SPATIAL Autocorrelation (SA) is the correlations of the observed data of an area in the form of SPATIAL pattern. The criterion of SA phenomenon occurrence is when the distribution of one observed variable value follows a particular pattern systematically.

Introduction: In recent century, human safety from crime is very important in everyday life. In terms of human needs, Maslow's (1943) hierarchy of needs suggests that sustainable environments should cater for biological and physiological needs, safety, affiliation, self-esteem, and self-actualization, respectively. Crime and avoidance from of are surely important in people's agenda as the most important issues in many countries worldwide. Geographers deal with the distribution of a wide variety of geographical entities and phenomena amongst human safety and freedom. They analyze SPATIAL distributions, pattern of this distribution in terms of objective and subjective phenomena, SPATIAL variability and so forth. The concept of SPATIAL analysis is related to discovery of SPATIAL patterns, causes and effects of phenomena, autocorrelation, etc. In the past, when performing SPATIAL crime analysis, geographers were limited to mapping crimes in locations and regions. However, technological improvements, first and foremost in the computer processor capabilities, have become essential in recent analytical advances in the methods available for analyzing place-based data. The initiation of computer mapping applications and additional geographic information systems (GIS) are important to being able to measure and represent the SPATIAL relationships in data. ESDA is a collection of techniques to describe and imagine SPATIAL distributions; identify unusual locations or SPATIAL outliers, discovering patterns of SPATIAL ASSOCIATION, clusters, or hot spots. Also, it suggests SPATIAL regimes or other forms of SPATIAL heterogeneity.

Introduction: Extreme precipitation is one of the most critical climate hazards and one of the consequences of climate change in arid and semi-arid countries. These hazards, if left unmanaged, could lead to economic and social damages. The present study aimed to identify the temporal and SPATIAL variations of extreme precipitation in Iran. Methods: Precipitation network data with a SPATIAL resolution of 15x15 were first used for a statistical period of 50 years (19612011). Then, for the purpose of variations of inter-decade precipitation in Iran, the study period was equally divided into 5 distinct periods. MATLAB software and GIS were used to perform calculations. For every periods, SPATIAL pattern, frequency, mean, coefficient of variation, and trend were calculated. The threshold of ≥, 95th percentile, and the coverage of 50% of the total area of the country along with the continuation of at least two days of precipitation were considered as the criterion for the extreme precipitation. Findings: The results of this study showed the highest frequency and extreme precipitation in the Caspian coast, the north-western and west, particularly the western Zagros. Investigation of the precipitation in different periods showed that the third period (1981-1990) had the highest frequency of extreme precipitation. It is while the highest coefficient of variability was observed in the first period (1961-1970) so that the maximum precipitation core was in the central and south-eastern Iran. Also, in spite of increasing frequency and precipitation trend in the southern half of the country in all periods, the northern half of Iran, particularly the Caspian coast had a decreasing trend.

Due to the unfair distribution of facilities and services, the issue of inequalities in various fields, especially in the education sector, is one of the issues that requires expert studies. In the present research, the analysis of educational INDICATORs in Iran has been done. The research approach is quantitative and the final study of 18 research variables has been done using multi-INDICATOR decision-making techniques such as Vikor technique and preference selection index. The results of Vikor technique show that Tehran has the highest score with a score of (0/0000). Khorasan Razavi is in a good position after Tehran with a score of (0/1830). In VIKOR technique, Ilam province with a score of (0/9759) and South Khorasan province with a score of (0/9763) have the lowest scores, and the status of educational INDICATORs in them is evaluated as poor and they need serious attention. The results of the preference selection index show that Tehran with a total score of (0/9509) and Razavi Khorasan with a total score of (0/8605) have obtained the highest scores in the preference selection index. The scores obtained from the preference selection index show that Semnan province with a total score of (0/2493), Qom province with a total score of (0/2693), Ilam province with a total score of (0/2730), and South Khorasan province with a total score of (0/2842) have the lowest scores. By using the Average nearest neighborhood the pattern of distribution of educational services in Iran, 1/530966, Z score 5/655593, and PValue 0/000 have been obtained. Based on the Average nearest neighborhood, the pattern of distribution of educational services in Iran has been scattered. Based on Moran's coefficient, the pattern of distribution of educational variables in Iran is Random.

Yazd Province is one of the most arid regions of Iran and its agriculture particularly pistachio cultivation depends on groundwater resources. In the recent decades, natural factors (drought and severe evaporation) and human activities (over-exploitation of groundwater) caused a sharp decline in the quality and quantity of groundwater in this province. In the present study, the SPATIAL and temporal variations in groundwater salinity (EC) were evaluated using geostatistical methods and ArcGIS software. For this purpose, ordinary kriging and INDICATOR kriging were used to prepare zoning and probabilistic maps, respectively. Zoning and probabilistic maps showed an increase of groundwater salinity towards higher than 8 dS/m from 2003 to 2012. It was also found that groundwater of Ardakan, Bafgh, Taft, and Abarkouh cities has a very bad condition in terms of salinity and using it for pistachio orchards irrigation can reduce seriously the yield of this plant and its cultivation in the province will be questionable. So as to avoid lowering the quality of groundwater resources in the province, appropriate management measures such as well volumetric water gauge installation and banning both well water extraction and new well water allocation are required.