![]() The surface of levee’s can be dissected by crevasse channels, which operate only during floods and have a crucial role in delivering water and sediment between the channel and its surrounding landforms. Due to their position, they may provide the most critical controls on floodplains, determining the distribution of water and sediment. Among them, levees, located next to the active or abandoned channels, are the most elevated forms they can even be a couple of meters higher than the surrounding areas. Rivers, through erosion and accumulation processes generate various landforms in their floodplains. This methodology can be useful in geomorphologic mapping. Our results help to understand classification results and the specific limits of laser scanned DTMs. However, CP and SU were not efficient measures of classification accuracy as they were not in accordance with the class level accuracy metric. RFE helped to identify the most important 13–20 variables, maintaining the high model performance and reducing the overfitting. We found that the object-based method had a better performance (95%) than the pixel-based method (78%). We also evaluated the classification probabilities (CP), the spatial uncertainties (SU), and the overfitting in the function of the number of the variables. Random Forest classification was conducted with Recursive Feature Elimination (RFE) on the objects (mean pixel values by forms) and on the pixels of the variables. We derived 60 geomorphometric variables from the DTM and prepared a geomorphological map of 265 forms (crevasse channels, point bars, swales, levees). We performed a classification of floodplain forms in a naturally developed area in Hungary using a Digital Terrain Model (DTM) of aerial laser scanning. A better understanding of their geomorphological characteristic helps to understand the main processes involved. ![]() Floodplains are valuable scenes of water management and nature conservation. ![]()
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