فصلنامه فضای جغرافیایی
پیاپی 71 (پاییز 1399)

Today, the concept of justice as essential in the process of urban planning and management of metropolitan areas studied, and primarily urban development requires social justice and the environment in cities. The right to adequate housing for all and justice Drmhm part of the urban land, in order to achieve justice and fairness in space in cities is of particular importance. The aim of this study was to assess the status of urban housing in the city is focusing on social justice. In fact, to achieve the answer to this question is whether in the city in terms of quantitative and qualitative indicators of balance and equality in the development of their housing.In the present study compared the final resolution of ten districts of the city housing VIKOR method is used. The results indicate an imbalance and disparity between Shiraz metropolitan areas so that the final index of 30% and 40% in areas of disadvantage are five indicators to test have an average level on them, which result of Azgham Towns in the city and especially the old texture in more central areas and the old city area is two and eight.

In this study, to investigate the disturbance drainage basin, 80 sub-basins were determined. The maps of geology, drainage, raster maps, fault basin was prepared. The performance area and perimeter of the basin, number and length of channels, frequency of drain, angle General, Internal angle faulting density, and angle of internal and public were calculated. The number of faults in the fault zone is about 10 to 15. These fault zone rock properties of marl, limestone, flysch, limestone, dolomite and limestone were Cenomanian. Analysis of variance based on lithology and density fault factors showed that there was a significant difference between the studied variables. Results of mean comparison with Duncan test showed that the sub-basins located on fault zones 2 and 3 are most disturbed drainage, respectively. Multivariate analysis results indicated that sub without fault in a category. Sub-basins of 73, 50, 51 and 72, however, the role of the effects of no-fault. But according to studies done on morphometric characteristics of a fault in the sub-groups, respectively. Sub basin of 2, 13, 4, 6, 14, 16, 23, 8, 39, 34, 70, 77, 80, 52, 67, 78, 7, 12 and 79 were the only sub basin that is likely to have undiscovered fault, was high.

Karst is a geomorphic and hydrological system formed by dissolved gems such as limestone, dolomite and gypsum (Oziert et al., 2014).In this study, considering the foreign and domestic studies, and considering the role of Paleoclima and the high difference of the ancient climate of this region with present-day climate in the degree of karst karsticity in the region, the degree of karstification of the basin with field, experimental and The hierarchical analysis model was developed.The study area is Kalat Mountain basin in Kopeh Dagh zone, located in the highlands of the thousand mosques and northeastern parts of the country. This basin has an area of 168.37 km2 located 145 km north of Mashhad and in Khorasan Razavi province.

Techniques used in this research include field, empirical, and hierarchical techniques . 1. techniques field A. Classification of Karstic forms of basin based on the method of Cvijic B) Division of karstic forms based on Waltham and Fox methods C) Evidence of Karst geomorphology of Kalat mountain basin   2) Experimental formulas of karst A) Corbel equation X=4ET/100 B)The switching equation X=FQTN/(  3) Laboratory techniques to investigate the dissolution of basin karst   A. Measurement of lime in sediment by calcicometric (volumetric) method with Bernard calcium    B) ICP method (analytical inductive coupled plasma) C) Weighting method 4) Analytical Hierarchy Model   

To identify the degree of karstification of the basin with field evidence, empirical and hierarchical analysis model, the following are cited separately: 1. You want to know:  Field evidence includes Cvijic methods, Waltham, and geomorphologic evidence. The following is a summary of the field evidence: Based on this categorization, the Kalat basin karsts are placed in the row of transition karsts. Because in this basin, the dimensions of the caves are small and not very large. Poles, also known as karst areas, are not formed in this basin, and because of their slopes and inappropriate topography they are not likely to be formed in the future. Devils do not have much to gain in the basin. Other forms of karstis also have not evolved.   According to this division, basin karsts are placed on the young karst ranks In the studied basin, the diversity of landforms is low due to field visits to the basin, and it lacks any cave deposits, and the cave does not really exist in it, and the karst hydrogeology is not much developed. These reasons make the study of the studied basin more youthful to semi-evolutionary. 2) Experimental formulas of karst A) Result of Corbel equation According to calculations, the number is obtained  23.66 mm per thousand years B) Result of The switching equation According to calculations, the number is obtained  12.92 mm per thousand years . 3) Result of Laboratory techniques to investigate the dissolution of basin karst A. Result of  Measurement of lime in sediment by calcicometric (volumetric) method with Bernard calcium . According to calculations, the number is obtained  36.3 B) Result of ICP method (analytical inductive coupled plasma):   In order to perform the experiment, four rock samples were taken from four important limestone formations of the basin of the ICP technique and analyzed in the laboratory and the results are as follows: Table 4: Calcium (Ca) element content in Kalat Mountain basin divided by four formations per% Type of formation Calcium content in% Tirgan 38.90 Mozduran 2 38.34 Sarcheshmeh 38.41 Shurijeh .7 C) Result of Weighting method According to this experiment, 4 samples of Tirgan, Mozduran 2, Kalat and Sarcheshmeh showed 4/3% of the total amount of lime in the sedimentology laboratory.  Result of Analytical Hierarchy Model The basis of this model is the comparison of the parameters of the parameters and ultimately the zoning of the karstic transformation. Considering the role of the various factors and the development of the karsts of the region in the past, and considering the different paleoclima of the past region with the current situation and the role of the various factors in the development of eight layer karst Information was selected. Based on field studies and the opinion of experts and consultants in the doctorchr('39')s thesis, the lithology factor was chosen as an important parameter in the development of the karst. After that, the distance from the fault was selected considering its important role in the development of the gap and gap. The climate and then the elevation are factors that have been selected as the important and influential factor on rainfall, evapotranspiration and temperature in this study. Subsequently, layers, slope, distance from the waterway were selected for slope and land use. Different layers of information have been categorized into standard layout and field visits by applying expert judgment and assigning weight to each stratum.

Earthquakes can cause significant disruption and devastation in communities. Especially, Iran is one of the countries with the most natural hazards, while earthquake causes most of casualties in this country for several reasons including the inappropriate construction methods, the improper physical growth and the lack of minimum necessary requirement. Mashhad is a city located in the northeast of Iran, the center and capital of Razavi Khorasan Province and the second largest populated city after Tehran. This city because of the high-density housing and the absence of urban development plans in worn-out context is facing a more serious risk. In this study a new hybrid method has been proposed for emergency location problem. First, a system dynamics model for the urban has been used to estimate the number of damaged buildings by focusing on construction and population subsystems. Second, the number of earthquake casualty has been estimated by the casualty estimation model of Coburn and Spence, while the output of system dynamics model is the most important inputs of this model. This method is implemented for different possible earthquake scenarios in Mashhad. Each scenario has been defined based on the length of active fault, the acceleration of activity and the greatness of the quake. Third, the Geographical Information System (GIS) has been used to specify the potential emergency location centers to cover the population. Finally, the location allocation model has been presented to locate the emergency location centers cover the survivors. The results of this hybrid model showed that we need at most 231 emergengency locations in the worst case and the minimum needed locations is 93.

Investigation morphological of rivers is essential for understanding current conditions and the potential of possible changes of the river in future. Measurement of the geomorphic indicators is one of the methods that can provide the extremely helpful for understanding these changes. In the basin of Talvar the existence of the beds changes has created the issue of research.

The area of the river basin Talvar in Kurdistan province, with a total area of ​​7,241 square kilometers, is geographically located between 48˚ 06  ́53 ̋   to 48˚ 12  ́ 48 ̋  East and 34˚ 54  ́ 20 ̋ to 36˚ 00  ́ 10 ̋ North. This basin is one of the sub-basins of Ghezel Ozan drainage basin, located at the southern end of the basin, east of Sanandaj.  The Talvar drainage basin is one of the sub- basin of drainage basin of GizilOzan that is located at southern part of this pool and north east of Sanandaj.  In this study, due to the wide extent of the basin, and also to get more accurate results, the basin of Talvar was divided into 15 sub-basins.

In this study some of important indexes are calculated which included: Sinuosity index (S), Shape basin index (Bs), Asymmetry factor of a drainage basin (AF), Drainage density index (P), Branching ratio index (BR), Time of concentration (Tc), confluence angles.
For the calculation of the time of concentration was used the Kirpich equation. For measurement of the confluence angles was used the Digimizer Software. At the end, data was implemented  model of Cluster Analysis in the SPSS software.

Check the value of the S: In the active tectonic areas river is in the form of direct line. If S is low and Closer to the number 1, is represents the tectonic activity in the area.  In the study area all of the sub-basins are equal to 1 or close to 1. So all are rated tectonic activity. The amount of S of sub basin number 12 is most of the others. Check the value of the Bs: The Bs value that is larger than the number 2 is indicating longitudinal basin.  Lower amounts of it is indicating weak tectonic activities.  So in the 1, 2,5,8,9,10,14,15 sub-basins, tectonic activity are high. 4 and 5 sub-basins are medium. 3, 7,11,12,13 sub-basins are weak.   Check the value of the AF: The AF indicator is one right way for determine tectonic tilting overload on the scale of the drainage basin. In a sustainable environment, AF should be about 50 that show the perfectly symmetrical drainage basin. So none of the sub-basins are not symmetrical. Check the value of the BR: BR in normal drainage basins is 3-5. So except for the sub- basin No. 1, all other sub-basins are normal. Check the value of the P: High density factor show active tectonic and the high sensitivity of the geological. The lowest value of the density related to sub-basin number 5. Check the value of the Tc: Usually the amount of Tc in a circular basin is shorter. But the stretches basin Tc is more.  Maximum value is related to the 1 and 5 basins. Minimum value is related to the number 3.  Check the value of the confluence angles: According to the calculations, 2 and 4 sub-basins has the highest average amount of angle and 5 sub-basin has the lowest.

Dendrogram corresponding to s shows that 12 and 13 sub-basins are single groups in terms of high s. and other basin are in a cluster. According to the dendrogram corresponding to BS 1, 8, 14, 15 sub-basins are in a cluster. 3, 12, 13 are in a cluster. 2 and 9 are in a cluster. And 4, 6, 7, 10, 11 are in a cluster. Dendrogram corresponding to AF shows that 1, 6, 14 sub-basins are in a cluster. 5 and 8 are in a cluster. 7 and 10 are in a cluster. 4 and 11 are single groups. And other sub-basins are also fitted up a single cluster. According to the dendrogram, 1 sub-basin is a single group Due to the high coefficient of divergence ratio. 14 and 5 that are longitudinal   sub-basins, are in a cluster. 2, 7, 15 are in a cluster and other sub-basins are in a cluster. The density dendrogram shows that 6 and 7 sub-basins that have a high permeability and multiple faults, are in a cluster. 5 and 12 are single groups in terms of relative poverty the density.  1, 4, 10, 13, 14 are in a cluster and other sub-basins are in a cluster. According to the dendrogram 1, 5, 15 sub-basins that are longitudinal sub-basins, are in a cluster. 2,3,10 are in a cluster. Number 7 is a single group. And other sub-basins are in a cluster. The average of confluence angles dendrogram shows that sub-basin 5 is a single group. 6 and 7 are in a cluster. 11,13,14,15 are in a cluster. 1, 3,8,9,10,12 are in a cluster. 2 and 4 are in a cluster. Accordingly, faults caused an increase collision angles. All indicators shows active or relatively tectonic in most sub-basins.

Heavy snowfall impacts the ski resort industry, outdoor activities such as snowmobiling and mountain climbing, homes, transportation networks, and vegetation. In the desert environment, such events as considered an unexpected climate hazard, due to incompatibility of human societies of these areas. The purpose of this study is a comparison of two widespread snowfalls during January 2008 and 2014 in the Kerman province, Using remote sensing and reanalysis data. Our results are presented in two main sections. First the temporal variation of the snow area over the Kerman province was investigated. In the next step, synoptically condition during heavy snowfall presented using NCEP/ NCAR data set. The results of the present study can increase our knowledge about the synoptic condition of heavy and widespread snowfall over arid environments.

The area of snow cover was calculated in order to determine the duration of snow cover on land surface. For this, we used from MODIS data. For analysis of synoptic reasons during heavy snowfall used from 2.5°×2.5° NCEP/ NCAR data. These data include the sea level pressure (SLP), air at the surface level, Geopotential height, Temperature of the upper levels, specific and relative humidity and uwnd and vwnd: zonal and meridional components. 

Snow cover area during January 2008 and 2014 During January of 2008 Iran has experienced a severe cold wave and more widespread snowfall, compared to the January of 2014. However, despite the severe cold wave of Iran, snow depth and area as well as the minimum temperatures of Kerman province were higher during January of 2014. The snow cover area was maximum at 16 and 17 January 2008 and 8 and 9 January 2014. Variation of daily changes in snow cover area represent important points. First, the snow precipitation was occurred during of the period, and second, temperature condition was suitable for persistence of snow cover on land. Therefore, our synoptic analysis is basis on the beginning and the end of the snow cover on the land.  The maximum snow depth at Kerman station during January 2008 and 2014 were reached in 13 and 23 centimeters, respectively. In addition, the minimum temperature at this station during January 2008 and 2014 dropped to -13.8 and -20.8, respectively. Undoubtedly, differences in the minimum temperature, snow depth and area (during 2008 and 2014), can be justified in patterns of pressure on a synoptic scale. 
Synoptically condition during heavy snowfall Mean of Sea level pressure during the presence of maximum snow cover (16- 20 January 2008) indicates the high pressure center over eastern parts of Russia. Following this high pressure, Kerman province is covered 1025 hPa isobaric. On the other hand, there is a similar pattern during 7-10 January 2014. The correlation coefficient between two SLP maps (R= 0.86) confirms this similarity. In addition to, such similarities can be seen at zero temperature isotherm which surrounds the Kerman province. There is a trough axis over the Kerman province, both on January 2008 and 2014.  However, the vorticity and relative humidity values are various during two heavy snowfall events. In the January 2014 the vorticity and relative humidity values were higher in comparison of January 2014.

The main objective of this study is an estimation of area under snow cover and synoptic condition during heavy snowfall in Kerman province.  During January of 2008 the land surface temperature in throughout the Iran is significantly lower compared to the January of 2014. However, the area and depth of snow, severity of cold-temperature is higher during January of 2014. Results show that, there is a similar pattern in the sea level pressure, the thickness of the atmosphere and surface temperature during maximum snow cover in Kerman province (16 - 20 January 2008 and 7- 10 January 2014). The southerly incursions of Siberian high-pressure systems (1015 hPa over study area), 0℃ Isothermal curve and thickness of 5500 geopotentioal height was seen during either two event over the study area. The correlation coefficients between Geopotential heights at different levels is stronger in January of 2014 in comparison to January of 2008. In addition, Positive values of vorticity and relative humidity conditions was better during January 2008. All these factors caused that the snow depth and spatial distribution of snow cover were higher in the January of 2014 compared to January of 2008. This study confirms that the remotely sensed products are valuable in the synoptic climatology study.

The Liveable urban environment is a desirable place for life, work, and entertainment, which meets the current and future needs of citizens. One of the most important challenges of Liveable on urban spatial is urban physical and environmental problems that affect the future of future generations and their quality of life. This paper analyzes and predicts the role of physical-environmental indicators in creating Liveable space in Zanjan city by analytical method. Fieldwork and library studies have been used to collect information. The statistical population consisted of residents of Zanjan, which was selected by Cochran sampling method, 384 samples. To analyze the data, the fittest test, exploratory factor analysis and structured / cross-flow futures research were used with SPSS and MIC MAC software. According to the results of the research, considering the fact that Zanjan physical-environmental management system tends to be unstable, however, the components of "Suitable prices for housing," "industrial pollution," "the proportion of public use to the needs of citizens," "the situation of waste tanks," "street flood security", "natural beauty of the neighborhood", "vegetation around the cities" And strong. And these relationships are mutually linked to the "affordable housing" component. As a result, in order to Liveable the urban space in Zanjan, it is first necessary to develop community-based programs around housing, the beauty of the city and neighborhoods, pollution, and refinement of the needs of citizens. Ultimately, in order to achieve the citychr('39')s Liveable goals, attention must be paid to controlling the citychr('39')s physical growth and development, the expansion of the public transport fleet, and attention to internal development.

Annual precipitation forecasting usually guarantees success in sustainable management of water resources and watersheds in cases like determination of rain-fed and water cultivation area and water resources consumption planning. Although precipitation does not follow a specified pattern; however, it has a correlation with some climatic parameters. If these parameters were easy to find, simple applicable models could be developed to predict annual precipitation. One of the simplest methods for predicting annual precipitation is regression models. The block box models such as Artificial Neural Network (ANN) has also been used for precipitation forecasting.  This study was an attempt to predict annual precipitation using some climatic parameters by multiple linear regression and ANN models.  

Chaharmahal-Bakhtiari and Yazd provinces are located in the southwestern and central part of Iran with semi-arid and arid climate, respectively. Mean annual precipitation of these two provinces are 560 and 110 mm, respectively. Meteorological data of the weather stations belong to 2001-2011 in Chaharmahal-Bakhtiari and 2003-2013 in Yazd province; respectively, were analyzed. Various parameters were calculated for predicting annual precipitation using long-term daily precipitation and temperature data of the meteorological stations. Among the parameters, total precipitation in the first half of the water year (R6m, mm), time to 47.5 mm cumulative precipitation since the beginning of autumn (t47.5, day), long-term mean annual precipitation (Rm, mm), average summer temperature of the preceding water year (Tsu, °C) and average temperature of preceding summer and current autumn of water year (Tsu.au, °C) that had a high correlation with annual precipitation, were used in multiple linear regression (MLR) models and artificial neural network (ANN) techniques. normalize mean square error (NRMSE) and degree of agreement (d) were used to evaluate accuracy of the models for predicting annual precipitation.

Results showed that the obtained MLR models were significant at a probability level of less than 0.01. Results also showed that both methods (MLR and ANNN) could accurately estimate the annual precipitation. Evaluation and verification of the models with NRMSE values less than 0.3 and d values greater than 0.8 confirmed the performance of the models. The best topology of the ANN network in the study was a multiple layer perceptron network with one hidden layer and two neurons and sigmoidal activation function. The findings of the study support the fact that higher temperature in summer and autumn was a sign of higher and lower annual precipitation in Chaharmahal-Bakhtiari and Yazd Provinces, respectively. Besides, higher time period to 47.5 mm cumulative precipitation from the beginning of autumn implies fewer amount of annual precipitation.  

This study showed that annual precipitation could be predicted by MLR and ANN methods in both arid and semi-arid regions with acceptable accuracy. According to the results, a rainy water year will be expected continuing a warmer summer and autumn in Chaharmahal-Bakhtiari Province; however, there will be a dry water year in Yazd Province followed by these conditions. Furthermore, if 47.5 mm cumulative precipitation takes a longer time since the beginning of autumn annual precipitation will decrease.