The aim of this paper is to present a Modified version of GAM (M-GAM) which should show that the results gained by using this version are more accurate and realistic. The modification is based on the inclusion of tourists and their opinion regarding the importance of indicators in the assessment process. The assessment was done by using both versions of GAM and the results were compared and analyzed afterwards. Both assessment methods were applied on the Lazar Canyon area located in eastern Serbia, a territory which possesses a large concentration of geosites on a relatively small surface area and it has great potential for geotourism development. The study revealed that the inclusion of tourists in the assessment process can have crucial impact on the final results. By introducing the importance factor in the Modified model we were able to point out those values which are of paramount importance for tourists. This can be rather useful in the improvement and planning of tourism activities as it exactly shows which of the lower values should receive the most attention in the future based on their significance for tourists.

The purpose of this article is to compare the karst geomorphosites of Kermanshah province based on the two key indicators of core values and complementary values using Vojisic 2011 Geosite Evaluation model (GAM) and Tamik Modified model (M-GAM) and Bozic 2014. The research type is applied and has been done by descriptive-analytical method (with field survey technique). The study area includes 6 geosites of Kermanshah province (Rijab waterfall, Bistoon mirage, Taghbestan mirage, Gilat-e-Gharb mirage, Sahneh mirage and Ghori Qaleh cave) which have rich environmental foundations for the development of geotourism. The results showed that the geomorphosites have appropriate scientific / educational and aesthetic value, but in terms of tourism values, the geomorphosites of the study area are not in a favorable condition. The Taghbestan mirage is in a good condition in terms of core values and complementary values. Also, the geomorphosites of Sarab Biston and Quri Qaleh cave are in a relatively good condition from this point of view, while in general, most geomorphosites of the study area has a higher core value and a lower complementary value. In other words, these geomorphosites can only be considered as potential tourist attractions in terms of scientific / educational, aesthetic values and need to promote sustainable tourism. Overall, the evaluation results of the models show a completely vague and deceptive picture of the current situation. The findings indicate that the inclusion of tourists in the Modified model of geomorphosites gives a more realistic and clear picture that can be useful in improving and planning the tourism activities of the province's geosites.

Land heritage and necessity of planning in order to safeguard this heritage is one of the greatest challenges facing the researchers of untouched spaces and international natural heritage. One of the most important instruments in this approach is considering tourism capabilities in the form of geological attractions and geomorphology of the land heritages and its bond with economical, cultural and social features of tourism. Geotourism plays an unparalleled role in the development of economic, cultural and environmental effects on land management and planning for the conservation and sustainable development of the geological heritage. The Alamut area of Qazvin, along with the legacy of land, is a significant destination in the country from the cultural and social point of view. In order to reach the goals of the sustainable development, it is important to identify the crucial geosites of the region and analyze them based on their different geo-tourism values. In the meantime, East Alamut is one of the areas that can attract many tourists with a variety of natural phenomena. In this study, using satellite images, geological maps, and field studies, 10 East Alamut lands with higher geo-touristic attraction were selected. In the final review of geo-tourism assessment based on the GAM method, the geosite of the Kalayeh Moalem was identified as one of the top geosits due to its scientific value in national level, having aesthetic, cultural and social values, and the existence of a set of functional, economic, and tourist services values. Evan Lake is also in the second priority due to high geological diversity, its ecological and cultural values, easy access, tourism services, appropriate infrastructure and also aesthetic and protective values. Alamut historical area, next to the Garmarud Valley is on next priority.

In this research, the Geosite of Sahoo Mountain has been investigated using Geosite Assessment model (GAM) which considers providing sustainable planning and natural heritage management and rendering them to tourism targets. It is based on previously- mentioned assessment models and proposed to evaluate the geo sites through two groups of main values and supplementary value. In the general assessment of Shahoo Mountain, the geo sites including Ghoori Ghal'e Cave, Sirvan Valley and Ravansar Spring got the high score of 20.5, 16.75 and 16.5, respectively and were identified as the best geo sites for geo-tourism purposes. The results show that they involve almost suitable scientific-educational and aesthetic value; however, they are not in good conditions in terms of tourism values of the studied regional geo sites. Also, from a conservation perspective, no active protection is done and as they are unknown, they become safe. Finally, it can be said that besides other natural and cultural values of Shahoo Mountain, it can provide an appropriate perspective to develop sustainable development of geo-tourism.

In recent years, Geotourism has become a major contributor to sustainable development issues, And has been raised as a focal point, especially for less developed local communities. Nevertheless, the experience of this field in the world shows that effective and real management positions are very efficient in this direction. Accordingly, the study of Geomorphodiversity and the identification of Geomorphosites and their actual monitoring with the hazardology approach is one of the correct paths in this area. In this research, this issue was investigated in Sardasht city by GAM model that based on expert opinions. The results of the study were to identify 14 geocytes of the index Which has basic capabilities in this field. Their analysis showed that the Shalmash Waterfall Geosite and Meadabad Forest Geosite have the highest value and the Kachaka cave, Sarprdan Karstic masses have the lowest value. However, analyzing the position of Geosites based on the GAM matrix and the Hazardology approach showed that the main value at the level of the Geosites is higher than the additional value. However, more accurate studies showed that in the main value, the protective sub-value is lower than the scientific and aestheticsub-values. Therefore, the existence of Geoconservation strategy is required depending on the active or inactivity of the Geosites as well as the development of the infrastructures in less active and active Geosites, respectively. The existing Hazardology approach showed that increasing access level through the development of main communication paths, increasing amenities, and especially the development of tourism residences that are also the basis for employment, is very effective. The existing approach have shown that branding is also an appropriate field, but the importance of educating and informing local communities about the stability of Geosites is very important. It can be said that the right move in the direction of tourism in the city of Sardasht provides for the establishment of sustainable employment, the implementation of Geoconservation strategy, the development of border security, and the creation of an appropriate alternative to false occupational concepts and, ultimately, sustainable development.

Landslide is one of the most common natural disasters that endanger the lives and properties of people in mountainous areas. Therefore, identification of risk exposure areas of landslide is essential to prevent and reduce damages by landslides. The purpose of this study is compared to logistic regression (LR) and generalized additive models (GAM) and the evaluation of their performance for landslide susceptibility mapping in the Chahardangeh Watershed, Mazandaran Province. At the first, landslide locations were identified by Google Earth images and extensive field survey. Then, the landslide inventory map was randomly divided as training data 70% for modeling and the remaining 30% was applied for the model validation. The landslide conditioning factors including topographic, hydrologic, geology and human factors were constructed in GIS. Finally, the receiver operating characteristic (ROC) Curve was used for the model validation. The validation of results showed that the area under the ROC curve for LR and GAM models were 81. 2% and 82. 4%, respectively. So, both of the models are suitable and efficient methods for landslide susceptibility mapping in the study area. Although, the obtained results showed that the GAM model performed is slightly better than the LR model for determining regions of susceptible to occurrence of landslide in the study area.

This reaserch utilizing Gap model evaluates Dehyaris’ services quality. To this end on the basis of theoretical principles and Dehyaris’ responsibilities 32 statements in behavioral, structural, social, economic and hygienic aspects was defined. The study area is 29 villages of Bonab County of East Azabaijan County (Iran). Population size consists of 14559 rural householders inhabited in mentioned villages and according to Cochran’ s formula sample size equal to 400 persons. Research instrument was rural householder’ s questionnaire that its validity approved by expert panel and Reliability confirmed via Cronbach’ s alpha (α > 0. 88-α > 0. 90 in all aspects). Findings revealed that in all mentioned aspect Deharys’ services quality was little and the gap between peasants’ expectations and perceptions especially in regard of economic aspect was greater than other dimensions. Also determined that between variables such as Dehyar’ s quality of behavior, his age and his participating in vocational education courses, with Deharys’ services quality in various aspects there is approvable positive correlation. Furthermore in regard of factors same as rural mayor’ s education level, his second job and type of his presence in village, significant differences can be seen in Deharys’ services quality. Finally items such as arranging coordination and cooperation between sectors and organizations, considering organizational behavior, experience, educational quality and vocational education factors put forwarded for improving rural municipalities’ services quality and increasing peasants’ satisfaction.

The prediction models of geographical distribution of the plant species are probabilistic and static models.They determinate the mathematical equations governing on geographical distribution of species with their current environment and environmental factors effective on the distribution of species. The aim of the current Study is to review the performance of Generalized Linear model (GLM) and Generalized Additive model (GAM) in determination of the relationship between vegetation and environmental factors in Polour rangeland. Stratified random sampling method was used. Five dominant species include Astragalus ochrodeucus, Ferula gumosa, Thymus kotschyanus, Onobrychis Cornata and Agropyron Sp were identified.the studied environmental factors were including 13 soil characteristics, 3 topographic factors and 3 climatic factors. The analyses were performed using Presence-Absence and GRASP package of R software. Also for evaluating the performance of prediction model, the statistical coefficients including AUC, AIC, RMSE and R2 were used. The results showed that the highest R2 in GLM model is related to presence of Agropyron Sp with 0.98 and also the lowest RMSE and AIC is related to Astragalus ochrodeucus with 0.29 and 12 respectively. Also in GAM model the highest R2 is related to Thymus kotschyanus with 0.98 and the lowest RMSE and AIC is related to Astragalus ochrodeucus and Ferula gumosa with 0.22 and 18.12 respectively.Also the highest AUC in GLM model is related to Onobrychis Cornata and in GAM model is related to Agropyron Sp with 0.86.Given the value of protecting and valuable plant species studied, the results of these models can be used in programs of conservation and improvement of the tourist area.

Flood is a phenomenon that causes a lot of environmental and socio-economic damage. The purpose of this study is to evaluate the efficiency of CART, GLM and GAM machine learning models in identifying flood risk areas in the Kashkan basin. Lorestan province and especially Kashkan basin, including: Selseleh, Delfan, Doreh, Khorramabad, Poldakhtar and Kuhdasht, is flooded and has suffered flood damage many times and in April 2019, experienced the largest flood of the last 200 years. In this regard, various factors including: height, slope direction, land curvature, slope percentage, distance from the river, drainage density, soil, lithology, land use and topographic moisture index were used. The digital map of all the mentioned factors was prepared in ArcGIS10.5 software and in the form of a database. The location of 123 flood events recorded in recent years in this basin was collected and randomly used in two categories of model training (86 cases) and model validation (37 cases) in modeling. Using machine learning models and environmental factors, flood potential prediction maps were prepared and then validated using AUC characteristic curve methods and TSS index. The results of model validation showed that CART machine learning model with AUC = 0.91 and TTS = 0.88 index was the most accurate model in predicting flood risk potential, followed by GAM model with AUC = 0.87 and TSS index = 0.84 and GLM model with AUC = 0.83 and TSS index = 0.88. Accuracy 0.91 CART model indicates the excellent accuracy of this model for the Kashkan basin. This model shows a larger area of ​​the basin under high potential and moderate flood risk conditions, which include most of the western areas as well as the central areas of the basin (Kuhdasht, Khorramabad and Poldakhtar), which are exactly parts The same areas were flooded in the great flood of 2019 and it is necessary to be in the first priority of flood risk planning and management in this basin.