Mar 14 2011

Shaken Awake – and new terrain product

The enormously tragic megathrust event east of Honshu island in Japan has been in my thoughts throughout the weekend.   It is natural to focus on the human loss and images of civic destruction; I’ve got little to add to that story.

When I saw the first news items, it was already Friday morning and eight hours past the event.  My concerns were for Hawaii and the arrival of a tsunami.  I was shocked by the energy released, as reported at NEIC:  Mo=3.9×10^22 Nm,  Mw=9.0 — for as many earthquakes as have been recorded and studied in Japan, this was a much larger event.  For disaster planning, that is Not A Good Thing.

Moment Tensor USGS/WPHASE  Mo=3.9x10^22 Nm

The beach ball diagram shows compression back up the thrust. Depth of event is 24km

While there was some concern for Hawaii, there is something to be said for the diffraction caused by the long line of seamounts extending northwesterly from the big island.  While the energy won’t be cancelled out, the height of the crest would be widened some.  By the time the tsunami reached California, it was a real concern and a literal wake-up call for emergency workers.  Our damage here was mostly an economic annoyance, with Del Norte county once again taking the brunt of the damage in Crescent City harbor.

With a check-in call to relatives in Hawaii saying everything OK, their eyes and mine turned towards Japan.  As I watched shocking videos of tsunami damage, I struggled to calibrate what I was seeing with my mental model of how fragile most human habitation structures are.  I’ve thought much about the effects of shaking, liquefaction, and occasionally about wildland fire.  I’ve read about losses in Marin county during 1982 flooding where debris flows destroyed houses or literally rolled them end-over-end down a slope.  I’d seen some videos from near Sumatra of debris flowing up streets after waves climbed up the beach.  Yet images from Japan recorded damage unfolding at an entirely worse scale.

My concern became much more engaged when I saw helicopter video of the south end of nuclear power reactor facility Fukushima Daiichi (No. 1).  You see, in the video clip I recognized not the reactor, but the cut slope behind it.  In a very strange sense of model-based deja vu, my memories were unequivocal: “I know that place!”.

Why?  Because about 17 or 18 years ago, I was fortunate to be part of a site design project for the (still yet to be constructed) Unit 7 and Unit 8 reactors.  Fortunate for me, because it was a first opportunity to learn not just ESRI Arc/INFO, but how to work with Bentley CAD software to create a 3D cut slope design.  My small contribution was to create a realization of slope that was  not simply faceted as a buffer surrounding the building footprints, but instead create a semblance of the natural cliff slopes  adjacent to the plant, while meeting the engineering requirements for not-to-exceed slope steepness, and a more natural-looking accumulation of drainage from the slope.

So apparently, after spending a couple of weeks learning to use 3D design software and creating a design that extended the existing cut farther southward, I had an image of the plant, its cliffs, and the breakwater that guided cooling water that stuck with me.  After having the flash of recognition with the video, I opened up Google Maps and found the site on my first inward zoom.  It was a bit spooky.

So now when I watch coverage of hydrogen venting that leads to building explosions, I feel a curious terrain-based sense of connection with the site.  I wish them well, and the safest possible return to production.  The TEPCO power is needed by many people.

And more ominous for the Pacific Northwest, I can’t help but reflect on what a similar megathrust event would mean for Cascadia.  Both Portland and Seattle would be in some sort of peril, although I don’t have a clear understanding of how tsunamis are modeled for either lower Columbia River or for Puget Sound.  But the possibility of a 9.0 megathrust event along the Cascadia subduction zone was a whole lot more abstract for me until last Friday.  It may not be the best time to reflect on it now while Japan is suffering—but the risk to the northwest has been a matter of public record for several years now and it not the time to forget that, either.  An event of that size and location would have tsunami implications both locally, and perhaps a far greater risk for windward Hawaii.


Closer to home,  this past week we’ve created a prototype 3D product that provides a facsimile of our 45cm terrain model—imported to Google SketchUp 8 with a georeferenced orthophoto texture on the terrain.  Things are not fully tuned up yet, but we are able to take TIN and decimated TIN surfaces out of ArcGIS 10, by way of clipping polygons that are interpolated to multipatch (3D multi-polygon features) and then exported to Collada with a KML point for georeference.  The Collada can be imported to SketchUp, at least up so some limit of detail.  Once there, I’m trying now to find the right way to smooth the facets and improve the rendering of the surface without having high-contrast dark facets—because the orthophoto textures are arriving intact and draping over the surface.  Only at the moment, many black facets are covering up almost half of the orthophoto in an aggravating triangular patchwork.

Next step: smoothing within SketchUp.

And inspiration from others who have gotten gridded terrain into SketchUp.

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Mar 12 2010

Sharing Terrain With the World – Google Earth style

It’s not fully 3D immersive, but hey, 2-1/2D ain’t half bad. The “dsm40cm” model of Marin County has been published as the county’s default terrain on Google Earth. It’s a great pleasure to work with folks who are not troubled by a county representing its surface on a 40cm single-precision float grid that weighs in at 77 GB. In terms of data bulk, that is about the same as the entire 30-meter version of the US National Elevation Dataset.

What one gets when piling that much detail into a single county of around 520 square miles of land area is every building pad, driveway, and crown of road paving that were resolved. The dsm40cm model was derived from an ESRI Terrain Dataset that incorporates our best available topographic contours (1:4800 scale 10-foot; 1:2400 scale 2-foot,) photogrammetric break and water lines, FEMA LiDAR and NCALM (GeoEarthScope) LiDAR data sets. The Terrain Dataset currently comprises 40 GB of vector GIS data.

When the finely detailed surface grids were first developed, we broke the county up into 20 work areas to maintain ArcGIS 9.3.1 in a stable and productive state, and 30cm posting interval grids were generated that covered the entire county–at least during development. When necessary, these grid tiles were mosaicked with ERDAS Imagine into a single seamless grid. The 40cm version was produced directly as a single seamless grid using ArcGIS 9.4 beta 1, on a workstation imaged with Windows Server 2003. The WGS84 UTM, NAVD88-Geoid 2003 result was provided to the Google Earth team earlier this year.

As with all GIS data sets, it seems, the more detailed it is, the more rapidly it may need updating. In the works for the next year or so are several improvements to the dsm40cm model. First: the photogrammetric break lines will be segregated into steeper sets that tend to run along ridges, and shallower slopes that tend to delineate road cuts and building pads. The ridge set will be used as soft constraints to resolve some artifacts where they rise above some contours.
Second: incorporate new LiDAR data as it becomes available. Some data has already been provided for the lowest part of Lagunitas creek, and it appears that Prof. Ellen Hines of San Francisco State University’s Department of Geography and Human Environmental Studies has been funded by USGS to gather LiDAR county-wide this year.

So there will be revisions, but an exciting aspect is to see data flows being brought into existence that support different levels of mirror world development.
Publishing the dsm40cm model in Google Earth is an important (and beautiful) threshold to cross. Making use of the dsm40cm model in county operations such as creek and watershed delineation will be the practical benefit that drives the work in the first place. And before too many more weeks, there may be entirely new approaches to publishing the data in an immersive environment (neither Second Life nor Opensim) to share.

Building pad in Kent Woodlands shows driveway-level detail

Kent Woodlands building pad and driveway, in the shadow of Mt. Tam

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Apr 22 2009

Something new for Earth Day

<<updated 20090424>>

As my patience with Second Life wanes, and I wait for more architectural input for my next SL build project, I have a dark OpenSim server with no fixed IP.  I’m having stability issues with the Linux SL client, but have upgraded the workstation to Ubuntu 9.04 Jaunty Jackalope.  Google Earth client there is more stable, the NVidia drivers install themselves (sans Envy), and everything Ubuntu-wise seems to be getting incrementally better by the quarter.

I’m grinding some large images that have taught me that one very special difference between Windows XP variants and Windows Server 2003 is the latter’s ability to open files on the high side of 80 GB.  I’d never quite realized it before but the moderately massive mosaics that I have created in years past (edging toward 250 GB single files) actually depended on Server 2003 to get created.  Once the destination file exists, then XP can take it from there, and in all cases Windows Explorer can copy the monster files.  But in that tenuous moment when a mosaic first grabs its space on disk for a huge output—one can’t seem to do that with XP.

So while I’m enjoying Google Earth on Ubuntu, there is something cool that I go back to Windows for, and that’s the new Google Earth browser plug-in.  Since I’m gaining a bit of facility with the keyboard shortcuts in the full-stop Earth client, these all carry over to the plugin.  My first test page has been stood up here and I’ve been deep into four continents with it so far.  I understand that the plugin is only available for Windows and Mac systems at this time.  If you can,  Enjoy! 

Also, as I get even faster with my keyboard navigation of G-Earth, I’ve actually seen some artifacts that are quite familiar from OpenSim.  While zipping about between the Gulf of Yakutat and Canada’s Mount Logan, at certain viewing elevations I can accelerate the point of view forward quite fast.  Doing so in this very mountainous terrain, I saw blocks of terrain standing up along what look like sim edges, resolving in a few seconds as more (sculpty?) bumpmap arrives.  This is the same sort of artifact I’ve seen with terrain sculpties and sometimes, with region crossings in OpenSim.  Also, I’ve found a couple of wild terrain grid errors in G-Earth.  In one, a quarry dug hundreds of feet below sea level, right next to the sea, is displayed as positive elevation (absolute-value terrain, anyone?).  In another, a boundary between US and Canadian terrain has a glacier flowing uphill onto a plateau.  Go figure.  Blame Canada! ;^)

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Apr 02 2008

Terrain Sculpties – OpenSim does Google Earth

Published by under OpenSim

The past four days have been a tremendous blur of internalizing NURBS into my mind, at least the SL sculptie variant of them. Now I’ve been aware for several months of how NASA used sculpted prims to represent detailed Mars craters (as published by Ireton), and I’ve certainly followed the beautiful work for David Rumsey done both by Telemorphic in 2003 (3D plots of historic Lake Tahoe area) and more recent historic Yosemite by Nathan Babcock). But there was something confusing and ultimately mysterious about using sculpties for terrain.

Not so much any more. Through several helpful blog and forum posts, and a score of hours spent in experimentation, I feel that I’ve brought the sculptie to heel for my terrain rendering purposes. Mostly, especially for OpenSim, it’s simply to display draped orthoimagery over an already precisely customized region terrain.

What I’ve learned is that for 1:1 mapping, where regional terrain is not available at more detail than the 10-meter postings from, then one can configure precise sculpted megaprims, only four to a region, and drape imagery quite effectively. The result is real-life imagery draped in the style of Google Earth, but coming out of a free OpenSim server into a free Second Life client, for a dozen or more regions on one server core. When using the technique that I’ve worked out, having only four scuplties to seamlessly cover the region means that the terrain sculpties will rez fully sixteen times (16X) faster than will either the David Rumsey or NASA educational islands.

There’s no special magic here: the region terrain is far superior as a way to represent real life terrain, as it can hold 64K of single-precision floating point values. A sculptie, by comparision, holds a mere 900 usable values that must be compressed to an 8-bit signed integer, for any one of the 900 points’ X, Y, or Z values that are practical to use to guide facets in a terrain “diamond”. This “diamond” is a way of describing what the terrain sculptie looks like after defining the outermost ring of UV values to wrap around to a single point safely below terrain surface, so as not to interfere with the 30×30 values useful to describe terrain in a way that cleanly tiles to cover multiple regions. The vertical scale of the terrain described this way is adjusted with the Z-dimension of the sculptie spheroid, which must be tuned using back-end OpenSim command “edit-scale” if one is manipulating a megaprim.

Anyway, when I get a chance to demo this for some Berkeley terrain, I’ll be sure to post a dramatic screen shot. As it is, the 12-region sim looks so realistic right now that almost any shot would be immediately recognizable by someone familiar with the site, so the good ones will wait for project time. Meanwhile, this one is intended to prove validity of sculpted terrain megaprims for draping orthoimagery.

Watch Out Google Earth

The tools that I used were: ArcGIS to reproject the seamless terrain and orthoimagery into a rotated local grid variation of WGS84-UTM; ERDAS Imagine to perform mosaicking, dicing, image stretch/rescaling, and layer stacking to build precise UV maps from real life terrain; and spreadsheet to calculate precise gradient values for the X and Y components of the UV maps. On the back end was OpenSim 0.5 using region definitions in the 0.4 style, and the terrain build was performed using the standard Second Life 1.19.0.(5) client running on Windows XP with a Radeon X1300 Pro.

A couple of days later, I revisited the sim and made a couple of updates to sculpties with the new 1.19.1.(4) Second Life client, and the orthoimage colors look different depending on sun angle–thanks to Windlight.  It’s not a bad thing, and gives one a reason to look up and appreciate the beautiful sky!   Back on Agni (standard Second Life Grid) by comparison, all the prims seem far more intensely colored and somehow more detailed with the new client.

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