Journal of Spatial Analysis

Climatic extremes are the special status (high or low) of climatic elements. In spite of the unique definition, there are a lot of thresholds which have been illustrated for extremes. For example, Bonneted (2006) has defined the climatic extremes as intensive and abnormal events that include the lowest and highest values in a time series. Becker et al. (2007) have referred to the extremes of climate as events in every given point that exceeds a special threshold in that place. High extremes and the upper tail of precipitation distribution of frequency have attracted a lot of attention of experts. The thresholds of extremes have been chosen based on geographic situations. The Joint World Meteorological Organization Commission (CCL) for Climatology on Climate Variability and Predictability (CLIVAR) Expert Team on Climatic Change Detection, Monitoring and Indices (ETCCDMI) have been established in 1998 in order to study and determine the indices of climatic extremes. They have introduced quintile indices. Due to consequences of extreme precipitation characters e.g. frequency, duration and intensity, the precipitation extremes have been in the center of attentions of many branches of science. Some experts call these events as social challenges that can determine economic sustainable development.  Extremes analyses are based on investigating the tails of statistical distribution of daily observations, because the longest time scale couldn’t show what it should have shown for extremes. Heavy precipitation for each day is defined as precipitation which is more than normal precipitation of that day in every given place. For this amount of precipitation absolute and relative thresholds have been defined. In present research, heavy precipitation is defined based on relative index and percentile parameter. By using 90th percentile, some characters of tempo-special distribution of extreme precipitation in Northwest of Iran are analyzed based on 729 stations. Northwest of Iran includes four province East and west Azerbaijan, Ardabil and Zanjan. This part of country has 126544.4 and occupied 7.2% of the entire country mainland. Geographic location of Northwest of Iran is located between the following coordinates:    The averages of sea level pressure (SLP) and 500 hp level patterns have been examined. Therefore, two data groups, station based and atmospheric based, have been used. Station based data include precipitation measurements during 1968-2007 synoptic , climatology and rain gauge stations related to Islamic Republic of Iran Meteorology Organization (IRIMO), rain gauge stations of Ministry of Power. Kriging Method is used as optimum interpolation method in order to provide maps of 14975 days. The pixel size of interpolation is chosen with 33× 33 kilometers dimension (approximately 116 pixel). Thus, data set of northwest precipitation with 14975 × 116 dimension and S-mode have been arranged. Atmospheric data include SLP and 500 hp data have been derived from NCEP/NCAR. The area experiencing heavy precipitation from 10-20 to 60-70 percent have been investigated. The map average and precipitation and precipitation center for all of these cases have been estimated. Some characters, for instance tempo-spatial presentation of heavy precipitation has determined by using Geostatistics Methods. A 14975  116 pixel data network was defined. According to 6 categories of extreme precipitation have been recognized. These categories are based on the extent of the area under extreme precipitation. It has been discovered 6 categories 10-20 percent to 60-70 percent of space under investigation. With the average increase of extreme precipitation amounts, the central mean of precipitation has centralized and the isohyets have become irregular. The small change in central mean of precipitation, a serious change had happened in precipitation distribution.   Mean of SLP pattern showed Siberian high pressure system that extended from east to west and indicated positives anomalies. low pressure system in the Red sea which is extended to Europe region and its extension to eastern of Mediterranean sea, south and north of Saudi Arabia as well as its extension to northwest and sometimes the whole west parts of Iran, formed an area with negative anomalies. The low pressure system which was close to European high, formed extreme pressure gradients. In the 500 hp level, the northwest of Iran is in front of the trough which is located in the east of Mediterranean Sea. As the depth of the trough increased, the area where experiencing heavy precipitation increased and the axis of the trough changed from vertical into horizontal shape. The occurrence of the trough formed negative anomalies in the area. In all cases, there are two ridges immediately in west and east of the trough  of the Mediterranean Sea. The occurrence of the western ridge caused cold air mass flowing in the trough where the Mediterranean’s warmer air mass exists and made the front’s formation possible. As the eastern ridge moved eastward, the area where experiencing heavy precipitation increased.

For a synoptic analysis of high polluted days in 13 and 14 November 2007, a combinatorial synoptic analysis was used. From methodology prospect, the present study has utilized the "circular environment" synoptic approach and with respect to the restrictions on very high-polluted days in Mashhad city, the subjective synoptic analysis used for data processing and analyzing the prevailing atmospheric conditions.

In the present research, four sets of the data, including the pollution data recorded at the stations monitoring air pollution, digital atmospheric data, data of upper air stations and the outputs of HYSPLIT model were utilized. The data on air pollution obtained from the Department of Environment Protection of Khorasan Razavi were related to Wahdat station located in the center of Mashhad city. The pollutants include CO, NO₂, SO₂, ozone, and particulate matter (PM₁₀(  prepared and processed on a daily scale for a 7-year statistical period (2005-2012). When studying the quality of air pollution over Mashhad city, it is necessary to indicate that Mashhad city had only one station monitoring air pollution (Wahdat station) until 2010 and unfortunately, out of 10 present stations for monitoring the air pollution, only Wahdat station was involved a suitable statistical period duration to be studied. Accordingly, the present study has been conducted only by using the pollution data recorded in Wahdat station and utilizing the data of other stations ignored due to the shortness of statistical period duration. The reanalyzed data of the National Centers for Atmospheric Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) with a horizontal separation 2.5 × 2.5 were used in order to study the atmospheric conditions. The atmospheric conditions include the sea level pressure, geo-potential height, vertical velocity, and orbit wind (u) & meridian wind (v) components on different atmospheric levels from the past 48 hours and in a 6-hour interval. In addition, upper air data about Mashhad station (Mashhad airport) were used on a similar period. Upper air data have been obtained from the website of Wyoming university (http://weather.uwyo.edu/upperair/sounding.html) on under study days, including air temperature,  dew point, direction, wind intensity and the atmospheric stability and instability conditions (based on Skew-T Curves – logP). These data are only available on Zero Greenwich hour. The outputs of the HYSPLIT model were also used as complementary data for tracing particulate matter in days 10 -15 in November. In this study, the HYSPLIT model, version 4.9 was used. In the present research, the role of regional atmospheric circulation and pressure patterns were investigated on a synoptic scale in very high-polluted days in November 2007 in Mashhad metropolitan. For this purpose, the mechanism dominated on occurring a very high-polluted period in this city was analyzed using a combinatorial method based on synoptic and thermodynamic analyses as well as tracing particulate matter. The results of studies involve the following findings: the days 13 and 14 November 2007 (22 and 23 Aban, 1386) show the highest concentration rates among the polluted days in Mashhad city. The findings of the research show that the synoptic pattern dominated the very high polluted period (13 and 14 November 2007) is a migrant high-pressure pattern. Accordingly, it may be concluded that the incidence of serious pollutions in Mashhad is initially the result of interacting local conditions with air circulation on a regional scale and then the other local factors. In the other words, Mashhad city would experience very high-polluted days only when regional atmospheric circulation provides suitable conditions to increase the concentration of pollutants. What is obvious is that in the winter season the serious pollutions occurred in Mashhad city are mainly as the results of prevailing extra-tropical systems (migrant anticyclone). Studying subjective synoptic analysis, tracing the backtracking of particulate matter and the atmospheric thermodynamic conditions ( combinatorial synoptic analysis) have provided a deeper and more accurate understanding of the conditions prevailing in the occurrence of serious pollutions in the northeast of Iran. Studying the output of the HYSPLIT model indicates that the migrant stack system of western wave together with the subtropical stack would control the air circulation pattern on the northeast of Iran in 13 and 14 November 2007. Tracing the particulates shows an anticyclone system on the zone. Also, studying SKEW-T Curves related to the migrant high-pressure pattern revealed a different structure, so that the day 12 November 2007 faced with a radiation inversion along with an increased temperature, but on day 13 November 2007 an inversion from the sort of subsidence between the interval of level 850 to 700 hpa was appeared and also reached to higher than 700 hpa.

As an important factor to be considered, rapid population growth, lack of resources and appropriate management has led the natural hazards threatening human societies increasingly. Although it is impossible to eliminate the effects of natural hazards, however, risk reduction and risk cities against natural phenomena has become the main topics of urban planning and design in recent years. Iran is one of the countries that are faced with numerous natural hazards. With Location and geographical characteristics, Iran is a main country located in earthquake belt; therefore earthquake is one of the main natural hazards in human settlements. Now, more than 70 percentage of Iran are at risk of earthquake. This study investigated spatial effects of urban roads and network on vulnerability in Amirieh neighborhoods. The aim of this study, identification and isolation of factors affecting the vulnerability of urban streets and quantify the effect of each factor is the vulnerability. Amirieh neighborhood with 10 (he) area, located in center of Sabzevar city. Amirieh is part of the detorated urban fabric in Sabzevar, therefore, earthquakes it is one of the main threats of this urban historic neighborhood. As a holistic approach, safety and immunization of the city is in regard with the recognition of constituent elements of urban structure completely. Comprehensive identification is aimed at reducing the vulnerability of urban and urban elements. In order to, one of the most important elements is the road network and impacts on the vulnerability of urban neighborhoods. Neighborhood is smallest unit of urban spatial planning that has the most important role in the planning and reduction at the risks of natural hazards. The spatial relationships between the components of an urban system that can fit through association with the whole city would be reduced environmental hazards, particularly earthquakes.-From planning perspective, any activity be organized in small-scale and size, will increase the possibility of its constituent elements in crisis management. The vulnerability of urban networks in related to spatial structure and impact on other infrastructure directly. The nature of the vulnerability of urban streets can be based on three factors: the structure, origin and traffic. As a structure, form and pattern of urban access associated with the vulnerability that this pattern is in related to urban network movement geometry and topological properties. Road network and access can be analyzed spatially by both composition and configuration. Composition of road network affected by the physical geometry and presented in different scales and defined by location, form, length, angle and direction. While the configuration is sets of the points witch defined by the related lines. Roads determine accessibility to critical points, and are including topological features, displacement, time travel or transport costs.

In analysis process of data and maps, scientific methods and models were used such as geographic information systems (GIS), the Analytic Hierarchy Process and method (AHP) and weighted overlaying map. Research method involves the following steps:

1. Introduction of indicators: In order to determine the vulnerability of the network in the various aspects needed to be based on the criteria established to determine the vulnerability and damaging. In this study, selected Indicators include: Type of road, the width of road, construction quality, density, population density and age of the buildings.
2. To determines the importance and ranking criteria: Each of the above criteria has the sub-criteria which based on expert opinions, and comparing them with field studies. The (AHP) was used to weight sub-criteria for the experts and paired comparison.
3. To weight the criteria: At this stage, the selection criteria are weighted by research. To determine weights, the criteria and sub-criteria, were quantified by which is determined measure the intensity excellence criterion of i to j. At this step, the above criteria and sub-criteria in the form of a questionnaire was given weight by the Group of Experts. Then, weights of each criterion was determined the final weight by Expert Choice software.
4. Layers integration and production of Vulnerability final map: in order to produce the final map of vulnerability, the command Raster Calculator and weighted overlap method was used in the GIS environment. Density calculation is one of the suitable methods of spatial analysis. we calculated the density to represent the value of points or lines in the form of levels. In this study was used Kernel density equation for converting line to surface value, due to represent of spatial value. Map applying numerical value to each pixel density is formed in the periphery.

In Amirieh neighborhood, Results show that width of streets, land use, population density, quality of construction and age of building will be in the range of medium to high vulnerability. In this study, 50% of the length of passages, more than 73 percent of the quality of the existing structure, 69% of land uses, and more than 40 percent of population density were classified in the range of high to very high vulnerability. The final vulnerability map shows that more than 58% of the total area is in the range of high and very high vulnerability. The areas with moderate vulnerability involve 19 percent of the entire neighborhood approximately. The final map shows that areas with low vulnerability appropriate width placed adjacent to the passages open while the passages the end and low width are critical zone of significant congestion. Too, the results showed that the topological characteristics of the network involved in the formation of critical points. So that in the event of a crisis and then could impair relief and evacuation of the neighborhood. From spatial perspective, vulnerability is influenced by two urban network properties:

1. Urban network structure: The street network is determined based on geometric features. This communication and spatial distribution of the points and roads in the neighborhood.
2. Spatial hierarchy: Spatial hierarchy access to the neighborhood of the important points is that the crisis could guarantee public services.

One of the most important calamities that affect the arid and semi- arid regions and is taken into account as threatening factors for human- life and destroying the natural resources is desertification, so recognizing and forecasting this phenomenon is very important. Desertification is a complex phenomenon, which as environmental, socio-economical, and cultural impacts on natural resources. In recent years, the issues of desertification and desert growth have been stated as important debate on global, regional and national levels and extensive activities have been carried out to control and reduce the its consequences. Desertification is considered as the third important global challenge in the 21th century after two challenges of climate change and scarcity of fresh water. At present, desertification as a problem, involves many countries, especially developing countries and includes some processes that caused by natural factors as well as human incorrect activities. In the other word, Desertification is the ecological and biological reduction of land that maybe occur naturally or unnaturally. The desertification process influences the arid and semiarid regions essentially and decrease the lands efficiency with increment speeds. The study area is located in the east and south of Isfahan. This region has been faced to increasing rate of desertification, because of drought, vegetation removal, change of rangelands to dry farming lands, water and wind erosion and lack of proper land management over previous years. Hence, aim of this research is monitor and forecasting of desertification changes in the east and south of Isfahan during the period of (1986-2016). In this research, the Landsat satellite images used as studies base for studying region desertification. Therefore, at first, satellite images of the study area were extracted from United States geological survey(USGS)website during the period of (1986-2016) and data and satellite images of TM5, ETM+ 7 and LDCM8 sensors of Landsat satellite were used which include thermal and spectral bands. In this relation, for studying the desertification condition in the south and east region of Isfahan, the Landsat satellite images of 4, 7 and 8 during 5 periods of 1986, 1994, 2000, 2008 and 2016 have been utilized. After completing the information data base, first, the soil salinity(S1, S2 and S3) and vegetation NDVI indices exerted on the satellite images. According to Fuzzy ARTMAP method, the land use changes during the period of (1986-2016) recognized in the studied region. In the other word, the vegetation NDVI and soil salinity (S1, S2 and S3) indices have been utilized for identifying vegetation and the desert and salty regions. For preparing the region land use map, the Fuzzy ARTMAP supervised classification method have been utilized and 5 land uses(desert and salty lands, vegetation, city, arid and Gavkhouni) in the region were identified by TerrSet software. The changes calculation in region uses during 5 periods accomplished by LCM model. Also, the Markov chain and Cellular automata synthetic model have been utilized for changes forecasting. This research results indicated that the greatest changes during studied period belonged to vegetation. This volume of change had been during 1986- 1994 that indicate 1062 km2 desertification. In the other hand, the greatest intensity of increasing the salty and desert regions have been occurred during 1994-2000 which indicate 495 km2 increasing. The CA- Markov synthetic method have been utilized for forecasting the land uses changes trend, too. In this relation, for assessing the forecast accuracy, the Kappa coefficient have been utilized which indicate 78%. Finally, it has been specified that the greatest changes during 2016-2024 will be in vegetation which about 60% of region vegetation will disappear and arid lands will be replace them. The salty and desert lands will disappear about 1% of vegetation, 3.3% of arid land and less than 0.01% of city and Gavkhouni. During 2016-2024 about 32% of Gavkhouni lagoon area will disappear and arid lands will be replace them.