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Figure 2. Pseudotachylite specimen from Vredefort impact structure. ©2016 Google Inc. Image: Landsat. Map by Hartwig Frimmel. Online version can be rotated,
and is available at http://dx.doi.org/10.1130/GSATG257.S2.
GSA TODAY | AUGUST 2016 2016; TurboSquid, 2016]) was used to clean scanning errors and
reduce model size. Google Earth literally shreds models with
more than 64,000 vertices, so reducing the number of vertices is
essential for most raw scans. Of the many vertex reduction
options in MeshLab, the only one that worked whilst main-
taining specimen quality was Quadric Edge Collapse Decimation
(see the GSA Supplemental Data Repository [footnote 1]). The
model was exported from MeshLab in COLLADA format for use
with Google Earth.
MULTI-VIEW STEREO AND STRUCTURE FROM MOTION
The most exciting recent modeling innovations are in the field
of multi-view stereo (MVS) photogrammetry. Se and Jasiobedzki
(2008) used video imagery from an unmanned vehicle and the
Simultaneous Localization and Mapping (SLAM) algorithm to
monitor an active mine. An algorithm called Structure from
Motion (SfM) uses multiple still images from a smartphone or
other digital camera to build 3D models. Snavely et al. (2008) and with a US$10 monthly fee). Karabinos (2013) used it to create
Enqvist et al. (2011) developed non-sequential SfM, enabling
model construction from image searches (Schonberger et al.,
2015). However, Sakai et al. (2011) require only two photographs,
and Gilardi et al. (2014) created 3D beach pebbles from a single
orthogonal photograph.
The bleeding edge of SfM technology is Autodesk® Memento
(2016), which at the time of this writing was in public beta-test
phase. It was slated for commercial release in May 2016 under the
new name Autodesk® ReMake. It promises to accommodate
billions of vertices with no limit on the number or resolution of
images. Such models will doubtless be too large to embed directly
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into Google Earth or Cesium virtual globes unless they evolve in
tandem, but will be accessible from virtual field trip stops via
HTML hyperlinks to modern browsers (Gemmell, 2015), of which
the fastest appears to be Waterfox (2016).
VisualSFM (Wu, 2013) is an open-source application with
enhanced SfM editing capabilities; however, it requires
command-line competency and is not for the faint-of-heart.
PhotoScan from Agisoft (2016) is a more popular choice (Pitts et
al., 2014; Shackleton, 2015) and whilst not free, is deeply
discounted for education. Bemis et al. (2014) review other SfM
methodologies, including UAV outcrop mapping. Probably the
easiest SfM application for beginners, however, is Autodesk’s
123D Catch.
Schott (2012) modeled mud cracks using Autodesk’s original
SfM application, PhotoFly—since renamed 123D Catch—which is
freely available from Autodesk (2016; there is a premium version
outcrop and boulder models. De Paor (2013) described the process
of porting 123D Catch models to Google Earth by processing
them through MeshLab. Bourke (2015) used SfM to model an
indigenous Australian rock shelter; Lucieer et al. (2013) mapped
landslide displacement using SfM and UAV photography; and
MCG3D (2015) made particularly good use of annotation capa-
bilities in a geo-tourism application.
Figure 3 shows a mantle xenolith from Salt Lake (Āliamanu)
Crater, adjacent to Pearl Harbor, Hawaii. The verilith was
collected by Michael Bizimis, University of South Carolina, and
mailed to the author for SfM modeling. Because the most impor-
tant part of this specimen is the saw-cut surface, it was possible to