فصلنامه فضای جغرافیایی
پیاپی 77 (بهار 1401)

Landslides and slope instability are major hazards to human activity, which cause damage, this instability and hazard are potential and damaging phenomena, our country is mainly mountainous topography, tectonic and seismic activities. The high humidity, diverse geological and climatic conditions have created most of the natural conditions to create a wide range of landslides. The purpose of this study was to identify the effective factors in landslide generation and identify potential landslides in Alamutroud basin in Qazvin province using logistic regression method. In this study, landslide distribution map of the basin was prepared by studying aerial photos and field surveys using GPS and satellite imagery. Eight effective factors including slope, slope direction, sea level rise, distance from riverbed, land use, lithology, distance from fault and drainage network density were used and then processed using Matlab software. , ARC GIS, IDRISI and EXEL. According to the results, 58.26% of the catchment area is in the low and very low risk zone and 17.44% in the high and very high risk area. Also the factors of height and distance from the ranch have the highest scores in landslide creation. Also the model validation indices including pseudo ROC and R_square ChiSquare were calculated /957 -2511/283 and/ 3518  respectively which have acceptable validity.

Temperature is one of the main factors influencing urban planning because it guides the type of facilities available in cities and even determines the urban structure, shape and texture. On the other hand, increasing vegetation cover is one of the most effective strategies to reduce urban climate impacts. In the present study, the land energy balance algorithm was used to achieve land surface temperature and the soil vegetation index of Nazarabad city was used to estimate plant poisoning. For this purpose, Landsat satellite images (TM-OLI), years (2000-2019) were used. First, the relevant images were obtained and the necessary preparations were made. Then, the object-oriented classification was performed. Linear regression analysis was used to estimate the correlation between surface temperature and vegetation. Surface temperature results showed that vegetation areas such as agriculture and rangelands averaged 32 and 34 ° C for 2000 and 2019, respectively. However, during these years, vegetation-free areas such as urban and wilderness areas that were devoid of vegetation have averaged 36 and 39 degrees Celsius, indicating the effect of vegetation on surface temperatures. Also in estimating the correlation between vegetation and land surface temperature, it can be said that there is a strong correlation between the data. Independent variables have been explained which show high value and the model is significant with 0.95% confidence and is able to express changes based on available data so it can be concluded that this model has high accuracy for this study.

In order to identify and classification of synoptic patterns of snowfall in Guilan province was used NCEP/NCAR reanalysis 1 database. For this purpose, 253 snowfall days from 1998 to 2018 (20 years) were determined and then 500 hPa geopotential level were used to classify patterns by PCA method. In this study, an environmental to circulation approach was used. The results of the data classification showed that four European high pressure patterns, bipolar blocking, Siberian and North Caspian Sea dynamic-thermal high pressure and Mediterranean cyclones control the area's snowfall days. In the first three patterns, the arrangement of the western wind waves and the amplification of the high pressure through the convergence of the air flow in the mid-atmosphere are considered to be obvious and the air subsidence in this level increases the vertical upward extend of high pressure to higher levels. Thus the above three high pressures and Mediterranean cyclones are also dynamic and this is one of the prominent features of synoptic patterns of snowfall days.

Economic problems are one of the main issues and problems in rural development and planning of the country. As can be seen in most cases, rural capitalists are reluctant to invest in rural areas. Accordingly, the goal of this research the reasons for this are the unwillingness of returning capitalists with rural roots to their rural homelands and investing in the countryside. For this purpose, Carpet weavers with rural roots residing in Mashhad were selected as sample. The research method was qualitative and the data were collected through questionnaires and interviews. In the following Carpet weaving villages were selected in the towanty and after visiting the villages that have had the most experience in carpet production (Pyweh Gan, Bulgur and Kazemabad (. The capitalists in this industry were identified and using the snowball sampling method of 25 rural activists were selected as sample. Also exploratory factor analysis and t-test were used to analyze the findings. The results showed that the averages were higher than the average this is indicative of the widespread problems facing the industry in rural areas. Also the results of factor analysis showed Factors such as lack of marketing and access to the sales market, lack of necessary infrastructure, and lack of advanced technology in the villages are factors affecting the lack of investment in the village.

Marls form the weakest part of geological formations that are highly erosive. Sustainable action in soil stabilization is biological operations. The dense cover of Pasture rangeland species in some areas of Marl has caused soil stability in these areas. It seems that some of the physical and chemical properties of marls play role in creating such a cover in areas covered by marl formations. This research was conducted with the aim of carefully and systematically study of plant species and determining their site needs and protective role in three eastern, southern and western regions in Ilam city. For this, 30 marl deposit samples were collected from three ranges and physical and chemical tests were performed on its. Botanical studies were also performed using repeated field visits and plot establishing at 180 locations, and plant samples were identified after transfer to herbarium. Results showed that, giving the stratigraphy of Marl Gorpi, Pabdeh, Gachsaran and Aghajari formations, sediments of these three regions in terms of salinity (EC), specific gravity (BD), sodium (Na +) and Soil saturation percentage (SP) and some physical parameters such as gravel, sand and silt particles have significant differences which R2 has shown significant statistical effect of soil physical and chemical properties on plant cover type. This difference could be as one of the effective factors in the diversity and difference of vegetation grown in three areas. In this research, the site need of plant species compatible with marl type and soil protection role of each of them in eastern, western and southern regions of Ilam city has been introduced.

Land surface temperature is an important indicator in the study of ground energy balance models on a regional and global scale. Due to the limitations of meteorological stations, remote sensing can be a good alternative to estimating surface temperature. In the present study, the relationship between different land uses and ground surface temperature in Kosar city and spatial autocorrelation has been investigated using Moran index. Landsat 8 (OLI) and Landsat 5 (TM) satellite images were used for this purpose. The present study was carried out in four main stages: a) preparing images for 1987 and 2015, b) making the necessary predictions, c) preparing a classification map using the object-oriented method, and d) extracting the earth's surface temperature with Separate window algorithm. The results showed that dryland and rangeland agricultural uses in 1987 and 2015 have higher temperatures than other uses, due to the dryness of selected agricultural products in the selected period (June), which caused the temperature to rise. Is. In contrast, the use of water areas due to their high heat capacity in these years have the minimum average temperature. In addition, hot and cold clusters of Kosar thermal islands were extracted using the hot spot analysis index (Hotspot). Finally, the analysis of spatial autocorrelation with global Moran indices showed that the surface temperature of Kosar city has a spatial structure and is distributed in the form of clusters.

The aim of the study was to investigate the conditions of atmospheric circulation patterns in the very wet months of Syria. By calculating the standard precipitation index (SPI) and using the precipitation data of 16 Syrian synoptic stations in the statistical period of 2016-2017, very wet months were identified. Then, combined maps of sea level pressure parameters, geopotential height and wind components at 850, 700, 500 and 250 hpa levels, as well as specific humidity at 850 level and 700 hpa level omega from NCEP-NCAR gridded reanalysis data were produced and were used to study the synoptic atmospheric patterns of very wet months. The findings show that formation of a deep trough is the most important model for creating very humid Syrian months, which is centred almost between eastern Turkey and western Egypt, and Syria is located in front of this trough. This trough, especially in the middle and upper atmospheric levels, causes to falling cold air on the eastern Mediterranean. The moving polar trough pattern at 700 and 500 hpa levels towards lower latitudes had caused the aforementioned advections. Formation of negative values of omega and rising air currents, along with southwest winds at sea level and other levels over Syria, have caused above-average rainfalls.

Atmospheric-oceanic macro scale phenomena have caused much of the worldchr('39')s climate change. Atmospheric-oceanic macro scale patterns are a suitable variable for predicting climatic elements, especially snowy days. In Ardebil province, light, semi-heavy and heavy snowfalls, in addition to local factors, are also related with Large-scale Atmospheric-oceanic circulation patterns. Forecasts for snow days in Ardabil province can provide by determinatiom of relationship between snowfalls and macro-scale phenomena of atmospheric-oceanic circulations in this province.

In this research, by snow days data of synoptic stations of Ardabil province as sample of climate of North West of Iran, statistical characteristics of snow days of this province was studied. The statistical period used in Ardebil, Khalkhal, Meshkinshahr and Pars Abad synoptic stations were 42, 31, 22 and 33 years from 1976, 1987, 1996 and 1985 to 2017, respectively. Independent two-sample T-test was used to compare the mean snow days of the stations under study. In this research, In addition to descriptive analysis, spearman correlation, order 6 polynomial and linear trend, multiple regression analysis based on backward method for determine of variability of snow days in Ardabil province by using 27 Large-scale Atmospheric-oceanic circulation pattern of Atlantic and Pacific oceans. Indicators of macro-scale atmospheric-ocean circulation phenomena used in this study were obtained from https://www.psl.noaa.gov/data/climateindices  which include: SOI, SENSO, EOF , MEI, NINA1, NINA3, NINA4, NINA3.4, ONI, PWP, TNI, EPO, NOI, NP, PDO, PNA, WP, AO, AMM, AMON, ATLTRI, CAR, NTA, TNA, TSA, WHWP and NAO.

The results showed that there is an average of about 35 days of snow at Ardabil station on an annual scale. The number of snow days in January, February, March, December, as well as annual scale, has an almost normal distribution. In Ardebil station, the relative normality of the distribution of the number of snow days on an annual scale and its similarity to December to March is due to the high share of snow days in these months in the composition of the number of annual snow days in this station. The coefficient of variation of most stations is also higher in May and October than in other months. Result of linear trend of snow days variability in Ardabil synoptic station shows a slow increase of snow days of this station. Snow days in most of the stations under study had significant correlations at 1% and 5% error levels by each there, which reflects the prevalence of snowfall at Ardabil province stations. In Khalkhal, Meshkinshahr and Parsabad stations, annual decrease in number of snow days is observed in annual scale. The 6th-order polynomial model predicted snow days in Ardabil station rather than other models. T-test results of two independent samples for snow days of the studied stations showed that significant value in Levenechr('39')s test was greater than 0.05, so the assumption of equality of variances cannot be rejected. The significant value of T test for equality of means indicates that in Ardebil and Khalkhal stations, the assumption of equality is confirmed, but in Khalkhal and Parsabad stations the assumption is rejected. At Parsabad station, the number of snowy days was significantly inversely correlated with the Atlantic oceanenic-atmospheric patterns. Results showed that the snowy days in synoptic stations of Ardabil province have a higher and more significant correlation with atmospheric-oceanic patterns of the Pacific Ocean than atmospheric-oceanic patterns of the Atlantic Ocean. At Ardabil, Khalkhal, Meshkinshahr and Parsabad stations, 48%, 90%, 99% and 49% of the changes in snowy days were explained by the atmospheric-oceanic patterns of the Atlantic Ocean, respectively. The results showed that in Ardabil station, NINO3.4, ONI, TNI and NINO1+2 patterns, in Meshkinshahr station, NP pattern and in Parsabad station, NEI, PNA, NP, NINO3.4 and NINO1+2 patterns, explained the highest percentage of changes by the number of snowy days of these stations with atmospheric-oceanic patterns of the Pacific Ocean. The results also showed that in Ardabil station, WHWP, NTA and AMM patterns, in Khalkhal station, WHWP, TSA and AMM patterns, AMO, CAR and TNA, in Meshkinshahr station, WHWP, ATLTRI, AMM and TNA patterns and in Parsabad station, The AMO pattern explained the highest percentage of changes by the number of snowy days of these stations with atmospheric-oceanic patterns of the Atlantic Ocean

Among synoptic station of Ardabil provinec, Khalkhal station has more significant correlation with Atmospheric-ocemic patterns of Pacific ocean. In Ardabil provinec, Atmosphoric-oceanic patterns of Atlantic ocean, determine variability of snowdays of Khalkhal and Meshkinshahr synoptic stotions more than Ardabil and Parsabad synoptic stations. The results of T-test of two independent samples showed that the difference of mean of snow days in all the studied stations in the two study periods were not significantly different from each other and it can not be claimed that the number of snow days in the studied stations has been affected by climate change. Distribution of correlation values of snow days in the studied stations with Atlantic and Pacific atmospheric patterns showed that in most of the studied models, correlation of snow days with selected patterns increased from south to north of Ardabil province.

One of the main concepts studied in geographical sciences is geographical space. Each of the different dimensions of space forms a subject in this science field. Humans have been creating artificial changes in the geographical environment for many years by creating built environments. One of the crucial dimensions of space is the physical dimension. As a built geographical space, the university has a conspicuous role in developing students’ individual and social personalities. Many of students’ interaction emerges on the campus. According to spatial justice, women should have an equal right to presence in public spaces. One factor diminishing their presence is the improper design and non-responsivity of the environment to their needs. This study aims to provide a framework to improve the status quo of university campus open space in Iran and increase spatial justice by creating equal presence opportunities and answering these two questions: What is the difference between the needs of men and women concerning the environment? And what are the Factors of a responsive environment to meet the different needs of the two sexes? For this purpose, four areas of “The factors of public space quality,” spatial justice,” “spatial rights of users,” “sex and gender-based needs” were extracted from the existing literature and examined by qualitative content analysis. After matching the texts and finding common internal meanings, analyzing and separating, integrating them, and obtaining the fundamental factors, CVR and CVI questionnaires were sent to ten experts to check the necessity and relevance of each obtained factor and criterion. After performing the calculations according to the experts, the necessary corrections were made and a new conceptual framework in three general physical, functional, and perceptional dimensions and in the five components of “security,” “accessibility,” “comfort,” “diversity,” and “aesthetics,” along with criteria and sub-criteria; as the “results” of research; Explained. This research helps architects, designers, planners, and policymakers design an environment that responds to the needs of all students. As a research agenda, this framework could also be the starting point for further empirical research for future researchers.