Whittier College. So, I came up with a talk with the hopefully entertaining title of FROM CRASHING KITES AND FRANKENMODELS TO EFFICIENT LARGE-SCALE UAV ACQUISITIONS AND BEAUTIFUL SHARED 3D MODELS. I am putting links to the talks on line in case they might be useful: PPT and PDF.

The presentation shows a couple of maybe interesting things:

  1. It shows a pretty 3D point cloud (video above) from our Photogrammetric model of the Tecolote Volcano, Sonora, Mexico hosted at
  2. It spends some time talking about and making the case for the OpenTopography Community Dataspace.
  3. As part of the OpenTopography Community Dataspace discussion, I (with slides and ideas from Chris Crosby) talked about standardizing metadata for these long tail data. See for example the different styles of metadata documents ("Survey Report"): for example Almaty range front fault, Koram site or Clear Creek, Idaho post-fire debris flow erosion--note the ones I uploaded are not great examples :).
  4. Of course, one of the really nice things that the OpenTopography Community Dataspace publishing of one's data allows is to mint a DOI. That DOI allows then for a data citation. I have added a new part of my CV that has a section on data publication. Here is an example citation style:
    Arrowsmith, J R., DiMaggio, E. N., Garello, G. I., Villmoare, B. and LediGeraru Research Project (2018): Photogrammetric model of a portion of the LeeAdoyta Basin, Afar, Ethiopia (point cloud [122M points], orthophoto [2cm/pix], and DEM [25 cm/pix]). Distributed by OpenTopography. AccessedOctober 23, 2018.

The conclusions are useful to highlight as well:

  • We are part of a revolution in 3 and 4 D data collection and analysis
  • Additional needs for the community include
    • Optimized data acquisition strategies
    • Low cost and high performance computation of point clouds and models
    • Efficient and accurate georeferencing
    • High quality differencing for change detection
    • Bring the tools and data into the (outdoor) classroom; need more curriculum (c.f. GETSI - GEodesy Tools for Societal Issues (UNAVCO) at
  • OpenTopography Community Dataspace
    • Great opportunity to expand the impact of emerging topography through improved access
    • Services and existing community of users
    • Community engagement & best practices
    • Please join us and start sharing your models and ideas for how to improve

Monday, March 11, 2019

Anniversary of Great Tohoku Japan earthquake and tsunami (20110311)

Today is the anniversary of the catastrophic great Tohoku Japan earthquake and tsunami of March 11, 2011. While I am not an expert of subduction systems nor tsunamigenesis, I was of course interested in the event and prepared some lectures about it. While there are many better and newer illustrations, I wanted to share the materials.

The first presentation was at the Arizona Science Center in 2011. Here is the folder of the materials.

I prepared a lot of content for a series of lectures at IT Bandung in Java that I presented in 2013 with the help of my former student Dr. Gayatri Marliyani. There is much high quality material at IRIS (some of which I have included). The main materials are in these three folders:

Friday, March 8, 2019

Idea for an earthquake intensity exercise based on 1857 Ft. Tejon earthquake data

I was cleaning some files yesterday and I found an old exercise I had deployed when I was first teaching Introductory Geology. It was intended to help students understand earthquake intensity (vs.) magnitude. I took the felt intensities as reported by D. C. Agnew and K. Sieh (1978), A documentary study of the felt effects of the great California earthquake of 1857, Bull. Seismol. Soc. Amer., vol. 68, pp 1717-1729 and compiled some of the more easily interpreted ones into a table and then provided a simple map of California for the students to map the intensities. Here is a link to the compiled data from Agnew and Sieh. THe work of Kerry Sieh on the 1857 earthquake is seminal. I think it was an ok exercise, but there are probably more interesting and more recent datasets. For example, I like the twitter-based work that is coming from the USGS colleagues. It should be possible to take some sample tweets and do an intensity mapping.

The 1857 earthquake and its foreshocks and aftershocks are fascinating an a sobering reminder of what will happen one day in California.

This figure from Toké and Arrowsmith, 2006 shows the 1857 foreshocks and the mainshock distribution (the latter is what the exercise mentioned in the last paragraph is supposed to look like) and compares it with the historic Parkfield earthquakes.

Monday, February 25, 2019

Updated review of fault scarp analysis

I am organizing for a presentation to my research group on fault scarp analysis. This is an ongoing obsession of mine. I have blogged about this topic here with some review. That is still a pretty good summary of things. I also have a couple of relevant Landers Earthquake posts here and here. And, we applied many of the relevant tools to analysis of cinder cone forms.

The 2017 post mentioned above is still a pretty good summary of things. However, the MATLAB-based guis for Penck1D and Scarpdater are not running well now on newer versions of MATLAB; they need an overhaul. We were really into guis back then but they require so much code relative to the actual modeling. Might be cool to rewrite in Jupyter notebooks, maybe see how much in landlab could be used.

I have prepared a new review powerpoint (PPT and PDF) with this outline:

  • Introduction and review
  • Diffusion-equation analysis of scarplike landforms
  • Observations
    • Direct dating of fault scarps
    • Fault scarp erosion monitoring
  • Modeling
    • Distributed deformation
    • Transport vs. Production limited
  • Extending processes 2D and nonlinear diffusion
  • Prospects and cautions
Of course it is incomplete and emphasizes the work of my students and colleagues. I note for example, this nice review from Wei, et al., Journal of Asian Earth Sciences, 2015:

Additional resources for my lecture include:

Some other useful web links include:

Tuesday, May 15, 2018

Specialization certificate for the assessment and management of geological and climate related risk (CERG-C) course in Geneva and Vulcano Island

I just returned from my second year of participation in the Specialization certificate for the assessment and management of geological and climate related risk (CERG-C) course in Geneva (Switzerland) and Vulcano Island (Sicily, Italy). It was stimulating, interesting, and beautiful. The course takes a "...multidisciplinary approach to the assessment and management of risk from natural hazards, merging ideas from disciplines such as the physical and social sciences, engineering, and economics" (website). The course has 8 modules and there were about 25 students from around the world participating. The course is lead by Professor Costanza Bonnadonna. Several other instructors participate and getting to know them has been quite nice. Amanda Clarke and I have joined the last few years

It is a tough place to work: view from La Fossa towards Vulcanello across the Vulcano town with Lipari and other Aeolian Islands behind

The last two years I have helped by providing a series of lectures in Geneva on topography and then participated in the field exercise on Vulcano Island (Sicily, Italy). I argue that it is a fundamental geophysical dataset for any hazard and risk assessment as it drives and resists processes and hazards. After all, potential energy = mass x gravity x relative height. Topography fits in the realm of Geodesy which is the science of accurately measuring and understanding three fundamental properties of the Earth: its geometric shape, its orientation in space, and its gravity field—as well as the changes of these properties with time. We know that surface processes act to change elevation through erosion and deposition while tectonic processes depress or elevate the surface directly. And, topography and geomorphology (study of landforms and surface processes) helps to link between timescales of seismology and crustal deformation (1-10 yr) and geology and tectonics (1-10 Myr)

Vulcano and topography and bathymetry of northern Sicily. Note that I demonstrate the very useful geomapapp.
I also demonstrate ArcGIS and show the data and topography from Vulcano.

At Vulcano, the students have the opportunity to put into practice their hazard and risk knowledge. The program starts with a field trip and lectures on the various volcanic hazards (unrest and degassing, single vulcanian, persistant vulcanian, subplinian from the main edifice ("La Fossa") and strombolian and lava flow eruptions from the adjacent "Vulcanello). Then the students work through vulnerability, warning messages, and even have a crisis exercise. They stay busy from 8 am to 10 pm. The studnet have to present almost every night a poster on what they analyzed for that day, with the assembled instructors as audience and evaluators. There are also evening lectures including a review of Italian earthquakes with extended lecture on L'Aquila by me and a very nice review of Italian Civil Protection by one of its representatives. And, one of the highlights is a volcano crisis "play" at the local elementary school in which the students have a script and take various roles as community members, media, safety staff, government officials, scientists, etc. to go throught a possible volcanic crisis at Vulcano. It was very cute and a great demosntration of how to engage communities to understand the hazards they face and what to do.

Professor Mauro Rosi from University of Pisa lecturing to the group with La Fossa vent behind.
Nice action video from the Mavic Air
INGV team demonstrating gas sampling from the fumaroles.

In order to demonstrate acquisition of topography as well as collect some for some of the research activities ongoing at Vulcano by the team, I worked with an INGV colleague Il maestro Dr. Fabio Pisciotta to collect photos from drones for structure from motion reconstructions. He has a lot of experience droning at Vulcano and was a great teacher. We teamed up with his Phantom 3 and our Phantom 4 Pro and collected more than 6000 images over the edifice. Stay tuned for the models...

Drone team.
Drone view of La Fossa.

Monday, January 15, 2018

Viewing 3D planes (discs) with a specified diameter and orientation in ArcScene

We have been pondering how to visualize planes in 3D as a way to assess correlation of beds in an area. My colleague Chris Campisano and our jointly supervised PhD student Dominique Garello was asking about this for a while. We discussed a few solutions, including the MOVE suite and RIMS among others. I know there is a lot of software out there for this.

I decided to tackle it in a very simple way with the constraint that it would only use Excel and ArcGIS (ArcMap and ArcScene). I googled around an there was not an obvious solution already.

The basic steps:

  1. Produce a disc in MS Excel by creating a circle with a specified diameter and center. Rotate the dip around N-S axis and then rotate around vertical to apply the strike (then make it the correct size and translate to correct center)
  2. Load the rim points into ArcMap, view the X Y points with elevations
  3. Create a TIN (triangulate the rim points to make the disk)
  4. Visualize it in ArcScene

I wrote a tutorial (link) and the spreadsheet is here.

Monday, October 2, 2017

Structure from Motion using video from my phone camera

Introduction. In my last post, I showed how I had extracted frames from satellite-derived video to build a 3D model of a mine from space. In this post, I show a similar workflow for phone camera: take a video of an object (some times a lot easier than numerous frames although lower quality) and make a 3D model using Agisoft Photoscan.

Video to images. (this part is repeated from the last post). The main generic challenge for SfM from video is to extract the video frames and prepare them for the SfM. The SfM part is no different from what my group has been doing for a while with Agisoft Photoscan. I used MATLAB to do the video processing. The script is here: readplanetvid.m. The main code bits include:
PlanetObj = VideoReader(videoname); %make a video object from an MP4 file
vidWidth = PlanetObj.Width; %get the width
vidHeight = PlanetObj.Height; %and height

mov = struct('cdata',zeros(vidHeight,vidWidth,3,'uint8'),...
'colormap',[]); %set up a MATLAB structure to contain the video

k = 1;
while hasFrame(PlanetObj)
mov(k).cdata = readFrame(PlanetObj); %pull out the frames one at a time from the MP4 object and put them in the mov
k = k+1;

step = floor(k/number_of_frames) %determine how many frames to skip each time to get the desired number
for i = 1:step:(k-1)
framepart = sprintf('_frame_%06d.png', i);
filename = strcat(foldername,'/',projectname,framepart);
imwrite(mov(i).cdata, filename) %easy to write the frame out as a png file

Video of a rock sample in my backyard. I took a short video of a piece of obsidian on a table with my Samsung J3. The nice thing about it was that I could gather a large number of views around the sample with relative ease. From that video, I extracted 150 frames, for example see below

I ran the files through the Agisoft Photoscan sequence of alignment (high), build dense cloud (medium), build mesh (medium), and build texture (medium). Here are a few screen captures of the result:

This one shows a somewhat complex background, but nicely indicates the path of the camera too.

And here it is with a trim to only show the sample on the table: