Simulator GIS – Darb Dabney’s OpenSim

Blemishes notwithstanding, nearly six months of back-burner work has reached a threshold of readiness and is outward bound to some engineering firms, flood mappers at FEMA, and interested parties within the county. A handful of known issues remain unresolved. Proper name is “tbsm45cm_20100823″, proper edition is “2010.08″.

This is the third version of the terrain. Second version was “2010.01″ and included multiple LiDAR data sets, but fewer than presently used, and was a topographic model only. First version was “2009.09″ and was mainly photogrammetry and FEMA LiDAR, and was the last version to be developed in California Coordinates. Once the massive NCALM LiDAR data sets were processed, it became easier to move everything into WGS84 UTM zone 10 north meters projection, WGS84 NAVD88 CONTUS Geoid 2003 vertical position.

The NOAA utility program VDatum, a brilliant Java-based application able to stream-process data sets of near-infinite size, brought the NCALM data to heel, and opened up decades of NOAA depth surveys to our use in integrated topographic-bathymetric surface modeling.

First-return NOAA ALACE LiDAR swaths were fused along the outer coast, as bare-earth filtered versions were not produced in 1997–2002; the benefits of LiDAR detail along the rocky coast do seem to outweigh the distracting appearance of structures near Rodeo Lagoon, Stinson Beach, and outboard Bolinas.

When ArcGIS 9.4 beta 2 reached its limit in ability to render the terrain dataset into 45cm grid over the full extent, the clipping quadrants created to resolve this problem ended up chopping a very small portion of Sonoma county that drains into Estero Americano; the full watershed remains intact in the 1-meter version of the terrain grid under analysis for county-wide hydrology. Likewise, the tighter clipping quadrants lost a few hundred meters of San Pablo Bay bathymetry just west of where Marin, Sonoma, Contra Costa, and Solano counties meet. Also, tighter clipping quadrants snipped a portion of the San Francisco Bar southerly of San Francisco’s Seal Rock that was intended to be part of the model. All of these areas exist in the 100cm grid, and will be part of drainage analysis.

Happily, we have updated the workstation to ArcGIS 10, and have been enjoying such great speed gains with Spatial Analyst that our ERDAS use has been noticably reduced. Finally, Spatial Analyst is often showing performance nearly on par with ERDAS. Thank goodness that the Raster Calculator survived the transition to version 10 ArcGIS!

Painfully, the existence of unutilized bathymetric data sets for upper broad-channel Corte Madera Creek and Bolinas Lagoon have been revealed this week. Hey, there’s already something to look forward to for the next build!

The new terrain is getting some immediate use in support of an effort to participate in ESRI’s Community Maps Program for large-scale topographic mapping. The Program provides a template geodatabase with 36 vector feature classes and two raster, into which local agencies may pour their data. Once tucked into a conforming schema, a template multi-scale map document is provided with 120 layers—30 at each of four large scales that correspond to Google Maps and Bing Maps projection and cache tiling schema. The difference is that the template document makes use of ESRI tools to allow much more local detail to be packed into a map designed with notably more sophisticated cartography than either Google or Bing maps now have. The Community Maps Program concept is that local agencies may publish their local detailed content in a fairly uniform style, while retaining a world-wide seamless context for their surrounding area.

Qualitatively, the effect is that, when viewing the ArcGIS.com topo map alongside either Google or Bing maps (on two monitors, with comparison made at the same scale), the ArcGIS.com map looks to be a larger scale. It isn’t, and I’ve measured the size of features to convince myself, but my mind insists that I’m zoomed farther in on the ArcGIS.com map for some reason. My guess is that it is a perceptual effect of the much greater amount of information that is cleanly displayed in the ArcGIS.com map versus the much sparser Google and Bing content at these large zoom levels. Try it out—it’s like a carto version of an optical illusion!

The 120 layers in the template large-scale topographic base map from the ESRI Community Maps Program are arranged to provide four precise cartographic designs for Google/Bing map cache levels 16 through 19, which correspond to these display scales
1:15000–1:6001 (level 16, a.k.a. ~9k)
1:6000–1:3501 (level 17, a.k.a. ~4.5k)
1:3000–1:1501 (level 18, a.k.a. ~2k)
1:1500–1:501 (level 19, a.k.a. ~1k)
One of the most attractive areas currently online is Toronto, ON where at levels 18 and 19, individual building outlines are graced with street addresses.

Anyhow, the new tbsm45cm model will serve County of Marin’s effort at large-scale topographic mapping several ways. First, it has made possible a very detailed hillshade that helps emphasize the grading around each hillside structure in the county. Second, it helps us to create the required metric topographic contours. These are necessary to meet world-wide mapping standards, and throughout this weekend, contours are being generated from a related (smoothed version) of the terrain on 50cm vertical interval. Needless to say, most of these won’t get used in the map renderings, but the ESRI cartographers have shared a very clever indexing scheme that will help us use this single set of metric contours to support the requirements for all four of our topographic map scales.

I don’t have much to say about these regions that hasn’t been written already, and my views have been less aesthetic than Shenlei’s.
But in the interest of boosting the bandwidth by which I can share OpenSim, I’ve invested in a much newer Adobe Premiere Elements than I’d been using for the past five or so years. It’s a gas to have it multi-thread while rendering, and I have direct-to-FLV write. Trying to share as much of the motion and fidelity via YouTube as I possibly can, I’ve crafted a video resolution that is a multiple of my Hippo / SL viewer screen. The FRAPS video direct to AVI (sorry, it’s Win XP) is 1600 x 1140 @ 10 fps. Yup, those are video frames. In the interest of surviving an upload, I’ve rendered them highly time-compressed, with output at 1515 x 1080 @ 15 fps. As of tonight there’s no sound, no intertitles, just the rushes.
oops, if I read the YouTube Instructions for best formats, I should have trimmed the width to 1440, which is a multiple of 16.
Also, I have more direct upload options now with Premiere 8 than I had with my (recently demised) copy Premiere 1.0. Go Figure ;^)
While the Windows box grinds out the video print, I’m over here on Ubuntu blogging in a tab of 64-bit Chrome 4.0.249.43 and it is fine & fast.

For these videos, I visited ScienceSim Geography22_44 region and set the view to wide angle, then sat up at about 500 meters and watched the regions rez their terrain. For some folks, it will rank right up there with watching lead-based paint dry. For geography folks I’m hoping that these few minutes of sped-up video will convey, by dogged repetition, the primacy of regions in the provision of virtual environment simulators.

By the way, I’ve got a task: I need to find a better buzz word for the GIS community. I’ve been advised by some serious and well-intentioned (not to mention well-informed) folk that terms like “virtual” and “immersive” are actually boring to GIS’ers. So I’ll need to think about how to convey the concepts of “Mirror World”, “Multiuser Virtual Environment”, “Immersive Connected Experience”, “Third-Person Virtual World”, and related concepts into a catchy moniker. Hopefully, one that is not presently trademarked, either!

I’m trying to remain serious about this, but some of the options are treacherous. Geography in Social Media has a possibly awkward acronym; maybe it can be saved in recognizable form as “GIS for Social Media” or “Geography for Social Media”: GFSM
The term “3D Map with Me” is terse, slightly ambiguous

Here is the video chopped as it was when uploaded with 1515 x 1080 resolution. Problem with that is that by not preserving dimensions at a multiple of 16, and saving my viewer’s aspect ratio rather than the (standard since 16mm film) 4:3 aspect, my upload is clobbered into something perhaps suitable for a smartphone. So please consider this the Smartphone Version of last night’s rushes:

Then, once again with feeling, or at least with a little more rest, there is what I hope to be an HD-friendly moving vision of OpenSim, as it appears on the ScienceSim Geography regions. Yes! After it ripened on the YouTube servers for a few hours, I now see all the higher-res versions available. At 1440 x 1080, this is pretty close to what I see on my screen with a live Hippo viewer.

And after a day’s cogitation: anyone care to comment on the term: “Social Immersive Media GIS” as a moniker? Oops — I used “immersive” 8^(

updated 2009 05 26

I’ve been waiting for some property boundary issues to resolve in SL, and it’s sort of pitiful to see how long that can take.  It’s with ever more regret that I find myself on the Mainland.  But that hasn’t kept lots of real-world interesting stuff from taking shape.

The following video is not new.  In fact it’s about a year old, but somehow I hadn’t seen it until tonight and I found it somewhat encouraging. Thanks for O’Reilly and Where 2.0 for bringing these two on stage together!

And the following pean to Google Earth did inspire me, personally. Hey, I was reading road maps at 5, covered my wall completely with National Geographic maps at 10, learned to navigate with nautical charts at 12, read aeronautical charts and completed an urban planning project at 14. Sometimes, it’s fun in rare moments when it’s dark overcast and I’m in an exotic place for the first time and I don’t know the way north; more often, I’ll savor the feeling of knowing which way is north while dreaming.

Meanwhile, back at the lab, the global set of county terrain is being compiled into an ESRI Terrain Dataset. This will include over 360 million masspoints, merging both interpolated 2-foot interval contour vertices together with FEMA LiDAR mass points, plus break lines and waterlines from photogrammetry. The goal is to use the ESRI Terrain data as a format to stage everything together to produce 30cm grid interval DEM in the urban areas. With luck, we’ll have that ready about the time that the latest photo mosaic finally gets loaded into ArcSDE successfully. Maybe grids from the Terrain can help create very detailed 3D county models. Hey Wei – we still have inverted terrain in Google Earth at the quarry on San Pedro Point! ;^)