Failure Prediction in Automatically Generated Digital Elevation Models
25 July 1999
Michael Gooch and Jim Chandler
Developments in digital photogrammetry have provided the ability to automatically generate Digital Elevation Models (DEMs) and is increasingly used by geoscientists (Chandler, 1999). Using overlapping imagery, dense grids of coordinates can be collected at high speeds (150 points per second) with a high level of accuracy. The trend towards using PC based hardware, the widespread use of Geographical Information Systems and the forthcoming availability of high resolution satellite imagery over the internet at ever lower costs, means that the use of automated digital photogrammetry for elevation modeling is likely to become more widespread. Automation can reduce the need for an in-depth knowledge of the subject thus rendering the technology an option for more users.
One criticism of the trend towards the automated black box approach is the common lack of quality control procedures within the software (Cooper 1998), particularly to identify areas of the DEM of low accuracy. The traditional method for accuracy assessment is through the use of check point data (data collected by an independent means of a higher level of accuracy against which the DEM can be compared). However, check point data is rarely available and the user is recommended to manually check and edit the data using stereo viewing methods, a potentially lengthy process which can negate the obvious speed advantages brought about by automation.
Research carried out at Loughborough sought to optimise the accuracies of automatically generated DEMs and focused upon the ERDAS Imagine OrthoMAX digital photogrammetric system(Gooch et al
, in press). This software uses an area correlation based algorithm over which the user has a certain amount of control through the use of a set of strategy parameters (Gooch and Chandler, 1998). These control the acceptance and quality control requirements for the derived data and early research work assessed the effect of altering these parameters on the resulting accuracy of the DEMs.
This work allowed a software data processing model to be developed that is capable of identifying areas where elevations are unreliable and which the user should pay attention to when editing and checking the data. The software model developed will be explained and described in detail in the presentation. Results from tests on different scales of imagery, different types of imagery and other software packages will also be presented to demonstrate the efficacy and significantly the generality of the technique with other digital photgrammetric software systems.
IV International Conference on GeoComputation, Mary Washington College, Fredericksburg, VA, USA, 25-28 July 1999.