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Abstract:
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Nowadays, digital terrain models (DTM) are an important source of spatial data for
various applications in many scientific disciplines. Therefore, special attention is given to their
main characteristic ‐ accuracy. At it is well known, the source data for DTM creation contributes a
large amount of errors, including gross errors, to the final product. At present, the most effective
method for detecting gross errors in DTM source data is to make a statistical analysis of surface
height variation in the area around an interested location. In this paper, the method has been tested
in two DTM projects with various parameters such as interpolation technique, size of neighboring
area, thresholds,... Based on the test results, the authors have made conclusions about the reliability
and effectiveness of the method for detecting gross errors in DTM source data. |