2007 Digital Elevation Contours
In 2007, NCTCOG contracted with Bohannan Huston to develop a terrain surface along with contours for 17 North Texas counties. The technology used to develop the terrain surface is called Auto-Correlated Surface (ACS). ACS is a “single return” technology, as opposed to LIDAR which can have multiple returns for one location and the resulting data may not be as accurate as LiDAR, especially in heavily vegetated areas. The 2007 contours are available at 2” resolution and are suitable for cartographic purposes.
Elevation contour products can be purchased through the DFWMaps Marketplace.
Stereo images were processed to automatically generated a digital elevation model. Any non-man made structures and vegetation were removed from the digital surface model. MicroStation design files containing ground elevations were clipped to eliminate overlap between stereomodels and filtered to declassify points that constituted excessively small elevation spikes.
|Altitude of Capture
||No higher than 5,500' above mean terrain
||January – March 2007
||Control panels were laid down and their positions recorded with static GPS. Positions were then corrected and network adjusted.
|DEM Point Spacing
|DEM Point Accuracy
||1.5 feet (horizontal)
||Texas State Plane, North Central Zone
||US Survey Feet
Source stereo images are collected at an elevation of no more than 5500 feet above ground. Theoretical design of the photogrammetric flight indicate a vertical accuracy will be achieved for an ASPRS vertical supporting 2.0' contour intervals. Contours have been generallized and smoothed which may slightly affect attributed elevation accuracy for the positional sample.
Aerotriangulation results for all raw imagery was checked for horizontal accuracy. Digital auto-correlated elevations correspond to the accuracy of the aerotriangulation. NSSDA validation indicates a vertical RMSE of .54' yielding a 95% confidence of 1.06 feet vertical on the digital surface model from where the contours were generated. Subsequent contour generalizing and smoothing will affect the overall positional accuracy of the contours. For more information on the 2007 contours, check out the project level Metadata.
The North Central Texas Council of Governments (NCTCOG) coordinated the capture of a photogrammetric surface using auto-correlation photogrammetric analysis techniques. The contour data are intended to aid in engineering planning. They are not intended to furnish measurements accurate enough for engineering design work. The NCTCOG provides these geographic data "as is" and makes no guarantee or warranty concerning the accuracy of information contained in the geographic data. NCTCOG further makes no warranties, either expressed or implied, as to any other matter whatsoever, including, without limitation, the condition of the product, or its fitness for any particular purpose. The burden for determining fitness for use lies entirely with the user.
Although these data have been processed successfully on computers of Bohannan-Huston, Inc. (BHI) and served by NCTCOG, no warranty, expressed or implied, is made by NCTCOG or BHI regarding the use of these data on any other system, nor does the fact of distribution constitute or imply any such warranty. In no event shall NCTCOG or BHI have any liability whatsoever for payment of any consequential, incidental, indirect, special, or tort damages of any kind, including, but not limited to, any loss of profits arising out of use of or reliance on the geographic data or arising out of the delivery, installation, operation, or support by NCTCOG.
Known issues with the 2007 surface and contour datasets:
- Where there are large areas of dense ground vegetation or tree canopy the density of verifiable ground control decreases which in turn decreases the accuracy of the surface and contour data in those areas. These areas can potentially be identified by long straight or more generalized contours.
- To create a cartographically pleasing contour the lines have been smoothed slightly. This smoothing has a small impact on accuracy but creates a much easier to use contour dataset.