Esolution, in the TanDEM-X satellite platform (provided by Deutsches Zentrum f Luft und Raumfahrt (DLR)) to derive the topographic indices [13] with SAGA GIS 7.9 [70]. The DEM was preprocessed as a way to determine and fill the surfaceISPRS Int. J. Geo-Inf. 2021, 10,6 ofIn this study, morphometric analysis was performed on a high-resolution DEM having a 12-m cell size resolution, in the TanDEM-X satellite platform (offered by Deutsches Zentrum f Luft und Raumfahrt (DLR)) to derive the topographic indices [13] with SAGA GIS 7.9 [70]. The DEM was preprocessed so that you can identify and fill the surface depressions applying the SAGA GIS tool “Fill Sinks” [71]. In total, as shown in Table 1, 18 factors that impact gully erosion had been derived from an comprehensive literature critique [7,9,30,55,56,72,73] consisting of six basic morphometric parameters (slope, aspect, strategy curvature, Profile curvature and catchment area, at the same time as catchment slope). In addition, we applied the Topographic Position Index (TPI), which compares the elevation of each and every cell with the DEM to the mean elevation of a specified neighborhood around that cell [74], at the same time N-Desmethyl Bedaquiline-d6 Autophagy because the Vector Ruggedness Measure (VRM), which measures the roughness with the terrain surface [75]. Two other parameters depending on the slope and distinct catchment region were calculated: the Stream Power Index (SPI), describing linear soil erosion potential [76], as well as the Slope Length Aspect (LS-factor), exactly where the L-factor defines the accumulation of water along with the S-factor that represent the slope steepness [77]. Right here we make use of the 3D version of the LSFactor, the Transport Capacity Index (TCI), substituting the slope length with all the specific catchment location. Additionally, the parameters for solar radiation, for example direct insolation and diffuse insolation, have been calculated [78], along with the valley depth and Vertical Distance to Channel Network (VDCN) had been also derived [70]. Two additional environmental parameters are represented by the lithology, with 8 lithotypes derived in the 1:250,000 geological map [37], along with the 2014 land cover classification data derived from the BGIS.SANBI.ORG web page (http://bgis.sanbi.org/Projects/Detail/44, accessed on 9 October 2021). The Normalized Vegetation Index (NDVI) was calculated utilizing the QGIS SCP plugin-in to get a Sentinel-2 image from 23 June 2019. The NDVI yielded facts on the N-Desmethyl Azelastine-d4-1 custom synthesis distribution with the vegetation within the region. Ultimately, the erosion types have been transformed into a grid having a 12-m cell size, plus the respective centroids have been converted into a point dataset. In total, 17,065 points were identified. For each and every point, the values from the parameters described above were assigned.Table 1. Environmental predictors for maximum entropy modeling. Kind Topographic indices Elevation Slope Aspect Profile curvature Strategy curvature TPI VRM Catchment slope Catchment region SPI LS-factor (TCI) Direct insolation Diffuse insolation VDCN Valley depth Environmental information Lithology Land use Remote sensing data NDVI Variable Range 1051269 m a.s.l. 0-64 060 -0.04.05 -23.36.98 -33.396.54 0.43 02.4 14458,355,264 m2 0,591,456 -6.16-14.95 0.60 kWh/m-2 0.57.91 kWh/m-2 -275 m a.s.l. -6675 m a.s.l. eight classes 35 classes Reference [71] [79] [79] [79] [79] [74] [75] [80] [80] [76] [77] [78] [78] [70] [70] [37] [60] [81]-0.94.ISPRS Int. J. Geo-Inf. 2021, ten,7 of2.3. Modeling In this study, we applied a maximum entropy approach (“MaxEnt”) to assess the two gully erosion varieties and to assess the extent in the Quaternary deposits. Ma.