Corrigendum to “Assessing the performance of GIS- based machine learning models with different accuracy measures for determining susceptibility to gully erosion” [Sci. Total Environ. 664 (2019) 1117–1132]

Data Mining Technique (Maximum Entropy Model) for Mapping Gully Erosion Susceptibility in the Gorganrood Watershed, Iran

Soil erosion is a serious problem affecting most of the countries. This study was carried out in Gorganrood Watershed (Iran), which extends for 10,197 km2 and is severely affected by gully erosion. A gully headcut inven- tory map consisting of 307 gully headcut points was provided by Google Earth images, field surveys, and national reports. Gully conditioning factors including sig- nificant geo-environmental and morphometric variables were selected as predictors. Maximum entropy (ME) model was exploited to model gully susceptibility, whereas the area under the ROC curve (AUC) and draw- ing receiver operating characteristic (ROC) curves were employed to evaluate the performance of the model.…

Soil Science Challenges in a New Era: A Transdisciplinary Overview of Relevant Topics

Transdisciplinary approaches that provide holistic views are essential to properly understand soil processes and the importance of soil to society and will be crucial in the future to integrate distinct disciplines into soil studies. A myriad of challenges faces soil science at the beginning of the 2020s. The main aim of this overview is to assess past achievements and current challenges regarding soil threats such as ero-sion and soil contamination related to different United Nations sustainable development goals (SDGs) including (1) sustainable food production, (2) ensure healthy lives and reduce environmental risks (SDG3), (3) ensure water availability (SDG6), and (4) enhanced soil carbo…

Comparison of differences in resolution and sources of controlling factors for gully erosion susceptibility mapping

Abstract Gully erosion has been identified as an important soil degradation process and sediment source, especially in arid and semiarid areas. Thus, it is useful to identify the spatial occurrence of this form of water erosion in the landscape and the most vulnerable areas. In this study, we explored the effects of different pixel sizes on some controlling factors extracted from a digital elevation model and remote sensing data when producing a gully erosion susceptibility map (GESM) of Ekbatan Dam Basin, Hamadan, Iran. An inventory map of the gully landforms was prepared based on global positioning system routes of the gullies, extensive field surveys, and visual interpretations of satell…

Gully Erosion Susceptibility Mapping Using Multivariate Adaptive Regression Splines—Replications and Sample Size Scenarios

Soil erosion is a serious problem affecting numerous countries, especially, gully erosion. In the current research, GIS techniques and MARS (Multivariate Adaptive Regression Splines) algorithm were considered to evaluate gully erosion susceptibility mapping among others. The study was conducted in a specific section of the Gorganroud Watershed in Golestan Province (Northern Iran), covering 2142.64 km2 which is intensely influenced by gully erosion. First, Google Earth images, field surveys, and national reports were used to provide a gully-hedcut evaluation map consisting of 307 gully-hedcut points. Eighteen gully erosion conditioning factors including significant geoenvironmental and morph…

Erodibility prioritization of sub-watersheds using morphometric parameters analysis and its mapping: A comparison among TOPSIS, VIKOR, SAW, and CF multi-criteria decision making models

Soil erosion, every year imposes extensive damages to human beings by means of reducing soil productivity and filling reservoirs from sedimentation in Ghaemshahr Basin in Mazandaran Province, (Iran); therefore, identifying prone areas to soil erosion for preventive measures is essential in this basin. In this research, erodibility prioritization of sub-watersheds of Ghaemshahr Basin has done using morphometric parameters analysis and different multi-criteria decision making (MCDM) models such as simple additive weighing (SAW), VlseKriterijumska optimizacija I Kompromisno Resenje (VIKOR), technique for order preference by similarity to ideal solution (TOPSIS), and compound factor (CF). For t…

Evaluation of multi-hazard map produced using MaxEnt machine learning technique.

Abstract Natural hazards are diverse and uneven in time and space, therefore, understanding its complexity is key to save human lives and conserve natural ecosystems. Reducing the outputs obtained after each modelling analysis is key to present the results for stakeholders, land managers and policymakers. So, the main goal of this survey was to present a method to synthesize three natural hazards in one multi-hazard map and its evaluation for hazard management and land use planning. To test this methodology, we took as study area the Gorganrood Watershed, located in the Golestan Province (Iran). First, an inventory map of three different types of hazards including flood, landslides, and gul…

Assessing the performance of GIS- based machine learning models with different accuracy measures for determining susceptibility to gully erosion

Assessing the performance of GIS- based machine learning models withdifferent accuracy measures for determining susceptibility togully erosionYounes Garosia, Mohsen Sheklabadia,⁎, Christian Conoscentib, Hamid Reza Pourghasemic,d, Kristof Van Ooste,faFaculty of Agriculture, Department of Soil Science, Bu Ali Sina University, Ahmadi Roshan Avenue, 6517838695 Hamedan, IranbDepartment of Earth and Sea Sciences (DISTEM), University of Palermo, Via Archirafi22, 90123 Palermo, ItalycCollege of Marine Sciences and Engineering, Nanjing Normal University, Nanjing, 210023, ChinadDepartment of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, IraneA- Fo…

Performance assessment of individual and ensemble data-mining techniques for gully erosion modeling

Gully erosion is identified as an important sediment source in a range of environments and plays a conclusive role in redistribution of eroded soils on a slope. Hence, addressing spatial occurrence pattern of this phenomenon is very important. Different ensemble models and their single counterparts, mostly data mining methods, have been used for gully erosion susceptibility mapping; however, their calibration and validation procedures need to be thoroughly addressed. The current study presents a series of individual and ensemble data mining methods including artificial neural network (ANN), support vector machine (SVM), maximum entropy (ME), ANN-SVM, ANN-ME, and SVM-ME to map gully erosion …

PMT: New analytical framework for automated evaluation of geo-environmental modelling approaches

Geospatial computation, data transformation to a relevant statistical software, and step-wise quantitative performance assessment can be cumbersome, especially when considering that the entire modelling procedure is repeatedly interrupted by several input/output steps, and the self-consistency and self-adaptive response to the modelled data and the features therein are lost while handling the data from different kinds of working environments. To date, an automated and a comprehensive validation system, which includes both the cutoff-dependent and –independent evaluation criteria for spatial modelling approaches, has not yet been developed for GIS based methodologies. This study, for the fir…

Assessing and mapping multi-hazard risk susceptibility using a machine learning technique

AbstractThe aim of the current study was to suggest a multi-hazard probability assessment in Fars Province, Shiraz City, and its four strategic watersheds. At first, we construct maps depicting the most effective factors on floods (12 factors), forest fires (10 factors), and landslides (10 factors), and used the Boruta algorithm to prioritize the impact of each respective factor on the occurrence of each hazard. Subsequently, flood, landslides, and forest fire susceptibility maps prepared using a Random Forest (RF) model in the R statistical software. Results indicate that 42.83% of the study area are not susceptible to any hazards, while 2.67% of the area is at risk of all three hazards. T…

Effects of hydrological events on morphological evolution of a fluvial system

Abstract This study quantifies morphological evolution of the Dez River, Iran, from 1955 to 2016. The approach uses a sequence of Landsat images, aerial photos, and topographic maps. In addition, the hydrological data including average daily discharge and yearly maximum discharge at the Dezful hydrological station for the period (1955–2016) were used. The study reach was divided into 48 meander loops from upstream to downstream. Active channel width (w) was determined at 10 m intervals and changes assessed along the study reach of the Dez River. Morphological indices including sinuosity index; straight meander length; centerline flow length; erosion area; erodible length channel migration; …