A data-independent method for quantitative accuracy assessment of morphological parameters extracted from grid-based DTM

This paper reports a research project on the methodology for quantitative and objective assessment on errors generated from grid-based hydrological modelling algorithms. Surfaces were defined using selected mathematical functions with different spatial resolutions. Because the theoretical values of surface morphological parameters on these mathematical surfaces are known through inference, they can be used as benchmarks that are independent from data structure and computer application algorithms. These mathematical surfaces were used to test selected terrain modelling algorithms, which can be found and implemented from literature. The actual output values from different algorithms were compared with the theoretical expectations so that the standard errors can be computed and their spatial distribution can be mapped. A preliminary test have shown that some existing algorithms that extract geomorphological and hydrological features from grid-based DTM failed to produce a reasonable result, indicating that these algorithms have some significant weakness and limitations due to their assumptions and data processing methods. While tested against the 'real world' DTM, these weakness were masked by the uncertainty of the accuracy of the source data and the fact that errors may be subtracted in the 'real world' DTM. While tested against the mathematical surfaces, on the other hand, the errors generated by the algorithms would be accumulated and propagated. Thus, the test has proven to be sensitive to algorithm errors and it can provide a quantitative and objective assessment on the correctness and accuracy of the computer algorithms for surface morphological parameter extraction.