Expert-driven semi-automated geomorphological mapping for a mountainaous area using a laser DTM

n this paper a semi-automated method is presented to
recognize and spatially delineate geomorphological units in mountainous forested
ecosystems, using statistical information extracted from a 1-m resolution laser
digital elevation dataset.
The method was applied to a mountainous area in Austria. First, slope angle and
elevation characteristics were determined for each key geomorphological unit
occurring in the study area. Second, a map of slope classes, derived from the laser
DTM was used in an expert-driven multilevel object-oriented approach. The resulting
classes represent units corresponding to landforms and processes commonly
recognized in mountain areas: Fluvial terrace, Alluvial Fan, Slope with mass
movement, Talus slope, Rock cliff, Glacial landform, Shallow incised channel and
Deep incised channel. The classification result was compared with a validation
dataset of geomorphological units derived from an analogue geomorphological map.
For the above mentioned classes the percentages of correctly classified grid cells
are 69%, 79%, 50%, 64%, 32%, 61%, 23% and 70%, respectively. The lower values of
32% and 23% are mainly related to inaccurate mapping of rock cliffs and shallow
incised channels in the analogue geomorphological map. The accuracy increased to
76% and 54% respectively if a buffer is applied to these specific units. It is concluded
that high-resolution topographical data derived from laser DTMs are useful for the
extraction of geomorphological units in mountain areas.