TY  - JOUR
A1  - Maerker, Michael
A1  - Pelacani, Samanta
A1  - Schroeder, Boris
T1  - A functional entity approach to predict soil erosion processes in a small Plio-Pleistocene Mediterranean catchment in Northern Chianti, Italy
JF  - Geomorphology : an international journal on pure and applied geomorphology
N2  - In this paper we evaluate different methods to predict soil erosion processes. We derived different layers of predictor variables for the study area in the Northern Chianti, Italy, describing the soil-lithologic complex, land use, and topographic characteristics. For a subcatchment of the Orme River, we mapped erosion processes by interpreting aerial photographs and field observations. These were classified as erosional response units (ERU), i.e. spatial areas of homogeneous erosion processes. The ERU were used as the response variable in the soil erosion modelling process. We applied two models i) bootstrap aggregation (Random Forest: RF), and ii) stochastic gradient boosting (TreeNet: TN) to predict the potential spatial distribution of erosion processes for the entire Orme River catchment. The models are statistically evaluated using training data and a set of performance parameters such as the area under the receiver operating characteristic curve (AUC), Cohen's Kappa, and pseudo R2. Variable importance and response curves provide further insight into controlling factors of erosion. Both models provided good performance in terms of classification and calibration; however, TN outperformed RF. Similar classes such as active and inactive landslides can be discriminated and well interpreted by considering response curves and relative variable importance. The spatial distribution of the predicted erosion susceptibilities generally follows topographic constraints and is similar for both models. Hence, the model-based delineation of ERU on the basis of soil and terrain information is a valuable tool in geomorphology; it provides insights into factors controlling erosion processes and may allow the extrapolation and prediction of erosion processes in unsurveyed areas.
KW  - Erosion processes
KW  - Boostrap aggregation
KW  - Stochastic gradient boosting
KW  - Spatially explicit prediction
KW  - Tuscany
KW  - Italy
Y1  - 2011
U6  - https://doi.org/10.1016/j.geomorph.2010.10.022
SN  - 0169-555X
VL  - 125
IS  - 4
SP  - 530
EP  - 540
PB  - Elsevier
CY  - Amsterdam
ER  -