Application of analytic hierarchy process, frequency ratio, and statistical index to landslide susceptibility: an approach to endangered cultural heritage

Is Overgrazing Really Influencing Soil Erosion?

“…Therefore, the specific objectives of this study are (1) spatially predict the gully erosion in the Bahluieț river basin; (2) employing two statistical models, FR and IV; (3) to evaluate the final susceptibility maps performance by using ROC curves; (4) to analyse the final susceptibility maps with and without the overgrazing as a conditioning factor; (5) to determine the number of Neolithic sites located in areas with high and very high susceptibility to gully erosion; and (6) to investigate the final susceptibility maps in the framework of big infrastructure projects (A8 motorway). Europe's cultural heritage is in danger from natural hazards [34] and anthropic interventions [35]; the cultural heritage from the northeastern part of Romania is no exception [19,[36][37][38][39]. However, significant efforts are made every year in order to highlight the importance of Neolithic sites in establishing the Romanian identity and to promote them from a tourism point of view [40].…”

“…The lithological setting of the area is characterised by non-cohesive deposits of Bessarabian age (an alternation of marls, clays with intrusions of sand, and oolithic limestone); the fine granulation of these lithological deposits led to the triggering and developing of geomorphological processes, The lithological setting of the area is characterised by non-cohesive deposits of Bessarabian age (an alternation of marls, clays with intrusions of sand, and oolithic limestone); the fine granulation of these lithological deposits led to the triggering and developing of geomorphological processes, especially gullying ( Figure 3). More details regarding the geomorphic characteristics of this area can be found in the literature [35][36][37][38][39]. Cucuteni culture is one of the most representative prehistoric cultures from Eastern Europe and is part of the well-known Cucuteni-Ariușd-Trypillia Cultural Complex (approximately 350,000 km 2 ).…”

“…Europe's cultural heritage is in danger from natural hazards [34] and anthropic interventions [35]; the cultural heritage from the northeastern part of Romania is no exception [19,[36][37][38][39]. However, significant efforts are made every year in order to highlight the importance of Neolithic sites in establishing the Romanian identity and to promote them from a tourism point of view [40].…”

Landslide Susceptibility Modeling Based on GIS and Novel Bagging-Based Kernel Logistic Regression

“…Statistical models are most commonly used in landslide susceptibility mapping, which are based on the analysis of the relationships between influencing factors and existing landslides [7]. In these statistical approaches, bivariate and multivariate statistical techniques are used for landslide susceptibility mapping throughout the world, including frequency ratio [8][9][10], index of entropy [11][12][13][14][15], bivariate statistical analysis [16], multivariate adaptive regression spline [17], analytical hierarchy process [18,19], statistical index [20,21], weight of evidence [13,21], evidential belief function [22,23], certainty factor [24,25], and logistic regression [26][27][28][29].…”

Landslide Susceptibility Evaluation Using Hybrid Integration of Evidential Belief Function and Machine Learning Techniques

“…The results showed that the RSCART model is the optimal model with the highest AUC values of 0.852 and 0.827, followed by LR and CART models. The results also illustrate that the hybrid model generally improves the prediction ability of a single landslide susceptibility model.Water 2020, 12, 113 2 of 29 weights of evidence [10][11][12], frequency ratio [13][14][15][16][17], logistic regression [18][19][20][21], linear multivariate regression, multivariate adaptive regression spline [22][23][24], and statistical index [25,26] have been widely used. However, these traditional statistical methods do not provide satisfactory evaluation of the correlation between landslide influencing factors [4,27].Therefore, machine learning technologies have drawn extensive attention, and many kinds of machine learning methods have been developed and used, such as classification and regression trees [28,29], adaptive neuro-fuzzy inference systems [30,31], fuzzy logic [32,33], alternating decision trees [34][35][36], support vector machine [37][38][39], artificial neural networks [40,41], and random forest [4,[42][43][44][45].…”