Evaluation of different DEMs for gully erosion susceptibility mapping using in-situ field measurement and validation

The spatial variability in any kind of geomorphic studies based on terrain attributes are the most important issues. This terrain attributes and their respective characteristics play a significant role in the formation and expansion of ephemeral gullies. Therefore, nowadays, the accuracy of terrain based geomorphic studies has been mostly dependent on the resolution and quality of the DEM (digital elevation model) data. As the rate of erosional power of water flow is dependent on the terrain characteristics, therefore the extraction of several terrain features from DEM data is necessary in the study of gully erosion. This case study investigates the scaledependence of DEM-derived terrain factors in gully erosion susceptibility (GES). This work on Garhbeta-I C.D. Block has focused on the comparison among the predicted GES maps through five types of DEM i.e. Shuttle Radar Topography Mission (SRTM), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Cartosat-1, ALOS World 3D-30 m (AW3D30) and Advanced Land Observation satellite (ALOS) coupled with the machine learning modelling approach of artificial neural network (ANN), convolution neural network (CNN) and deep learning neural network (DLNN) algorithm. A total of sixteen conditioning factors were chosen for GES assessment based on the topographical, hydro-climatological conditions and multi-collinearity analysis. Here, importance variables are measured by mean decrease accuracy (MDA) method of random forest (RF) algorithm and the result is shown that elevation is the most important factor for gully occurrences. Validation result of receiver operating characteristics-area under curve (ROC-AUC) has been indicates that DLNN model in ALOS DEM (AUC = 0.958) gives the most optimal accuracy in GES assessment. The output maps can assist in identifying gully-prone risk areas, and several suitable with sustainable managements should be taken for conservation accordingly.