DM4DEM: A GRASS-compatible tool for blunder detection of DEM

Gonzalo Durañona (gonzalod@interware.org) and Carlos López (carlos.lopez@ieee.org) (*)
Centro de Cálculo, Facultad de Ingeniería
Montevideo, URUGUAY



Present day GIS are complex pieces of software devoted to manipulate, analyze, store and report results about geographic data. However, there is a substantial lack of standard, readily available tools to critically analyze the input data itself, in order to detect or highlight suspicious values. This complain about present day software is highly complementary with the one raised about uncertainty of data, but is not the same. We here attempt to (see references) improve the accuracy of the dataset by using judiciously the supplied algorithms, which might help in reducing the uncertainty to some extent. DM4DEM (which stands for Data Mining for Digital Elevation Models) is an application for Graphical Information System which can do quality control of raster data in general, and in particular of DEM. Its interface allows the user to locate unlikely values of the elevation of the digital set using different criteria or algorithms even provided by the end user, and later edit them within the same environment.
The blunder (or oultlier) detection algorithms shipped with the software does not assume any particular source for the DEM (i.e. contour lines, photogrammetric pairs, direct survey, etc.) which makes it very suitable for end users, which might receive the data just “as is” without metadata about its lineage.
The usefulness of the software is illustrated with some example data taken from the literature. To the author´s knowledge, this is the first implementation of this feature in a popular GIS package.

The software has the following functions:

 This product was created to be executed either from the GRASS shell or the TclTk-Grass bar. Making use of graphical interfaces, the DM4DEM system follows the same styles of the applications TclTkGrass, so the user can work on a familiar environment.
Moreover, using the GRASS philosophy, the system follows the same programming styles that allow the product to be used cross-platform. It can be installed on different architectures, giving it more portability for his massive distribution. His development was done almost all by Linux, and was tested on an AIX Unix system. The system allows keeping information of the different projects the user works on, integrated with Grass tools, for the visualization, storage and manipulation of results from the algorithms.
There is also the possibility of modify the elevations by automatic algorithms (already supplied or not) or by manual estimation.
The product will be available on the WEB soon, both in source and compiled form for the abovementioned operating systems.

Keywords: blunders, DEM, outliers, automatic detection, accuracy improvement, GIS, GRASS

Selected references:
López, C., 1997. Locating some types of random errors in Digital Terrain Models. International Journal of Geographic
            Information Science, 11, 7, 677-698.
López, C. 2000. On the improving of elevation accuracy of Digital Elevation Models: a comparison of some error detection
            procedures  To appear in Transaction on GIS, 4,1.
Felicísimo, A., 1994, Parametric statistical method for error detection in digital elevation models. ISPRS J. of Photogrammetry
            and Remote Sensing, 49, 4, 29-33.

(*) To whom correspondence should be directed


Presented at:

        4th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences
        July 12-14, 2000
        De Rode Hoed, Amsterdam, The Netherlands


Full size paper for download!