Landslides are the most frequent phenomenon in the northern part of Iran, which cause considerable financial and life damages every year. One of the most widely used approaches to reduce these damages is preparing a landslide susceptibility map (LSM) using suitable methods and selecting the proper conditioning factors. The current study is aimed at comparing four bivariate models, namely the frequency ratio (FR), Shannon entropy (SE), weights of evidence (WoE), and evidential belief function (EBF), for a LSM of Klijanrestagh Watershed, Iran. Firstly, 109 locations of landslides were obtained from field surveys and interpretation of aerial photographs. Then, the locations were categorized into two groups of 70% (74 locations) and 30% (35 locations), randomly, for modeling and validation processes, respectively. Then, 10 conditioning factors of slope aspect, curvature, elevation, distance from fault, lithology, normalized difference vegetation index (NDVI), distance from the river, distance from the road, the slope angle, and land use were determined to construct the spatial database. From the results of multicollinearity, it was concluded that no collinearity existed between the 10 considered conditioning factors in the occurrence of landslides. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used for validation of the four achieved LSMs. The AUC results introduced the success rates of 0.8, 0.86, 0.84, and 0.85 for EBF, WoE, SE, and FR, respectively. Also, they indicated that the rates of prediction were 0.84, 0.83, 0.82, and 0.79 for WoE, FR, SE, and EBF, respectively. Therefore, the WoE model, having the highest AUC, was the most accurate method among the four implemented methods in identifying the regions at risk of future landslides in the study area. The outcomes of this research are useful and essential for the government, planners, decision makers, researchers, and general land-use planners in the study area.

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The appropriate locations of road emergency stations (RESs) can help to decrease the impact of traffic accidents that cause around 50 million injuries per year worldwide. In this research, the appropriateness of existing RESs in the Khuzestan province, Iran, was assessed using an integrated fuzzy analytical hierarchy process (FAHP) and geographic information system (GIS) approach. The data used in this research were collected from different sources, including the department of roads, the department of health, the statistics organization, forensics, police centers, the surveying and geological department, remotely-sensed and global positioning system (GPS) data of accident high crash zones. On the basis of previous studies and the requirements of the Ministry of Health and Medical Education, as well as the department of roads of Iran for the location of RESs, nine criteria and 19 sub-criteria were adopted, including population, safety, environmental indicators, compatible area in RES, incompatible area in RES, type of road, accident high crash zones, traffic level and performance radius. The FAHP yielded the criteria weights and the ideal locations for establishing RESs using GIS analysis and aggregation functions. The resulting map matched the known road accident and high crash zones very well. The results indicated that the current RES stations are not distributed appropriately along the major roads of the Khuzestan province, and a re-arrangement is suggested. The finding of the present study can help decision-makers and authorities to achieve sustainable road safety in the case study area.of medical services, such as pre-hospital medical and transportation, trauma care and assistance for people who in need of emergency care [7]. Definitions differ, but in most cases, the geographical availability and provision of services are introduced as main factors [8,9]. Choosing optimal locations for emergency stations can help to achieve these aims. The locations of road emergency stations (RESs) are one of the most critical factors that can play a role in the degree of damage caused by accidents. Proper distribution of RESs is key to being able to respond to accidents within a standard time [10]. Therefore, determining optimum locations for RESs is a vital issue that road administrators face [11].After cardiovascular diseases, road accidents are the main reason for death in Iran [12][13][14]. Iran has a very high rate of road accidents; it is twenty times greater than that of the world's average [15]. The number of fatalities per 100,000 people per year for Iran is 32.1 (Figure 1). According to a UNICEF report, every 19 min one person passes away on Iran's roads, and every 2 min somebody is informed that one of his/her family members has survived a crash accident but with severe injury that may cause lifetime disability [16]. Each year, road traffic accidents cause the death of almost 28,000 people and disable or injure 300,000 more in Iran [12]. Cost of traffic fatalities in Iran is estimated at $6 billion U.S. every y...

Landslides are one of the most detrimental geological disasters that intimidate human lives along with severe damages to infrastructures and they mostly occur in the mountainous regions across the globe. Landslide susceptibility mapping (LSM) serves as a key step in assessing potential areas that are prone to landslides and could have an impact on decreasing the possible damages. The application of the fuzzy best-worst multi-criteria decision-making (FBWM) method was applied for LSM in Austria. Further, the role of employing a few numbers of pairwise comparisons on LSM was investigated by comparing the FBWM and Fuzzy Analytical Hierarchical Process (FAHP). For this study, a wide range of data was sourced from the Geological Survey of Austria, the Austrian Land Information System, Humanitarian OpenStreetMap Team, and remotely sensed data were collected. We used nine conditioning factors that were based on the previous studies and geomorphological characteristics of Austria, such as elevation, slope, slope aspect, lithology, rainfall, land cover, distance to drainage, distance to roads, and distance to faults. Based on the evaluation of experts, the slope conditioning factor was chosen as the best criterion (highest impact on LSM) and the distance to roads was considered as the worst criterion (lowest impact on LSM). LSM was generated for the region based on the best and worst criterion. The findings show the robustness of FBWM in landslide susceptibility mapping. Additionally, using fewer pairwise comparisons revealed that the FBWM can obtain higher accuracy as compared to FAHP. The finding of this research can help authorities and decision-makers to provide effective strategies and plans for landslide prevention and mitigation at the national level.

Plants disease epidemiology provides us with some information about the spread of diseases in different regions with various climates and helps us conduct suitable managing operations and predictions about the spread of disease to other areas. Geographic Information System (GIS) has been widely used as an important tool in epidemiological studies. Wetwood disease is one of the most important bacterial diseases on elm trees found in the Northwest of Iran. The disease has spread in different regions of Tabriz (located in the Northwest of Iran), which has become terribly epidemic. Geographic Information System as an appropriate tool in epidemiological examination of plant disease is useful in various ways. In this study, the epidemiology of bacterial wetwood disease on elm trees in Tabriz was investigated using GIS databases. The results indicate that the disease has become epidemic in different areas of Tabriz. According to the results, although the disease was not found in some regions, its severity was very high in some other areas. Based on the distribution map, the wetwood disease most highly exists in the central regions and some parts of the northern regions of the city, but eastern regions are least affected.