Journal of Spatial Analysis

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. Caspian Sea south coast future climate change estimations through regional climate model
many physical of the procedures related to climate change are not perceived thoroughly. Scientific knowledge used to show those procedures completely, and to analyses forecasts is so complex, since most current studies about climate physical model have been done through semi experimental and random models and most of the current analysis techniques are still going through early stages. One of the important aspects of this study is modeling physical procedures of sea level rise geographical pattern, which is used practically for SLR threat evaluation of special geographical location, meaning Caspian basin. Since Caspian basin is a closed sea, it is heavily influenced by climate change and meanwhile is changing due to physical level and environmental change. It is necessary to define Caspian coast climate change possibility with specific focus on climatology and meteorology fine data, also to define the scale of sea level fluctuations for the sake of exact planning in different fields. This study aims at presenting a new dynamic method, via using an integrated model system named SIMCLIM, which can clarify SLR satellite changes well.
According to scientific examination existing in this study, based on scatter scenario 4.5 RCP and 8.5 RCP for the following years, until 2100, temperature and precipitation change proposal have been presented. On one hand, Caspian coastal climate change analysis and estimation were based on climate patterns and water flows in the form of regional climate statistical model in order to simulate and forecast, on the other hand surveying chronological changes of Caspian sea coast slope with satellite height measurement was done to measure sea surface height fluctuations The present study has used SIMCLIM model for the first time in order to clarify Caspian sea level changes, elements, and effective climate reasons, all simultaneously in one project. The project base is according to coastal systems and procedures. Coast line shore change simulations are based in Bruun law.
In future the frequency and intensity of extreme events temperature and precipitation will increase. Extreme events illustrate changes in extreme temperature and precipitation measures, in comparison with the base period of 1981-2010 which convey precipitation sum or the temperature beyond 95 percentile of base period. Temperature and precipitation coefficient of variation for the whole Caspian basin is positive and it varies from 25 to 88 percent. A disordered pattern is dominating south basin of the sea. Sea level changes, considering vertical earth movements, which is 2 mm in a year, resulted from subsidence of Caspian pit seabed have been obtained for both scenarios. In general, annual sea level average while ignoring seasonal changes, is increasing consistently and it was calculated 1.22 cm each year according to high estimation procedure in scenario 8.5 RCP and it was 0.93 cm based on scenario 4.5 RCP. Predicted results were compared with real results of base20-year period from 1995-2015. Base period results in three levels of sensitivity of low, mid, high shows 8.4, 10.1, and 11.8 cm rise; after comparing them with model forecast results, meaningful coordination at the level of 95 percent was found out. In both scenarios, all over the Caspian shoreline water advance and destruction will exist. In the worst case scenario of 8.5 RCP of 2030, current coast will decrease about 23 meters and in 2060 it will be about 53 and in 2100, there will be 117 meters advance towards land.
Precipitation and temperature percent for 2030, 2060, 2100 will change increasingly. Spatial variability and annul coefficient of variation are various in different regions. North, western north, eastern north and east will include the least temperature fluctuations, and the highest percent of precipitation with the highest coefficient of variation all convey chronological period precipitation distribution with disordered accumulation and more local difference in this region in comparison with other regions. Then Caucasus mountainous region will have the highest increase in precipitation with a suitable scatteredness, during a year. The southern part of Caspian Sea will be with the highest increase in temperature and the least amount of increase in precipitation in percent. High coefficient of variation in this area illustrates abnormal and disordered pattern on the threshold of precipitation for both scenarios.
 fluctuations in sea level based on subsidence of Caspian pit seabed was calculated.In general, average annual sea level is increasing which will be 1.22 cm, per year for scenario RCP 8.5 and 0.93 cm for scenario 4.5. Due to incapability of world community in decreasing releasing greenhouse gases, it is expected scenario that 8.5 RCP to come to reality.
 Caspian Sea shoreline is influenced by water advance and destruction. The difference between two scenarios in 2060 will be 3 meters and in 2100 will be 12 meters. Instinctually, such advances in coasts with less depth and less slope will be more. This study suggests that coastal changes are inevitable. However, this region inhabitant owns no systems or no systems have not yet developed to aid them be able to adopt with the climate changes.
 
Keywords: Sea level rise, South Caspian basin, Extreme event, Coefficient of variations, shoreline.

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Assessing the Homogeneity of Temperature and Precipitation Data in Iran with Climatic Approach
 
Extended Abstract:
Qualitative evaluation and validation of atmospheric parameters such as precipitation and temperature are the most important condition for statistical analysis in climatic and hydrological researches. In addition, the meteorological and climatological data have a crucial role in transportation, agriculture, urbanization and health services.  Therefore, it is clear that using wrong data source for atmospheric investigations is the first hazard in natural hazards analysis. This study aimed to investigate the homogenization of minimum and maximum temperatures and precipitation data for 36 weather stations over different climatic classes in Iran. The Standard Normal Homogeneity Test (SNHT), (Alexanderson and Moberg, 1997), Pettit test (Pettit, 1979), Cumulative Deviation test (Buishand, 1982) and Worsley’s Likelihood Ratio test (Worsley, 1979) were carried out to study homogenization of minimum and maximum temperatures and precipitation data (1966-2015). The results revealed that 91.5 % and 88.5 % of minimum and maximum temperatures data, respectively, were in non-homogenized category. Although, Isfahan, Saghez and Gorgan for minimum temperature and Bandar-e Anzali, Sharekord, Kashan and Saghez for maximum temperature showed a homogenized condition with 5 % level of significance. The results showed most of the weather stations (28 out of 36 stations) had homogenized precipitation data. Even though, seven stations including Birjandd, Kerman, Kermanshah, Saghez, Sanandaj and Tabriz had homogenized precipitation data. The Urmia weather station was in doubtful class. That is precipitation data of Urmia weather station were homogenized by two tests results and were non-homogenized with other two tests of homogenization. The spatial distribution of trend variations of minimum temperature average was between -2.8 to 2.8 degree Celsius over the country. Moreover, maximum and minimum variations of minimum temperature occurred in northeast and northwest of the country, respectively. There were a significantly increasing trend (p<0.01) in most of the regions. The results also indicated that the significant variations happened for maximum temperature in most of the weather stations, mainly in northern half of the country. The minimum temperature jump was mostly found in 1985, 1994 and 1998 years during the study period (1966-2015). The maximum variations of minimum temperature were in Mashhad, Shahroud, Ahvaz, Yazd and Semnan weather stations with 2.8, 2.3, 2.2, 2 and 2 degrees Celsius, respectively, jump for above mentioned years during 1966-2015. In addition, the minimum change in minimum temperature was occurred in Birjand, Urmia and Bandar Abbas with a jump of 0.6 degrees Celsius. It should be mentioned that, unlike other stations, the Khorramabad (Lorestan Province) and Fasa (Fars Province) had a decreasing trend for minimum temperature. It changed from 10.3 to 8.3 and from 11.8 to 10.2 degrees Celsius in Khorramabad and Fasa, respectively. The results showed that the commencement of maximum temperature jump for most of the weather stations happened in 1998 with 1.1 degrees’ Celsius change. According to our study, a remarkable decrease in precipitation data was occurred in west and northwest of the country. There was a depletion of 80 to 150 millimeters from 1998 in Tabriz, Sanandaj, Saghez and Kermanshah weather stations during study period (1966-2015). Besides, 25 to 45 millimeters reduction in precipitation was found in south and southeast of the Country which has arid climate including Birjand (South Khorasan Province), Zabol (Sistan and Baluchestan Province) and Kerman. It was revealed that the variations of minimum temperature were larger than maximum temperature which was in agreement with results obtained by Rafati and Karimi, 2018. The results showed that the start of increasing maximum temperature in most of the weather stations was in 1998. It could be due to increasing the global temperature which is in accordance with results found by Steirou and Koutsoyiannis, 2012. The results revealed that about 80 % of precipitation data of weather stations were homogenized. These results were in agreement with results obtained by Hosseinzadeh Talaee et al., 2013. The results indicated that tests of homogenization for minimum and maximum temperatures and precipitation data could use in different climate over the country. Therefore, it could not allocate a single test to a particular climate type. In conclusion, it should be noted that before any analysis pertaining to environmental hazards, the calibration and maintenance of the weather instruments should be carried out periodically. In addition, the metadata and station history for relocation of the weather station should be checked. The relocation can create great changes in meteorological parameters due to elevation, latitude, longitude and land use/land cover differences between two sites.
 
Key Words: Homogeneity tests, Climate Data, Weather Station, Metadata
 
 
 

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ite selection for Temporary Earthquake Shelter Compounds, Using Analytic Hierarchy Process and Weighted Linear Combination based on GIS; Case Study: Shahrood
 
Abstract
Natural disasters are unpredictable and unavoidable and their occurrence in human settlements has led to catastrophes in many cases. Therefore, it is necessary to prepare prior the occurrence of these events. A prompt response can be a solution to this goal. As long as assurance is provided to the affected population that there is no lack of assistance and facilities, their ability to return to pre-disaster conditions and recovery will be increased. Selecting the right accommodation according to the needs of people after natural disasters, as well as planning to meet the needs of the victims, not only reduces risks and expedites recovery operations during reconstruction, but also strengthens the protection structures and advances the safety aspects of communities prior to any kind of incident. Increasing concerns arising from high occurrence of natural disasters, especially earthquakes, and witnessing the unpleasant consequences, will emphasize the need for proper habitation conditions and facility provision. Iran is a country that is prone to disasters. In fact, no country in the world is immune to natural disasters. In this research, urban areas of Shahrood located in Semnan Province, have been studied with regard to seismic potential and proximity to the southeastern part of Alborz Mountain and Shahrood’s faults as a sample for selecting appropriate post-earthquake shelters. The overall purpose of this research is to propose a decision making process for efficient and safe spatial planning in the wake of crises. In the first step, the structural vulnerability of buildings in terms of foundation quality and their vulnerability measures is estimated at 24% of the city, which is equivalent to 12778 buildings prone to destruction, even facing a mild earthquake. After analyzing the possible damage to the city, according to the average household size of 3.43 people in Shahrood, 43829 people are estimated to be homeless. The amount of space needed to accommodate these people, with an estimated per capita of 30-45 square meters per person, was estimated at 132 to 198 hectares, which could be used in a few distinct and scattered spaces. After determining the area needed for settlement, the criteria influencing the location of temporary shelters were identified based on scientific literature and analysis of previous experiences. According to these studies, the criteria for influencing this concept are classified into nine groups including access, location, cultural, economic, compatible and incompatible neighbors, infrastructure conditions, land quality as well as space area. The subsets of these nine criteria can be categorized into two groups: constraint factors and classification possibilities. Factors such as distances from faults, high voltage electric power lines, vulnerable zones, gas stations and chemical storage facilities are known to cause limitations. The concept of the facility in this research, in addition to proximity to residential areas, main roads and storage depots, includes access to compatible applications, medical centers, security centers, fire departments and outdoor spaces; hence it is necessary to accommodate people at the minimal distance from these facilities. Parameters such as area, surface water, infrastructures and available energy sources are some of the criteria that need to be measured in terms of their quality in proposed options and decisions are to be made on the basis of their existence and accuracy. Since each parameter has a different effect on the location of temporary accommodation therefore, the list of priorities is sorted accordingly. In this article, a methodology for locating shelter after an earthquake has been recommended by using hierarchical analysis, weighted linear combination and GIS. In this multi-criteria decision-making process, the weighting process was performed on each parameter by paired questionnaires that were provided to 40 experts, and analyzed according to the principle of hierarchy (AHP) and arranged in Expert Choice software. Then, all of the data layers in GIS software were combined with WLC method according to the criteria and standardization. The Geographic Information System (GIS) has been used as one of the most useful tools in allocation and land use planning. To analyze the data in the software, after converting the data into the Raster structure and classifying the layers in appropriate categories and in accordance with the functional radius, a conclusion was made in the Arc GIS environment. The output, obtained by overlapping the collected items, is a list of land plots suitable for post-disaster shelters, sorted according to the aforementioned priorities.
 
Keywords: site selection, temporary sheltering, AHP, WLC, GIS
 
 

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Analysis and Measurement of Environmental Resilience of Villages in Gorganrud Watershed against Flood (Golestan province, Iran)
 
Abstract
Environmental hazards are inevitable phenomena that always place serious risks on the development of human societies, especially rural development. In the recent years, however, significant changes have been made in crisis management approaches, and the prevailing view has shifted from the "reduction of vulnerability" approach to "resilience improvement". Resilience is a new concept often used in the face of unknowns and uncertainties. Therefore, along with this change of attitude, it is important to examine and analyze natural hazards in terms of resilience. According to global statistics, floods, as one of the most devastating natural disasters, have caused the greatest losses and casualties to human settlements, which is true both in our country and in Golestan province. Investigations show that only in the statistical period of 1991-2014, 106 rainfall cases have led to the occurrence of floods in this province. These floods have damaged natural resources, the environment and the prevalence of environmental pollution; In addition, other natural and human factors have contributed to the heightened risk of flood damage. But if it was planned for the restoration of villages, then the damage could be reduced. Therefore, this research was conducted with the general purpose of determining the relationships between environmental factors and factors of rural communities of Gorganrud watershed on their resilience and numerical values. Finally, the residual spatial analysis of rural limited settlements was studied. Accordingly, the research questions are as follows: a) What is the relationship between environmental factors and factors in the villages of Gorganrud watershed in Golestan province with the resilience of the communities living in them in the face of flood? b) What are the resiliency values ​​of these communities in the environmental dimension and which zones? This is an applied research with descriptive-analytical method. A library of researcher-made questionnaires was used for collecting data using library resources. The statistical population consisted of 106 villages with 22,942 households. First, 31 villages were selected by cluster sampling. Then, using Cochran formula, 318 families were selected as sample size and selected by simple random sampling method. Also, for assessing the validity of the questionnaire, using Delphi collective wisdom methods, it was determined by using historical studies and opinions of experts in rural areas. The reliability of the questionnaires was also determined by using the Cronbach's alpha coefficient in the pre-test method. The value for the household questionnaire was r_a1=0.841 and r_a2=0.862, respectively. All steps for statistical analyzes have been performed by Excel and SPSS software. Additionally, the development of mapping, risk-taking, risk and resilience was also done with the help of ArcGIS software and the weight of each criterion was determined by the Super Decision tool; Then, using the weighted and linear overlapping methods, each of the sub-criteria of the main indexes was multiplied in its weights. The study area is divided into two distinct sections in terms of geological and geomorphological structure. The southern and eastern parts of it are the ripples of the eastern Alborz mountains, which are taller in the southern part and extend along the east-west direction. Also, the northern part of the studied basin is the Gorgan plain, in which the main branch of Gorganrud flows from east to west and all branches of the south and east are drained. Following the general slope of the main branch and its long-standing walls in the mid-east, it is usually not flooded; but as far as the west is concerned, its slope is very low and one of the flood plains is considered as the basin. The results of the research show that there is a significant relationship between the environmental factors of the studied basin villages and the resilience of the communities inhabited by them in the face of floods. Also, the average environmental resilience of the whole region was lower than the average (2.76 average), rural households in the sub-basins of TilAbad and ChehelChai with an average of 3.24 and 3 had relatively good environmental resilience, But most of the rural households in the sub-basins of Ghurechai and Lower of Gorganrud, Mohammad Abad-Zaringol, Madarsoo and Sarisoo, with an average of 2.89 to 1.85, had a poor environmental resilience. In addition, According to the flood risk resilience map, it can be said that of the total 31 sample villages studied, about 29 percent of sample villages have "medium upward" resilience in facing flood risks; conversely, most of these villages (71%) also have relatively low degree of resilience. Also, comparing the findings of this study with the results of most other researches, such as the studies of Olshansky and Kartes (1998) regarding the necessity of considering the environmental factors of settlements, observing the necessary environmental standards and the necessity of using proper land use management tools to reduce risk hazards and improve resilience, Center of Emergency Management Australia (2001) on the need to consider the state of the infrastructure, including the level of communications and accesses, biological conditions, including the status of pollution, as well as geographical characteristics, such as distances and proximity, climate, topography, as well as the general results of studies by Rafiean et al. (2012) in special selection of the most suitable model of resilience based on the combination of carter and socioeconomic model due to the simultaneous attention of this model to its geographical features and its comprehensiveness, as well as attention to the local communities' participation, Rezaei (2010), Shokri Firoozjah (2017) and Anabestani et al. (2017) Regarding the low value of the calculated population, the resiliency number of the society is consistent and consistent with the lack of attention to infrastructure issues, locations, etc., which is below the baseline (3). As a result, all of the aforementioned components of the resilience of inhabitants of sample societies have been affected by its environmental dimension, which is often due to insufficient attention and insufficient handling of them, which reduces resilience of rural residents to flood risks.
 
Keywords: Environmental hazards, Flood, Vulnerability, Resilience, Spatial analysis, Golestan Gorganrud basin.
 

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The effect of Urban Development on Watershed Hydrological Properties (case study: Tajrish Watershed)
Throughout the human history, societies and rivers have been closely linked, so that the human civilization began from the riverside (Stevaux et al. 2009 (. The quantitative and qualitative characteristic of river is vulnerable to land-use changes (Kang et al. 2010). Natural and urban watersheds are influenced by the rapid land use change due to urban development (Furusho et al. 2013). Hence the importance of land use as an environmental variable have made its changes as a major issue in environmental changes and sustainable development) Verburg et al. 2009).
The development of urbanization and industrialization of cities and communities have undesirable effects on the hydrological response of watersheds. It increases the magnitude of runoff and contamination, reduces the base flow and the groundwater recharge. Hence, urban authorities are urged to pay more attention to the environmental damaging effects of the urbanization process and the increase of construction. In this regard, attention should be paid to the effect of type of land cover and land use on urban runoff and hydrological changes in surface flow. Tehran as the largest metropolis in Iran has ascending trend of land cover and land use changes due to the growing population.
In this research, the effect of urban development on the hydrological characteristics of the Tajrish sub-watershed (in Darband watershed) located north of Tehran has been investigated. Results of this study indicated that the river Darband is exposed to hydrological hazard due to human need for space and land use and land cover changes. The studied area is affected by decreasing pervious area, increase of runoff coefficient, and change in water quality parameters.
Darband River watershed consists of two streams of Darband and Golabdareh which are considered as the major rivers of the Tehran-Karaj Basin. This river originates from the mountains of the Tochal located in northern Tehran. The catchment area of Darband River in the studied area is 39.88 square kilometers.
In this study, aerial photos of years 1345, 1358 and also   and IkONOS images in year 2011 were used to detect the changes in land cover and land use in the Tajrish watershed. Pas-Ghale sub-watershed in upstream of Tajrish was selected as benchmark since its land use doesn't affected by human interventions. SCS-CN method developed by the United States Department of Agriculture (USDA) was used to estimate the quantitative changes in surface storage and runoff volume. Man-Kendall test was used for temporal trend detection of discharge and chemical parameters of surface water and also. The change of water type was identified annually using the Piper diagram in the aqQA software. Frequency analysis was carried out for peak discharge data using the weibull’s empirical method.
During three considered periods, the curve numbers (CN) and runoff coefficient (C) in Tajrish watershed significantly increased. Significant trend was also observed for the chemical parameters of surface flow in Tajrish. While the surface storage and initial abstraction ratio (λ) indicate decreasing trend.  Relationships of CN and λ with rainfall depth (P) were also computed for both studied watersheds. According to the Piper diagram, the distribution of ions in the cation diagrams at both Maghsudbeik and Pasghaleh stations is generally more directed toward sodium. In the triangles of anions, both of the stations studied tend to show more calcium biocarbon content. Presence of sodium ion in the surface water is due to igneous formations in the watershed. The surface water in Pasghale station, indicate a neutral type of water. Whereas, saline water type is detected in the Maghsudbeik station. The increase of urban utilization over the past three decades could be the main cause of changes in the hydro chemical characteristics and water type along the Darband River.
Investigation of land use changes in the Darband watershed indicate that the impervious surface has increased during years of 1996 to 2011. Results also indicate that the CN and λ values in Pas-ghale watershed are more correlated to Pin compared with ones observed in Tajrish. The results also reveal that hydrological modeling in watersheds undergoes land use changes and urbanization will result in imprecision results.
 Many chemical parameters of the water quality of Darband River have been increasing at the Maghsudbeik station such as Chlorine, sulfate, sodium, electric conductivity and TDS and in the coming years, it can be considered inappropriate in terms of agriculture in the water class.
 
Keywords: Darband River, land cover and land use, Piper diagram, SCS-CN.
 
 

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Agricultural crops have damaged a lot due to the aftermath of late spring frost, and because low temperatures have damaging effects on agricultural production, it is essential to anticipate and prevent potential damages. Often, atmospheric temperature variations are very urgent due to the high temperature of the systems and the plants cannot adapt themselves with severe oscillations and, have been damaged. The aim of this study was to analyze the climate of the spring frost in Kermanshah, identifying the sea level equations and the late spring freezing frost of the period from 1990 to 2015. This survey has been done to determine the period of the freezing phenomenon, determine the minimum daily temperature of 7 stations placed in Kermanshah,  Hamedan, and Ilam. After analyzing the data of spring frost freezing of Kermanshah province using the main component analysis technique and hierarchical clustering method, the most common 10 patterns of late spring coldness of the area were studied and determined. In 10 resulting cluster, 8 clusters were related to the high-pressure pattern of Siberia. From the total 91 days of spring frost freezing in Kermanshah province (79% (72 days)) is due to the high rainfall of Siberia, 12% (11 days)  is due to the Mediterranean climate and 9% (8 days) is due to the Van lake climate. These pressure patterns were named according to the location of their deposition, which caused the loss of the environment and the freezing frost of the spring.

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Landslide susceptibility mapping is  essential for  land use  planning and decision-making especially in  the mountainous areas. The main objective of this  study is to produce landslide susceptibility maps (LSM) at Dalahoo basin, Iran  using two statistical models such as an  index of entropy and Logistic Regression and to compare the  obtained results. At the  first stage, landslide locations identified by Natural Resources Department of Kermanshah Province is used to prepare of LSM map. Of the 29 lanslides identified, 21 (≈ 70%) locations were used for the landslide susceptibility maps, while the remaining 8 (≈ 30%) cases were used for the model validation. The landslide conditioning factors such as slope degree, slope aspect, altitude, lithology, distance to faults, distance to rivers, distance to roads, land use, and  lithology  were extracted from the spatial database. Using these factors,  landslide susceptibility and weights of each factor were analyzed by index of entropy and Logistic Regression models. Finally, the ROC (receiver operating characteristic) curves for landslide susceptibility maps were drawn and  the areas under the curve (AUC) were calculated. The verification results showed that the index of entropy model (AUC = 86.08%) performed slightly better than conditional probability (AUC = 80. 13%) model. The produced susceptibility maps can be useful for general land use  planning in the Dalahoo basin, Iran.

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Investigating the threats of mangrove forests
with the help of remotely sensed data
 
Behzad Rayegani: Assistant Professor of College of Environment, Department of Environment
 
 
Mangroves are a group of trees and shrubs that live in the coastal intertidal zone. Mangrove forests are very important because they are known as natural heritage and crucial in protecting coastal ecosystems. Mangrove forests stabilize the coastline, reducing erosion from storm surges, currents, waves, and tides. The intricate root system of mangroves also makes these forests attractive to fish and other organisms seeking food and shelter from predators. So, they are ideal places to support the elements of seafood networks. However, these forests are in danger of degradation because of rapid population growth, poor planning and unsustainable economic development. In the process of regenerating an ecosystem, it is necessary to identify the precursors of the threat, to consider the means to eliminate these threats. Therefore, identifying the threatening factors of the mangrove forest ecosystem is the first step in the restoration and protection of the ecosystem.
This study aims to investigate the change and the destruction in Mangrove forests and to identify threatening forces in the Hara Protected Area. Remote sensing is now widely used in studies of ecosystem changes because its information is available for the past, and there are many highly-developed techniques for change detection through remote sensing. Therefore, in order to identify the threatening factors of mangrove forests, remote sensing techniques were used to identify changed areas during a 15-year period. Images of ETM+ and OLI sensor from 2001 to 2015 were collected in the Hara Protected Area (Khorekhoran International Wetland). Given that we have used the multiple-date remote sensor data in this study, it was necessary to use absolute atmospheric correction methods for radiometric harmonization of data. So, with the aid of the ERDAS IMAGINE 2014 software, the Atmospheric and Topographic Correction (ATCOR) model was applied to all data. Subsequently, due to the difference in radiometric resolution of the OLI sensor with the ETM+ sensor, the output of ATCOR of both sensors was stretched into 8-bit data in order to eliminate the existing divergence in radiometric resolution. Also, based on spatial information, one of the image of OLI sensor at the current time was corrected geometrically, and then other images were registered to this image to eliminate geometric errors. There are many ways to detect changes with the help of remote sensing data, but we used two widely used techniques in this study: 1) post-classification comparison; 2) Change detection techniques of Algebra. Totally four different change detection methods were applied to these images. Change detection techniques of Algebra image method include image difference, image ratio, regression and post-classification comparison were used. At first, with the knowledge of the studied area, by combining the two supervised and unsupervised classification (hybrid method), the pixels that were known as mangrove forests were identified in both time periods of study. Then pixels with decreasing trend were determined by post-classification comparison method. From the image of the mangrove forests with the logic of Boolean (OR), a mask of mangrove was obtained, which showed the areas of mangroves during the two periods. This mask was used to make the second group of methods for determining changes (Algebra method) applied to the data. By doing this, in all algebra methods, the histogram showed the normal distribution. Finally, the vegetation spectral indices were applied to the data and their coefficient of variation was obtained in the Boolean mask area. Among these indices, NDVI showed better performance, so the algebra operation was used for this index. Accordingly, areas with decrease, increase and no change trends were visited and then overall accuracy and kappa coefficients were determined.
The results showed that the method of post classification comparison has the highest accuracy in the monitoring of vegetation changes in mangrove forests. This method with a total accuracy of over 93% and a kappa of more than 0.9 showed the highest accuracy in the detection methods of the changes, therefore, in the final examination and prioritization of the regions, this method was used. The surveys showed that the smuggling of fuel due to pour gasoline into the water and camel grazing are the most important destructive factors in the mangrove forest. After determining the rate degradation in four regions, these regions were ranked in order to carry out reclamation and restoration projects.
In the case of intelligent use of the capabilities of remote sensing, one can easily identify the threatening factors of an ecosystem. In the case of mangroves, the only limiting factor is tidal conditions. It is therefore recommended that, as in this study, images are chosen to determine the changes that are in a same tidal state
 
 
Keywords: Remotely Sensed change detection, Image Algebra Change Detection, Post-classification comparison, Determination of thresholds
 
 
 
 

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The application of Extreme value analysis method in heat wave hazard climatology; case study in Mid-Southern Iran
Abstract
Greenhouse warming poses the main cause of atmospheric hazards’ exacerbation and emergence in recent years. Earth planet has been witnessing frequent and severe natural hazards from the distant past; however, global warming has strongly influenced the occurrence of some atmospheric hazards, especially the ones induced by temperature and has increased the frequency and severity of those risks. Such extreme risks arising from temperature element and being affected by global warming could be referred to hot days and their frequency more than one day which undergo heat waves. Of the studies conducted worldwide in conjunction with the phenomenon of heat waves, the following can be pointed out; Schär (2015) has focused his studies on the Persian Gulf and the worst heat waves expected in this area. The recent work revealed an upper limit of stability which enables the adaptability of human body with heat stress and humidity. If people are exposed to a combination of temperature and humidity over long periods higher than this level, they will lead to hyperthermia and death, because heat dissipation from the body is physically impossible. Paul and al-Tahrir (2015) using a high-resolution regional climate model demonstrated that such a situation can occur much earlier. In Iran, in relation to heat waves, Ghavidel (2013) analyzed climatic risk of Khuzestan province in 2000 regarding super heat waves using the clustering approach. The obtained results unveiled the establishment of a low pressure at ground level and high pressure dominance at mid-altitudes up to 500 hp as well as the increase in atmosphere thickness having led to the ground overheating. Added to that, the source of heat entering into Khuzestan is advective and hot and dry air transport through Arabian Peninsula, Iraq and Africa. Ghavidel and Rezai (2014) addressed in a study to determine the temperature-related threshold and analyze the synoptic patterns of super heat temperatures in southeast region of Iran; the results of study approved that the only pattern effective on the occurrence of super heat days in Iran’s southeast is the establishment of the Grange’s heat low-pressure at ground level and subtropical Azores high elevation dominance at 500 hPa level. In this study, absolute statistical indicators, also recognized as above-threshold values approach, were used in order to identify, classify and heat waves synoptic analysis in the warm period of the year in the southern half of Iran. To use above-mentioned indicators, firstly daily maximum temperature statistics of studied stations with the highest periods were averaged every day once in June to September and once for the months of July and September. Using statistical indicators of long-term mean and standard deviation or base period, indicators would be defined for the classification of heat waves and days with peak extreme temperatures. In such classifications, usually long-term average or base period is multiplied by 1 to 3 to 4 times standard deviation and each time is account for the factor of each class.
To select the days for synoptic analysis, averaging was performed of all classified waves into four heat wave categories of low, intermediate, strong and super heat; accordingly based on the maximum blocks in each class of heat waves, days that had the highest temperature values were selected as the class representative for mapping and synoptic analysis.
This study dealt with investigating heat waves synoptic during the year’s warm period in the southern half of Iran. Studies showed that a variety of synoptic systems in the year’s warm period affect the study area. As well as, synoptic analyses concluded that in the southern half of Iran over the year’s warm period when occurring heat waves, low-pressure status dominates the ground level (caused by Gang’s low-pressure and local radiant mode); thus high-pressure status with closed curves is prevailing in atmosphere’s upper levels that gives rise to the divergence, air fall and Earth's surface heating. Studying the status of the atmosphere thickness in the days with the heat wave in the study area indicates its high altitude and thickness that this itself implies the existence of very hot air and susceptibility of the conditions for the occurrence of heat waves. In addition, wind maps at atmosphere’s different levels well illustrate the wind of very warm and hot air masses from the surrounding areas to the southern part of Iran; therefore it can be noted that aforementioned hot air masses mainly wind from places like different regions of the Arabian Peninsula, Iraq, North Africa and the low latitudes to the study area.
 
Keywords: Synoptic analysis, heat waves, maximum blocks, southern half of Iran.
 
 
 

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Risks assessment of forest project implementation in spatial density changes of forest under canopy vegetation using artificial neural network modeling approach
 
Nowadays, environmental risk assessment has been defined as one of the effective in environmental planning and policy making. Considering the position and structure of vegetation on the forest floor, the main role of forest under canopy vegetation cover can be noted in attracting and preventing runoff in the forest floor and reducing subsequent environmental risks. The purpose of this article is forest under canopy vegetation density changes modeling considering forest ecosystem structure and forest management activities as an environmental risk. The main objectives of this study were to: (1) model forest under canopy vegetation density in forest ecosystem to elucidate the ecological and management factors affecting on under canopy vegetation density; (2) prioritize the impacts of model inputs (ecological and management factors) on under canopy vegetation density using model sensitivity analysis and (3) determining the trend model output changes in respond to model variables changes.
In this study, Land Management Units (LMUs) were formed in the region considering ecological characteristics of land. LMUs were mapped out based on Ian McHarg’s overlay technique by ARC GIS 9.3 software. Ecological factor classes of an LMU differ from ecological factor classes of adjacent LMUs (at least in one ecological factor class). The following types of data were solicited for each LMU:
(1) Ecological variables: Altitude or elevation (El), Slope (Sl), Aspect (As), soil depth (SD), Soil Drainage (SDr),Soil Erosion (SE), Precitipation (Pr), Temprature (Te), trees Diameter at Breast Height (DBH), Canopy Cover (CC), and forest Regeneration Cover (RC).
(2) Management variables: Cattle Density (CD), Animal husbandry Dsitance (AD), Road Dsitance (RD), Trail Dsitance (TD), logs Depot Dsitance (DD), Soil Compaction (SC), Torist impacts (To), Skidding impacts (Sk), Logging impacts (Lo), Harvested trees volume (Ha), artificial Regeneration (Re) and Seed Planting (SP).
(3) Forest under canopy vegetation density: The percentage of under canopy vegetation density in each LMU was estimated by systematic random sampling method. In each LMU, a one square meter sample was taken. The average percentage of under canopy vegetation density in sample units of each LMU was calculated and used in the modeling process.
ANN learns by examples and it can combine a large number of variables. In this study, an ANN is considered as a computer program capable of learning from samples, without requiring a prior knowledge of the relationships between parameters. To objectively evaluate the performance of the network, four different statistical indicators were used. These indicators are Mean-Squared Error (MSE), Root Mean-Squared Error (RMSE), Mean Absolute Error (MAE), and coefficient of determination (R²).
Various MLFNs were designed and trained as one and two layers to find an optimal model prediction for the under canopy vegetation density and variables. Training procedure of the networks was as follows: different hidden layer neurons and arrangements were adapted to select the best production results. Altogether, many configurations with different number of hidden layers (varied between one and two), different number of neurons for each of the hidden layers, and different inter-unit connection mechanisms were designed and tested.
In this research, 129 LMUs were totally selected, then ecological and management variables were recorded in them. In the structure of artificial neural network, ecological and management variables were tagged as inputs of artificial neural network and the percentage of under canopy vegetation density was tagged as output layer. Considering trained networks (the structure of optimum artificial neural network has been summarized in Table1), Multilayer Perceptron network with one hidden layer and 4 neurons in each hidden layer created the best function of topology optimization with higher coefficient of determination of test data (which equals 0.857) and the lowest MSE and MAE (which are 0.866 and 0.736 respectively). Considering the results of sensitivity analysis, ecological and management variables like the forest canopy density, cattle density in forest, soil erosion and soil compaction respectively show the highest impact on forest under canopy vegetation density changes (Fig1).
 
Table1. The structure of optimum artificial neural network in forest under canopy vegetation density

Output Layer	First Hidden Layer	Network features
Linear	Hyperbolic tangent	Transmission Layer
Gradient descent	Gradient descent	Optimization Algorithm
0.7	0.7	Momentum
1	4	Number of Neurons
-0.9 up to 0.9	-0.9 up to 0.9	Normalization

 
Table2. The structure of optimum artificial neural network in test data

MSE	MAE	RMSE	R2	Data	The structure of network( the number of neurons)-epoch
0.716	0.678	0.846	0.931	Trainning	Tanh(4)-160
0.793	0.703	0.891	0.894	Validation
0.866	0.736	0.931	0.857	Test

 

 
Fig1. The results of sensitivity analysis of artificial neural network model
 
Nowadays, artificial neural network modeling in natural environments has been applied successfully in many researches such as water resources management, forest sciences and environment assessment. The results of research declared that designed neural network shows high capability in forest under canopy vegetation density modeling which is applicable in forest management of studied area. Sensitivity analysis identified the most effective variables which are influencing under canopy vegetation density.
So, to identify hazardous LMUs in study area, we should pay attention to the canopy density of LMUs as the variable with high priority in determination of under canopy vegetation density. We believe that, in hazardous LMUs in forests, we should pay attention to some modifiable factors of LMU, which is cattle density in forest, by timely plan for livestock elimination. The forest under canopy vegetation density assessment model, in forest projects impact assessment, could be a solution in decision making about forest plan structure and implementation of similar projects in similar locations. 
 
Keywords: Forest plan, Environmental impact assessment, Multilayer perceptron, under canopy vegetation, artificial neural network
 

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Modeling Drought Effects on Sustainable Livelihoods of Small Scale Farmers in Rural Settlements of Kurdistan Province
1. Assistant Professor, Department of Agricultural Extension and Education, Khuzestan Agricultural Sciences and Natural Resources University
2. Professor at Department of Agricultural Management and Development at University of Tehran
3. Professor at Department of Agricultural Management and Development at University of Tehran
4. Professor at Department of Agricultural Management and Development at University of Tehran
 
Vulnerability and adaptation to climate change are local and context-specific, though connected to complex processes at multiple temporal and spatial scales. As such, there is a growing awareness that place-based studies of current and past responses to climatic stress can shed light on the capacity of a given system to respond to future climate change. There is also a growing appreciation of the importance of institutions—formal and informal—in shaping adaptation strategies and mediating the adaptive capacity of households and communities. While rural resource-dependent communities have historically coped with climatic fluctuations, whether such coping mechanisms are still successful today, and will be in the future, depends on the structure of supporting institutions and the way in which they mediate access to entitlements.  Indeed, most social–ecological systems have undergone dramatic change in the last century due to climatic, landscape, and institutional shifts. Because coping mechanisms are developed in relation to particular landscapes, livelihoods, and institutions, social and ecological changes have altered relations across these elements, impacting the effectiveness of particular coping strategies. For instance, pastoralists have historically deployed a suite of coping mechanisms in response to the highly variable climate of semi-arid and arid landscapes. Yet, these capacities may be increasingly compromised in the rangelands of East Africa due to increasing exposure to climate extremes, such as flood and drought and shifting institutional environments. The mechanisms that pastoralists in East Africa historically utilized to cope with climate variability were part of a tightly coupled system where livelihoods, institutions, and landscapes were mutually reinforcing. Pastoralists’ livelihoods were co-produced with a savanna mosaic landscape managed as a common property system by formal and informal customary institutions.
Farmers frequently cope with risks due to the uncertainty of climatic conditions .Population growth,  changes in agricultural policies, environmental regulations and the degradation of natural resources such as soil and water also present farmers with numerous challenges. Although farmers have experience in coping with a certain degree of uncertainty, increased climate variability and changes may cause severe problems. Drought in particular is a climatic disaster that creates substantial costs for farmers and affects their agricultural systems extensively. Drought is the most complex of all natural hazards . making the arid and semi-arid regions of the world vulnerable. Although drought has not been well documented ,  the resource-dependent sectors such as agriculture are the most vulnerable to the impact of this phenomenon. A review of the long-term annual precipitation trends indicated that drought had a worldwide return frequency of every 20e30 years .  However, in the last 50 years, some countries such as Iran and Bangladesh have experienced approximately 27 and 19  drought events, respectively. Therefore, for arid and semiarid regions, drought is a recurrent feature that could lead to the loss of crop production, food shortages and starvation  if not managed appropriately. According todrought impacts could be managed at macro (national), mesa (local) and micro (village and household) levels. However, the micro-level management (i.e., what the farmers do in response to drought) is of great importance. A review of the studies of farmers’ decision-making in response to climate variability revealed that most research has focused on the decision event and not on the entire process.
The main Purpose of this study was to modeling drought effects drought effects on sustainable livelihoods of small scale farmers in rural settlements. Statistical population of this study consisted of all Small-Scale Farming in Kurdistan province. Using Kerjcie & Morgan sampling table, 402 person were selected as the sample using stratified proportional sampling method. The instrument of the study was a questionnaire which its validity was confirmed by a Content validity and construct validity and its reliability was established by calculating Chronbach's Alpha and Combined reliability Coefficient (α>0.7). 
The results of Man- Kendall test showed that the level of aquatic and dry crops, along with the amount of crop production, has increased over time but there is no statistically significant effect on dry production. Also, the results showed that in the economic aspect, the greatest impact on distribution of income and living expenses, in the social dimension, on location affiliation and security and social welfare, the environmental dimension has had an impact on environmental pollution and land resources and on institutional aspects more on the cooperation and participation of the people.
In addition, the results of structural equation modeling showed that drought had the most impact on sustainability livelihood dimensions, respectively, on social, environmental, economic and institutional dimensions.
Keywords
Sustainable livelihood, drought, small scale farmers, rural settlements, Kurdistan province
 
 
 

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Today, air strike on installations and urban areas, is normal. As such, vulnerability assessment cities and provide the right solution for harm reduction is essential. The purpose of this investigation was to identify factors causing damage in the district of twenty in Tehran. The research method is descriptive-analytic and Data collection is library and field. Data analysis is based on using Ahp and GIS. Results show, In the district twenty , There are three zones vulnerable. Including, The old Central, The high-density Dolatabad and sizdah aban neighborhood. These zones are 34 percent of the land. The reason of it is Poor physical structure. Statistical Society is Twenty district in Tehran. Sample size is 384 people of residents of the district. Because, in this area there are strategic factors, is An important part of the tehran city. in the end, are provided The right solution of Reducing vulnerability.

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A new Approach to Urban livability, Thermal Comfort as the Primitive Condition to enhance the livability: Case study, District 22 of Tehran.
 
 
Ahmad Porahmad: Professor of Urban Geography and Planning, University of Tehran
Hossain Hataminezhad: Professor of Urban Geography and Planning, University of Tehran
keramatollah Ziyari: Professor of Urban Geography and Planning, University of Tehran
Saeideh Alijani^*: PhD candidate of Urban Geography and Planning, University of Tehran
 
The concept of urban livability is defined as the quality of life and wellbeing of urban residents. That is the interaction of people, environment and built environment. The residents can achieve happy life and well-being only when the nature surrounding them is happy and healthy. According to the range of welfare concept there is a spectrum of quantitative indicators that directly measure (human body temperature, heart rate, air temperature, wind speed ...) and qualitative indicators such as quality of life, pleasure and joy. The comfort and ease of environment are in the middle of the spectrum, in other words, the intrinsic concept of ambient comfort is environment. The inadequacy of natural environment will affect both indicators in the spectrum and lead to citizens' dissatisfaction and decline in social welfare and threaten the health of humans. Living in a salty marsh or very dry hot climate is never happy and satisfied. Accordingly, many concepts such as living quality, living environment, and quality of place, quality of life and sustainability are often used interchangeably with livability).
         This research is trying to weight the natural environment at least equal to the other two components of the sustainable development triangle. Among the components of natural environment, climate is playing the most important and significant role. Urban climate affects all aspects of city including building interiors, city architecture and open spaces. Thermal comfort of open spaces promote the social life and interrelations of residents. Therefore, in order to promote the social relations and economic activities especial consideration should be paid to open spaces. Accordingly, two types of data were measured for calculating the thermal comfort in the district 22. Subjective and objective evaluations which present qualitative and quantitative data. Objective data includes micrometeorological measurements with mobile instruments. Subjective data evaluated actual sensation vote or perception vote of thermal comfort by people using the urban open spaces. To this goal, questionnaires were prepared and scattered through space users simultaneously with micrometeorological measurements. Subjective data evaluated perceptual sensation vote of thermal comfort by people using the urban open spaces in three hot days of August 2018. Nine points are selected for site measuring and field survey which are representative of two types of urban open spaces in this research:1) Urban park and 2) street. Four cardinal points were chosen adjacent to the Shohadaye Khalije Fars Lake inside the park located in sidewalk pathway around the Lake.  Other five points were selected in streets with different orientation and aspect ratio through the district. The physiologically equivalent temperature (PET), mean radiant temperature (Tmrt), sky view factor (SVF) and aspect ratio (H/W) are the most important indicators in this research which were calculated for evaluating comfort in the district.
      Results showed that urban open spaces in the district are discomfort and expose people to the extreme heat stress; over 40°C. This determines that, the natural environment especially around the Shohadaye Khalije Fars is not comfort. The questionnaire also indicated that people felt warm and dissatisfied.
        There is a high linear correlation between thermal comfort and mean radiant temperature and globe temperature. Therefore, it is concluded that thermal comfort in the district, is directly affected by urban areas.  Also in the streets with low SVF and high aspect ratio, PET were calculated more comfortable than other streets. Point 5 at Naghibzade street, confirmed the effect of urban geometry on thermal comfort. Otherwise, the lack of tremendous trees for creating shade is visible especially around the lake. The high linear correlation between Tmrt and SVF around the lake confirmed the openness of the area and the high amount of solar radiation. Therefore, planting more trees for creating the shade effect is necessary. 
        The perceptual analysis of thermal comfort indicated that by increasing of PET, people felt warmer. However, in a city like Tehran, people are more resistance to the heat stress. In addition, the characteristics of human body strongly depends on psychology and individual features and is a hard issue to predict. Otherwise, the people who felt warm were more than those felt slightly warm which indicates dissatisfaction of people. To be noticed that, thermal comfort of above 40 °C in summer is an alarm to urban planner and designers to rethink about climate consideration and global warming as a most important urban challenge in the district seriously. Besides, the consideration of thermal comfort and urban geometry should be imbedded into the comprehensive plan. This research proved that the climatic consideration for improving the quality of life and livability is important and urban designers and planners should rethink and review the comprehensive plan of Tehran to make a livable and sustainable city in the future.
Keywords: urban livability, climate comfort, sustainable development, urban sustainability, urban geometry, physiologically equivalent temperature, district 22 of Tehran.
 
 
 
 
 
 
 
 

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Resilience, as a concept to confront abnormalities, surprises and unexpected changes in recent years has been raised as the ability of places, societies, and systems to respond to the dangers of tensions and pressures; so that the system can quickly return to pre-stressed situation, threats It accepts the future and confronts them. Central region of Iran according to the zoning studies of the national physical plan of Iran, including three provinces of Isfahan, Chaharmahal and Bakhtiari and Yazd, in a desert climate with many crises in the permafrost environment that has disturbed the state of resilience of the region, and as a result the scheme and target application regional resilience on policy and planning to reduce vulnerability and to cope with various trans-regional crises. Despite the fact that the concept of resilience at the level beyond the city has become apparent, there is still no clear framework for measuring this situation at the regional level. Based on this research, it is believed by the trans-regional and multi-dimensional nature of the resilience that by modifying and applying the concept of resilience to the integrated and multi-dimensional at the regional level, an appropriate framework for status measurement regional resilience in the form of a composite index and thereby risk reduction planning and promoting the resilience of the presentation To give. In this regard, the major purpose of the research is to develop an optimal framework for assessing, measuring and ranking the resilience situation in the central region of Iran. The results show that Chaharmahal and Bakhtiari province have the highest resilience and then there are two provinces of Isfahan and Yazd, respectively. In the meantime, Yazd province has the lowest resilience among the provinces of the central region; therefore, it is necessary to focus on planning and allocating resources to promote and improve priority sectors. Responding to resilience agendas requires the adoption of transregional planning and decision-making approaches such as environmental regionalism.

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Drought is one of the most complex and unknown natural phenomena that causes a periodic water crisis in the affected areas. Increasing water demand on the one hand and the experience of droughts in the province in recent years have led to the water crisis. Knowing the drought is one of the requirements for water crisis management. The purpose of this study was to analyze the trend of the SPI drought index in Isfahan province using nonparametric Sen’s slope test, Pettitt’s change point test and Man-Kendall test. From the monthly climatic data of 10 synoptic stations with a length of 27 years (1990-2017) for time series    The results of applying  Mann–Kendall  and  Sen’s slope tests based on SPI Index for  9, 12, 18, 24 and 48 month time periods, shows drought trend is significantly increasing for all stations out of Ardestan, Esfahan and  Shahreza  stations. In Ardestan station, the drought trend is significantly decreasing for 9, 12, 18, 24 and 48   month time periods and in Isahan station, the drought trend is significantly decreasing for only 48 month time period, and in Shahreza statition, the drought trend is significantly increasingonly for only 18 month time period.
  Despite all stations, the drought trend for one month time period, is significantly increasing just  for Naein station.
   In addition, applying Mann–Kendall test  on monthly rainfall for all station  shows downward but  not significant trend.
   Finally, applying Pettitt’s change point test based on SPI  Index  for 9, 12, 18, 24 and 48   month time periods indicates  the existence of a  significant change point. For same periods we observe  no change point for the monthly rainfall  in all stations.
   In summation, considering the SPI drought index, about 59% of  all stations show significant downward trend bases on Mann-Kendall test and 60% of  all stations show significant slope  based on Sen's slope test and 75% of  all stations show significant change point based on Pettitt's test. In general, for drought analysis using different time periods for the SPI index, in a short time period. (such as 6 months) drought is more frequent but shorter, and as the period increases the duration of drought also increases but frequency decreases. All together, we are facing  a water crisis in Isfahan province and  we must manage water demand  very urgently.

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Identifying spatial patterns in vulnerability involves a comprehensive look at vulnerable points. And provides analytical power to the authorities. Therefore, it is necessary to recognize patterns of vulnerability so as to minimize the amount of damage to them in the event of a crisis. The city of Tehran, as the political and administrative center of the country, is faced with a variety of risks due to demographic burden and physical development. In this research, we tried to analyze the spatial distribution pattern of urban vulnerability to natural hazards in social and physical dimensions in Tehran's 7th region. The method of this descriptive-analytic study and the model used for trigonometric fuzzy logic. The results indicate that: According to the z score, the positive values are 1.96 up, which form the clusters of hot spots in the southeastern region of the arena; It is a sign of more vulnerability in these areas. Also, negative values of 1.96 and less, which are statistically significant and blue, have formed cold spots, And it is interpreted that low vulnerability zones are clustered in space and are mainly located in the northwest. Therefore, the lower the color range in the red and blue areas was less statistically significant  to the point where this positive net worth is 1.65 that in this situation, the spatial behavior of the vulnerability is considered to be non-significant in terms of hot or cold clusters with high and low values and spatial autocorrelation that the map is also displayed in yellow.
 

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The consequence of human activities caused destructive and irreversible problems to the original state in the few past decades that has attracted the attention of all walks of life. The sinkholes are one of the mentioned effects in different parts of the planet such as Iran, Hamadan and especially have been happened in Kaboudarahang-Famenin plain. Researchers believe that the most important consequences of the indiscriminate withdrawal of groundwater and illegal wells and the activities of Shahid Mofatteh thermal power plant change the parameters of soil caused appearance sinkholes in that area. All of the geological information, faults, hydrological, elevation, slope, aspect, and land use investigated by topographical geological maps, also digital elevation models and Google Earth image processes used for the study on the extraction and sinkholes due to the numbers and distribution of wells were assigned in GIS software. The results show that the level of groundwater, geology, land use and height of the range are the most effective factors in the creation of sinkholes; but the efficiency of surrounding factors and in somewhere farther from the sinkholes. The construction of Ekbatan dam on the most important river as the main water provider of understudy plains, the development of Hamadan city and changing the surrounding land use in Bahar county to agricultural, prevent from reaching water to the Kabodarahang and Famenin plains as a former and increasing the water demand in downstream is caused numerous sinkholes that was provided with favorable conditions than before (the dissolution of limestone).

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Abstract

Urban heat island (UHI) is one of the environmental phenomenon which has made difficult environmental conditions for citizen. This study aims to evaluate the spatial and locational variability of Esfahan urban heat island according to the role of land use. Thus an area about 190.2 square kilometers (km2) in Esfahan, as the microclimate, was studied. In order to analyze the relationship between land use and land cover changes on Esfahan urban heat island, the images of Landsat 7 (TM and ETM +) and Landsat 8 (OLI / TIRS) on 20 July 1989, 17 August 2005, 18 August 2014 have been used. The results show that the urban areas has experienced 31% changes in positive direction; while the agricultural sector and green space havehad a reduction of 25% in their area. The analysis of the intensity of heat island show that heated cores are related topoor and barren lands with about 37/33 and 36/5. Although the most area of thermal classwere related to warm thermal class in 1989 and 2005, the average thermal classes were about 63/8%in 2014. Moreover, the locational variation distribution of Esfahan heat island shows that the locationof the heat island has gradually changed. For example in 2014 it included small parts in the south of the city, military zones and barren lands in the south, some parts in the north west and north east areas and small areas in the east of Esfahan. This means that urban development isn’t the main factor of the surface temperature increase and urban heat development, but rather the type of land use has influenced the decreasing or increasing of air temperature.

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Investigation of desertification trend needs an understanding phenomena creating changes singly or action and reaction together in the manner that these changes end up in land degradation and desertification. In the investigation of pedological criterion affecting on land degradation in alluvial fans, first, maps of slope classes, land use and geology were created, then a map of units was founded by overlaying and crossing these maps and grid layer created by extension of ET GeoWizards in ArcGIS 10.3 software. In this research three indices of erodibility, salinity and permeability of soil were considered, finally according to the seven level scales, each of them was shown as the classified map. In this research, nonparametric methods of Friedman and Kendalls' W rank tests were used to prioritize the options, in the manner that after defining crisp numbers in seven level scales, the rank means were calculated. The rank means obtained from Friedman and Kendalls' W rank tests alter from 7/00 to 17/33. Obtained results from the nonparametric methods showed that 74/18 % (4245/77 ha) and 25/82 % (1477/67 ha) of the area were classified into two classes of medium and very heigh desertification potential, respectively. The results also showed that the youngest and old gravel fans of the area have desertification potential of very high (798/75 ha) and low (152/23 ha), respectively.