Darb Dabney's 3d GIS – OpenSim

Many interesting projects have been happening, so many that projects have been backed up while workstations grind through their days-long work flows. This creates opportunities to update systems while we wait, and so the past week has seen massive updating of Windows system stuff and deleting old development tools so that the decks were cleared for MS SQL Server 2008 R2 Management Studio. With a bit of shape2sql from SharpGIS and today we’ve had our first spatial tables loaded and fledgling spatial SQL queries made.  Oh, at the end of the day we got the third of five workstations updated to ArcGIS Desktop 10 and the full complement of seats moved over to ArcGIS 10 licensing.

What’s been holding things up has been some final processing of cartographic-grade contours, one of the key new feature classes developed for support of the ESRI Community Maps Program, where local jurisdictions grind their own cache tiles for large-scale topographic mapping.  Since it’s part of a worldwide seamless map, of course the contours and spot elevations must be metric—which meant generating new contours.  The bathymetry was done on one-meter interval, with some half-meter supplemental contours in shallower waters.  The topography was done at quarter-meter intervals up through 25 meters elevation, where we’d included all available LiDAR data, the half-meter intervals through 50 meters, and one meter up to the summits.  All non-integer meter contours were flagged as supplemental, and contour index attributes were also calculated for 2, 5, 10, 20, and 50-meter intervals.   Spot elevations were derived from VARGIS photogrammetric spot elevations that were screened down from about 75,000 points to just 440 points, using neighborhood focal statistics.

For performance’s sake, after index attributes were calculated, the contours were chopped into segments not-to-exceed 500 meters shape length.  When all the chopped segments from all the various elevation ranges had been merged to a single polyline feature class in a feature dataset in a file geodatabase, spatial indices were built for the cache tile scales about 1:1200, 1:4800, and 1:19000.  The purpose is to make the contours as fast as possible not just for web app interaction, but for rendering the large-scale cache tiles.  In the end, the contours in this one feature class have about 1.4 million polyline features that fill the file geodatabase to about 6.8 GB of data.

Meanwhile, some great brainstorming has taken place with regard to hydro-enforcement of the terrain model, so that accurate synthetic flow lines can be generated county-wide.  Based on prototype work performed by Evan K. Babb before summertime, we knew how to deal with our terrain features and manually generate hydro-enforcement features.  Now, with a funded project to do the work county-wide, we’ve needed to devise a spatial analysis technique using the approach described by Poppenga and others in 2009.  Based on some correspondence and personal communication with Poppenga, we have sketched a workflow that should automate the creation of most simple (single road-crossing) hydrologic enforcement features, especially in the absence of accurate or complete spatial features for culverts.

So with the contours completed, it should be possible to have some progress made on automation of hydro-enforcement, completing more of the data development for large-scale topographic base mapping, help my colleagues continue the ArcGIS 10 migration, and follow up with some demonstration spatial SQL queries.  It’s an exciting couple of weeks!

There’s also been a thread of thought over the past six years or so that supports the workflow of using Visual Studio to compose SQL queries, in preference to the direct SSMS (SQL Server Management Studio, Tool Formerly Known As “Enterprise Manager”) ways of composing a query, because the typed pattern matching (MS: Intellisense) pulls up all the various ST__  spatial methods that are available in SQL Server 2008 spatial, but saves one needing to look-it-up and type-it-in correctly.  Such productivity gains really help boot up the learning experience a bit faster!