Journal of Spatial Analysis

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Groundwater resources are important sources for the supply of water in agriculture, industry and drinking in Ardabil plain, therefore underground water resources planning and sustainable management of these resources are important. The purpose of this study is grading the villages in the plain of Ardabil in underground water crisis and changes during the years 1360-1391. The information obtained from 39 wells, piezometers in plain of Ardabil. Using simple techniques and fuzzy cumulative weighting and interpolation methods, the piezometers interpolation of shallow water table and how it changes during the period is showd.

Introduction
     Groundwater is one of the main sources of drinking water supply for many people around the world, especially in rural areas. Groundwater can be contaminated by natural or human activities are numerous. All activities including residential, municipal, commercial, industrial and agriculture can affect groundwater quality. Groundwater contamination can result, such as the loss of a source of water supply, high cost of clearing the high cost of alternative water supply or cause potential health problems. Given the importance of determining the results of the plains of the country, the aim of this study was to determine changes in aquifer storage of Ardabil using statistics and analysis on multi-criteria decision-making and evaluation of groundwater is a crisis situation.

Data and Methods

     In this study, the data of piezometers wells in of Ardabil plain scattered through the city of Ardabil Regional Water Authority have been prepared. Also, the surface layers and point to the plains of Ardabil, political divisions and the location of wells, piezometers villages for final maps have been used. The data of deep wells, as well as cultivation of four major product with a high water requirement of wheat, barley, potatoes and forage to determine the relationship between ground water and water harvesting has been a drop in water table.

The study area

     Plain study area is located in the north-west of Iran in Ardabil province (Figure 2 and Figure 3).  The average height is about 1360 meters above sea level  It covers an area of approximately 820 square kilometers and is located in the Gharasoo watershed.

• Inverse Distance Weight;
• Global Polynomial Interpolation;
• Local Polynomial Interpolation;
• Radial Basis Functions;
• Straight Ranking;
• Fuzzy Normalized;
• Fuzzy multi-criteria decision-making;
• FSAW.

   The first step is to evaluate each process and required hydrological data collection, and the coordinatingits location. The geostatistical methods of IDW, GPI, LPI, and RBF in the ArcGIS software were used for  interpolating all existing data and a drop in water table in the area of standards for grades 10 class (raster) within restricted fields of Ardebil were determined.

    Finally, using simple collective weight, weight-bearing layers and layers of loss data water table for the years 60 and 90 is obtained. To get the final map of water table drops, the two layers are deducted and the final map of Ardabil plain water table drop that phase is obtained.

     Analysis showed the reduction of water table almost 47 percent in 1391 compared to 1360. As can be seen in Figures 12 and 13, maximum of 45 meters water table wells, piezometers in 1360 to more than 70 m in 1390 has come to reveal the deterioration of the aquifer Ardabil.

    Pholadloo_e_Shomali district with the highest concentration of deep wells in the near future to continue the removal of existing deep wells, groundwater resources will go into sharp decline.

    Sharghi Village goes to the crisis and in the meantime, the central Vilkij district includes the eastern part of the plain, the drop in water table aquifer at greatest risk to the two villages in East and Central Vilkij.

• Due to the limitations of traditional agricultural development potential ground water;
• Increase the efficiency of irrigation, changing crop patterns of water needed to fill low-power consumption;
• Efficient use of water resources and prevent unauthorized digging deep wells to exploit the nutritional front, especially in the East and Southeast plains.

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The term "Game GIS” implies to real spatially enabled games in which a special part of the world is virtually simulated, represented and managed. In fact, game GIS is an integrated system consists of video games and geographical information systems, aimed to simulate and representing spatially enabled environment. The achieved result of implementing a game GIS service can be exploited before a crisis for wise designing of a city and diminution of the aftermath casualties. As the decision making process plays the key role to reduce the losses, the need arises for using the models as much as close to the reality. By this, it is possible to use the virtual world in in the form of a game rather than experiencing the real world with real wounded and killed persons in. This enables us to recognize and manage a test environment for promoting the managing the real environment of a city during and before a natural hazard disaster like an earthquake. The game GIS may be counted as a service for sharing and dissemination of spatial information as well as online GIS to have a visual and synoptic management of the earth plant facing various disasters. The current research is aimed to design and implement a software architecture for an earthquake game in Tabriz city (Iran).

The study area is district 10 of Tabriz located within a fault zone. According to field surveys, 82.1 percent of buildings in the study area may be vulnerable against earthquake in terms of the quality of building construction.

Methodology of the research to design, program and implement the game GIS service are undertaken as the following processes: data collection, database creation and software production.

The collected data includes master plan maps of the district 10, building quality, number of floors, building façade materials, age of building, street network (adopted from the master plan of Tabriz) and population of each parcel.  Also, some regions are assumed as hospital, relief-rescue center and treasury money.

To design the software, 2D environment of MapControl and for implementing the game into the 2D environment, ArcEngine of ArcGIS have been exploited. The mentioned engine gives us possibility to use of analysis and modelling capabilities as much as closer to the ground reality which are compatible with available geometry of the terrain (Amirian, 2013, 17-19). The MapControl is a framework in which the map and game area are displayed. Symbology is used to show the persons as well as equipments. Briefly, the stages undertaken during the current research can be explained as the following:

• Data collection based on available sources via field surveying.
• Data processing and creating a database from street networks and building owned the age, materials, floors fields.
• Calculation of vulnerability rate for each building separately as well as the amount of deconstruction damage per Richter.
• Drawing the street and alley network to prepare network analysis dataset.
• Preparing special network analysis database and evaluation in various situations.
• Using the gained layers and implementation of the scenario.

After that, the conceptual architecture of the software has been designed based on the scenario.

The game GIS services has been designed with 6 different classes offer numerous functionalities responsible for displaying program commands and different views of the game. Finally, the service is designed and implemented in a real schema for crisis management application. The resulted game is played in 4 stages. In the first stage, the player starts with a 5 Richter magnitude earthquake and ends while the player gets to 8 Richter. The designed software simulates the destruction rate of buildings based on the influential factors, wounded transfer routing and rescue operation. The game player gains credit according to his quickness and agility. The player would go to the next stage with one Richter magnitude higher, if gains enough credits during each stage. The result of the current research as a Game GIS service, can be used in earthquake simulation happens in various magnitudes for management of decreasing the effects of earthquake, quick reaction, maneuver and education. Considering the achieved results, designing and performing the game GIS service over the web based on open source technologies rather than being desktop and commercial service, can be suggested as a new research frontier for the future researchers.

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Vulnerability to natural hazards is one of the most important issues of villages in Iran. Iran is listed in the first ten accident-prone countries in the world. It annually imposes many damages on villages through natural disasters such as earthquakes, floods, etc. To tackle the problem, an important attempt was applied during the recent decades is the policy of resettlement. The mentioned policy has been followed in forms of movement, integration and aggregation of villages. As spatial foundation and location of settlements are mostly based on natural environmental factors, then before any attempt, or before any dislocation of the villages, ecological potential of the new place needs to be evaluated. However, as dislocations resulted from unpredicted events such as flood are associated with emergency conditions and would be done very quickly; there is not enough time for evaluation before the action. In result, conducting such plans, unlike their positive impacts on service-delivery, cannot be quite welcomed due to ignoring the ecological and environmental factors which need to be considered before any actions. Therefore, such plans can create some negative consequences and be considered as non-successful plans.

       One of the projects that have been implemented in connection with this issue in Golestan province is dislocating and integrating flooded villages on Kalaleh County during 2001 to 2006. Based on the mentioned plan, twelve villages which were located at higher section of Gorgan Roud and were aggregated and located at a new site named “PishKamar”. These villages were flood-damaged. Such a site was urgently constructed based on a top-down approach, urban-based patterns and without considering the needs and ideas of stakeholders. So, such a plan needs to be evaluated and assessed against some normal and standard criteria. As such mistakes can be repeated elsewhere, recognizing the pros and cons of such plans would be a good guide and experience for the next projects. The present paper aims to evaluate the ecological potential, physical design of the site as well as measuring the levels of PishKamar site resident’s satisfaction.

      This study is a kind of the ex-post facto evaluation and its methodology is descriptive – analytical. To do that, we have considered a four-steps ecological potential of the site using Makhdom’s model. We also have used the 1:50000 topography maps, 1:250000 geological maps, 1:100000 land-use maps and 1:100000 soil fertility and capacity. All layers were transferred into ArcGIS environment, for more analysis. Data collection was based on surveying, interview and questionnaire. The statistical sample include 1350 households heads resided at the studied site, of them 200 persons were randomly selected for data collection purposes(According to Cochran   in the formula, standard deviation was 36%, test statistical was 1.96 and α was equal to 0.05). The results of the first stage of our study indicated that based on 330 primary integrated cells and overlaying the maps, there would exist 13 homogenous ecological units. In addition, a significant proportion of the Makhdom indicators used to assess indices was confirmed by chi-square test. Accordingly, 67% of cells in class I with good ecological potential and 8/28% of the cells in the appropriate ecological class II and only 2.4 percent were in class 3 to be inappropriate ecologically. Thus, of total 13 units, 11 units with an area equivalent to 127 hectares were classified as class I and II, and environmental units with an area of three hectares in third class were inappropriate. Therefore, the studied site was evaluated as a good site in terms of ecological conditions.

     In addition, evaluation of residents' satisfaction mapping site in terms of compliance with the ecological conditions and the physical texture design which was based on systemic approach of sustainable development indicators was revealed that the maximum satisfaction of residents was related to house orientation and strength of buildings, road network design and architecture patterns.But the dimensions of environmental issues including soil resistance as a result of landslides, climate harmony with the architecture and the wind direction has not completely been considered. Totally, of 11 evaluated criteria, people were satisfied with 6 of them and disappointed with another 5 criteria. It was confirmed by T-test.

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Today slum refers to those areas of the city which are not necessarily situated at the corners of the city, but to those which are in margins from economic, social, cultural, and other urban life aspects, that has formed a settlement in which the least living-supplies of healthy water, electricity and gas, transportation system and a clean environment suffice their lives. This type of settlement is due to the asymmetry and commonality of features and conditions of living in the main parts of the city. And generally indicate the low level of living conditions in comparison with the average standards in the main city specifically, and also in living conditions in cities as a whole. On the other hand, informal settlement refers to the discordance of settlement with the approved regulations of governmental organizations and particularly of municipalities. Those areas which are situated outside the servicing scope of the general and governmental organizations such as electricity, gas, and telecommunications offices, along with municipalities accompany various phenomena such as urban poverty, poor housing, immigration from countryside to cities, environment pollution, unhealthy environments and etc.

            In Iran, slum began in the 30s (solar calendar) with the immigration of village dwellers to the cities, and after a decade, it was prospered due to land reforms and economic-social policies of the day, a growing increase which has never stopped since. Slum or informal settlement in the outer parts of the cities is not just a physical notion but is an outcome of the macro structural factors in economic, social, cultural, and political aspects in a national or regional scope. The reasons for this phenomena vary which can differ from one place to another. Nevertheless immigration is one of the main reasons for slum settlements. It can simultaneously play two roles; it can be a solution to demographic crises. It leads the surplus population out of the region and accordingly the human power is directed where is needed most. It balances the structural asymmetries of population and by reducing the development imbalances in different regions result in the betterment of the status quo. And on the other hand, it might be possible that by immigration of the human power, the economic equilibrium between the source and destination community would be disturbed, and by having a community without any human power, it generates complex social and cultural situations; which all in all leads to a congested crowd overpopulating specific big cities and regions.  In this way, it brings about problems in servicing and efficient regulation of issues and thus be regarded as a disturbing element of development and mutual understanding. The investigated region has been exposed to the crises of immigration and slum settlements recently, so much so that based on the population and housing census of 2006, population growth rate of Shahriar rose by a far distance from other cities to 8.7 percent. Thus, this research was conducted to investigate the elements of immigration and slum dwelling in Shahriar city. And it aims to answer these questions:

1. How social, economic, and demographic factors influence the slum settlements of those who have migrated to this city?
2. How is the local dispersion in Shahriar?

On this basis, with the researches and investigations conducted at the outset of the study, district 2 was selected as a fit choice out of the three districts of 1, 2, and 3 which settled slums. Since all the locals were not slums in this specific districts, with proper investigation the slum areas were identified which had a high rate of immigration; with whom interviews were ran and questionnaires distributed. To this end, by following Cochran formula, 200 people were selected as samples through cluster random sampling out of the statistical community. To analyze data, descriptive statistical methods such as central index, dispersion and inferential statistics like Chi-square, Wilcoxon and Friedman tests were utilized.

The results of the  study indicates that the slum in Shahriar are situated in the old and cheap sections of the three districts of 1, 2, and 3. Also, after a detailed examination it was proved that Shamloo local in district 2 is more suitable than the other ones. On the other hand, by investigating the economic factors (such as job opportunities and income) it was indicated that immigration is very important from the aspect of providing job opportunities. Secondly, social factors are more important in slum settlements issues. For instance, one can refer to urban and welfare facilities, educational facilities, health and recreation facilities are all social factors. On the other hand, those people who have migrated due to pursuing education, higher level of welfare, better facilities etc. are all below 30 years old. Based on the findings of this research, families were not significantly changed after immigration in comparison with the period before it, but it is a vital element in three membered families in times of immigration. All has been done to meet the financial needs of the family. Therefore, one can claim that most immigrations to slum areas have been due to economic and social deficiencies of the source society.

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Accessibility to precise spatial and real time data plays a valuable role in the velocity and quality of flood relief operation and subsequently, scales the human and financial losses down. Flood real time data collection and processing, for instance, precise location and situation of flood victims may be a big challenge in Iran regarding the hardware facilities (such as high resolution aerial imagery devices) owned by the correspond organizations. To overcome the mentioned inabilities as well as reducing the financial costs for real time monitoring purpose of a flood, the current research intended to use the capacity of the flood victims and other volunteers to collect and upload real time data to rescue themselves. By means of this, flood real time spatial and non-spatial data collection is applicable via public and per-person participation based on the needs of each victims. The current Open Source workflow has been so designed that by using a browser like Mozilla, Explorer, Chrome and etc., and without the need for installing any software, the victim transmits his/her exact geographic location (captured automatically by the designed web service) and other multimedia data such as video-photo. Also, the flood-affected person announces the type of the damage and consequently, demanded rescue operation to the managers as a text information. After data processing on the server, the information is represented as a real time rescue map for decision making. The rescue plan may be mapped based on the singular aid as well as plural plan in the cluster form specialized for a particular group of victims in each bounding box. To design the web service, a client architecture for victims, other volunteers and managers has been developed, for implementing the service, Open Source technologies, server-side and client-side programming languages, Geoserver and WFS (Web Feature Service) standard adopted by OGC for spatially-enabled representation of victims demands, have been exploited. The research result is a browser-based service in which the client service offers automatic zooming to the current location of the clients and sends the rescue request including personal identifications and the type of injury using PHP (stands for Hypertext Preprocessor) and SQL (Structured Query Language). In the other side, on the client side designed for managers, the requested rescue submitted by the victims and other volunteers are mapped and displayed real time by OpenLayers and WFS. The result introduces an efficient applicable method for gathering real time and high accuracy geographic-multimedia-text data collection and consequently, extremely reduces the relief operation costs. Finally, the proposed methodology causes better performance and spatially clustering of victims to decrease the aftermath of the flood in a region like Iran suffers from the lack of expensive hardware technologies for precise data collection and transmission.

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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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Today, the impact of climate is considered on the life, health, comfort, activity and behavior in a form of the branch of science   such as human biology. Due to difference of frequency people with each other, the sensibility of every one from weather can be different from the other one that's why the climate can’t be totally undesirable or the climate can be totally desirable for all the people, so we can say that all of climatic elements are affected on human comfort but the effect of some of them is quite cleared and the effect of the others is mild and sometimes invisible. The greatest effect on comfort and discomfort can be included temperature, humidity and solar radiation. The aim of this research is to investigate and determine    the area risk of climatic comfort. For this purpose, the temperature, precipitation and humidity data have been extracted for Khuzestan province form Esfarazi database. In this approach, first different properties of the temperature, precipitation and humidity for the area with climatic discomfort   have discussed   based on the conditional probability distribution. This study has been identified the areas of climatic comfort in Khuestan province using multivariate analysis (Cluster analysis and Discriminant analysis) and spatial autocorrelation pattern (Hot Spot index and Moran index) with an emphasis on architecture. The results showed that the risk area of climate comfort is included mostly  of  the western parts of  Khuzestan province namely the border areas with Iraq and some parts of  southern  of  province .On the other hand ,trend analysis the  range of this area to climatic discomfort indicated that it has increased significantly  in  recent periods .The results also  showed that  the local distribution of   precipitation  in all periods in the areas of climatic discomfort  has  been   a high  the coefficient of  variations.

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Designing and implementing a 3D indoor navigation web application
              Extended abstract
Nowadays, due to the complexity of interior space of buildings, the need arises for indoor navigation inside such spaces. Indoor navigation systems may be helpful for emergency evacuation of the crowd in natural hazards such as earthquake as well as human-made disasters. These systems can also act as a decision support system for officials. Literature survey on indoor navigation services shows that a large number of researches have been conducted around designing and implementing such systems but automatic indoor spaces topology extraction of the current building information models remains as a challenge. This research aims to introduce, design and implement a web-based indoor navigation system using CityGML data model in LOD4 (level of detail) to overcome the mentioned problem.
The architecture of the current research is a browser-based web application service such that the data model processing and graph creation is implemented on the server side, the client interface and calculated path are represented on the client side (browser). Through the CityGML data model processing, firstly, the building navigable spaces such as room floor, doors and stairs are extracted and then, each space as a node and the connections between the nodes are defined as edges, are imported to the navigation graph. Programming on the server side has been performed by Python language and web development languages including HTML (Hypertext Markup language), JavaScript, JQuery and AJAX are used on the client side. Cesium virtual globe has been exploited to display the data model and the calculated route.
To evaluate the introduced methodology and designed service, a three floor house with CityGML format in LOD4 was used as the case study. Generally, a client can request a 3D calculated path by selecting the source and destination points on the client browser. The server receives the request and returns the response as a 3D line to the client browser on the Cesium environment. In addition, a descriptive graphical user interface for visual inception of the route is offered to the users on their browser.
One of the advantages of the designed web application is that, the service is implemented on the browser. Hence, all devices equipped with a browser have possibility to run the 3D routing service. Besides the mentioned cross-platform capability, average expectation time of the graphical interface loading, data module processing and path finder module are 7.03 milliseconds, 12.42 seconds and 2.44 seconds respectively that visits a valuable criteria in emergency situations like an earthquake phenomenon. Regarding this fact that CityGML is a new data model and supported by a few software, the introduced architecture causes less implementation costs as well as automation of these systems.
 
Keywords: 3D indoor navigation, web application, interior space of buildings

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 Detection and Attribution of Changing in Seasonal variability cause of climate change (Case study: Hillsides of Central Southern Alborz Mountains)
Abstract
One of the most important challenges for the human communities is Global Warming. This vital problem affected by Climate Change and corresponding effects. Thus this article attempted to assess the trend of real climate variables from synoptic stations. Daily precipitation, Daily Maximum Temperature and Daily Minimum Temperature have been selected for the Hillsides of Southern Central Alborz Mountains and have been tried to prove climate change and attribute the related forcing such as Greenhouse Gases. The Capital of Iran located in this region and this region has a special occasion, because at least a quarter of Iranian population live in these provinces (Tehran and Alborz) and four big dams located in this region. The Intergovernmental Panel on Climate Change’s defines ‘‘detection’’ of climate change as ‘‘the process of demonstrating that climate or a system affected by climate has changed in some defined statistical sense, without providing a reason for that change,’’ while ‘‘attribution’’ is defined as the process of evaluating the relative contribution of multiple causal factors to a change or event with an assignment of statistical confidence. Regional D&A studies provide an insight to local changes in natural systems and may help in planning and developing robust adaptation strategies. Previously, formal detection and attribution have been used to investigate the nature of changes in various climatological variables such as air temperature, surface specific humidity, ocean heat, sea level pressure, continental river runoff, global land precipitation and precipitation extremes. However, almost all of these studies deal with climatological or meteorological variables at the global or continental scale. Studies which have attempted to formally detect and attribute regional hydrometeorological changes to anthropogenic effects are rare. Regional-scale D&A analysis is more difficult because the detection of anthropogenic ‘‘signal’’ in natural internal climate variability ‘‘noise’’ is determined by the signal-to-noise ratio which is proportional to the spatial scale of analysis, especially for real observation data. For overcoming this issue interpolation method (IDW) has been applied to transfer point data to area (gridded) data. The point data gathered from 3 synoptic stations (Mehrabad, Karaj and Abali). Then transferred data have been Standard and Averaged for 3 years. Standard values of annual and seasonal amounts have been computed for individual stations as the average of the standard values of annual and seasonal amounts available 3 years anomaly values. Estimates of annual or seasonal variables anomalies were obtained by averaging the annual or seasonal by 12 or 3 respectively. For detecting and attributing 3 simulation signals (ALL, GHG and NAT) selected from Canadian General Circulation Model (CanESM2.0) of CMIP5 archive subcategories. Space–time series of observations and model simulated variables responses to external forcings (the “signals”) first have been compared qualitatively by computing correlation coefficients between observations and simulations. This simple method does not optimize the signal-to-noise ratio nor provide a quantitative measure of the magnitude of model simulated response relative to that in the observations. Nevertheless, it provides an easy-to-understand view of the similarity between observed and model-simulated changes. Optimal detection and attribution analysis very often requires a reduction of dimensionality. This is typically done by projecting both observations and simulations onto leading empirical orthogonal functions (EOFs) of internal variability and using the residual consistency check to determine the number of EOFs to be retained in the analysis. To produce internal variability for residual test and consistency, Pi-Ctrl Runs have been used. The Preindustrial simulations have high volume, this subject complicates calculation therefore Experimental Orthogonal Functions (EOFs) have been used to reduce the Pi-Ctrl simulations volume and provide situations for Optimal Fingerprint. Optimal Fingerprint method is the best method for Detection and Attribution. Results have been obtained by this manner indicated Global Warming affected the study region by affecting on mean cumulative winter precipitation (0.88), mean spring minimum temperature (0.78) and mean summer maximum temperature (0.76). These numbers are the beta coefficient that named scaling factor. Although the scaling factor for the mean spring minimum temperature affected from GHG signal obtained (0.73), but the GHG forcing alone didn’t have a significant effect on the precipitation and maximum temperature. Also, NAT signal didn’t have significant effect on the region alone, too. The obtained results of this study indicate the earlier studies, such as Wan et al, 2014.
 
Key words: Climate change, Detection, Attribution, Optimal Fingerprint, Hillsides of Central Southern Alborz Mountains
 

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 Relationship between hydrogeomorphic features and suspended sediment load under Kashfarud basins
 
Introduction
As a stressful stimulus, river sediment is the most significant threat to aquatic ecosystems. To prevent or minimize the damage, three stages of the erosion process should be investigated (Naseri et al., 2019: 83). Determining the amount of sediment transported by rivers is important from different aspects. Sediment carried by water flows is considered a factor effective in shaping the geometric structure and geomorphic characteristics of rivers (Tashekabood et al., 2019: 282).
Data and methodology
To estimate the amount of annual suspended sediments, the flow and sediment statistics of hydrometric stations (8 stations) and meteorological stations (13 stations) were employed (Figure 2). The research statistical period is 25 years (1993-2017). The altitude, area, and perimeter of the basins were obtained from topographic maps with a scale of 1.25000. To investigate the correlation between independent and dependent variables, the normality tests of Shapiro-Wilk and Kolmogorov-Smirnov were performed in SPSS16 software. To extract the geomorphic features of the basins, the digital elevation model was used. Then, ground surface corrections and pretreatments such as removal of hydrological pits were performed and ground drainage pattern was determined.
Stepwise multivariate regression
In the present study, stepwise multivariate regression was used to reduce the number of independent variables and determine the effective factors in the sedimentation of the basin. This method investigates the effect of several independent variables on a dependent variable (Zare Chahuki: 2010). In stepwise multivariate regression, the independent variable that has no more significant effect on the dependent variable is removed from the analysis, hence excluded from the equation. The general form of the stepwise regression equation is:
Equation 1                                                                            Y= a + B1X1 + B2X2 + …… + BnXn + e
Data description and interpretation
The principal component analysis method was used to determine the most effective characteristics of sediments as well as their grouping. In principal component analysis, variables that have a high correlation and are distributed in a multidimensional space are reduced to a set of non-correlated components, each of which is a linear combination of the main variables. The obtained non-correlated components are called principal components (PCs). Prior to component analysis, the KMO coefficient was used to ensure the appropriateness of the data for principal component analysis. This coefficient fluctuates in the range of zero and one and if its value is less than 0.5, the data will not be suitable for principal component analysis and if the values of this coefficient are between 0.5-0.69, The proportionality of the data is moderate and if the value of this coefficient is more than 0.7, the data will be quite suitable for performing principal component analysis.
Regression analysis results
In this study, the sediment weight of the basin was considered as a dependent variable and other parameters as independent variables. The variables of slope, precipitation, basin length, Elongation Ratio (R), circularity coefficient, and unevenness of the basin have a higher correlation with the amount of sediment production in the basin than other variables.
An eigenvalue was used to determine the number of factors. The minimum eigenvalue for the selection of final factors is 1, and factors with an eigenvalue bigger than 1 are considered final factors. The results showed that the three factors of circularity coefficient, compactness coefficient, and basin form coefficient have an eigenvalue bigger than 1.
Conclusion
The results showed that geomorphic parameters have a high correlation with the amount of annual sediment. The results showed that seven factors of slope, precipitation, basin length, elongation ratio, circularity coefficient, unevenness coefficient, and form ratio of the basin were the most important in estimating the amount of suspended sediment based on the principal components analysis method. The average of special sediment varies from 134 tons per year in Dehbar basin to 16 tons per year in Kardeh basin and also the average annual sediment varies from 261.6 tons per year in Golmakan basin to 156.7 tons per year in Shandiz basin. Evaluation of Bartlett's test of sphericity tests and KMO values is 0.9. Therefore, the data is suitable for factor analysis. The percentage of variance explained by each factor indicates that the circularity coefficient with 50.71% of the variance explains all the research variables. In total, three factors of circularity coefficient, compactness coefficient, and form ratio of the basin could explain 82.6% of the variance of all research variables. Therefore, the results are consistent with Lu et al. (1991), Sarangi et al. (2005), Tamene et al. (2006), Zhang et al. (2015), Salim (2014), and Ares et al. (2016).
Khorram Dareh sub-basin with heavy rainfall (504 mm) has the lowest specific sediment, which is due to the geological structure of the region. Based on the calculated indicators, most of the studied sub-basins are elongated. The form ratio of the basin is less indicative of the elongation of the basin. The highest branching ratio of the basins is in the vicinity of faults. Also, high circularity values indicate points prone to sedimentation. River sections up to degree 3 are located in more subdued areas and have a steeper slope. Golmakan, Khorram Darreh, Zashk, and Dehbar sub-basins have a high potential for sedimentation. Regression equations of sediment measurement curves are usually used in sediment load estimates. The most important reason is the ease of application of these equations. According to the research results, it can be concluded that the integrated use of principal component analysis, cluster analysis, and multivariate stepwise regression has a suitable and acceptable efficiency in estimating suspended sediments. Testing the regression model concerning different climatic and hydrological regimes of Iran’s watersheds to achieve an efficient pattern of using these equations can be fruitful in estimating sediment load in different regions.
 
Keywords: Hydrogeomorphic, Sediment erosion, Kashfarud basin, Stepwise multivariate regression

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Designing a Volunteer Geographic Information-based service for rapid earth quake damages estimation


Introduction
The advent of Web 2.0 enables the users to interact and prepare free unlimited real time data. This advantage leads us to exploit Volunteer Geographic Information (VGI) for real time crisis management. Traditional estimation methods for earthquake damages are expensive and time consuming. In contrast, volunteer and web-based service are near real time with almost no cost services. the lack of accessible real time data collection services causes delayed-emergency responses for disasters like an earthquake. This drawback is critical when we encounter a problem like buried people with valuable seconds for emergency rescue operation.
The current research aims to design and implement a web-based volunteer data collection service for rapid estimation of earthquake damages and number of buried people.

Methodology
To investigate the capacity of VGI in rapid estimation of earthquake, a technical frame work based on the web technologies has been programmed and implemented. The designed service is comprised of server and client sides.
The client side is a two-side browser-based service includes volunteers (users) and managers pages. On the user page, volunteers have a web page to enter and fill in the blank forms and taking a photograph of the target building and compare it with pictures. They watch the sample pictures in different level of damages and compare their building with the samples and give a grade of the most similar picture with their building. This grading process leads the server to analysis and classify the incoming data and create the heatmaps for managers. On the managers page two online discrete heatmaps for the both earthquake damages and buried people are displayed. In fact, the heatmaps present the online and real time quantitative situation of the building damages and buried persons as hot spots. These hotspots have the first priority for giving emergency services. The manager page also exploits query tools to request different level of details and classes from the server side.
The server side is responsible for receiving, saving, spatial analysis and transmission of the requested result to the client side. This task is carried out by the exchange side. As the citizens are entered to the browser-based service and fill in the blank forms for building damages based on the mentioned guideline and report the buried people, These forms are transmitted to the server side and a geo-server performs spatial analysis including Heatmap, distance and clustering analysis. Then, a real time damage and buried people map are prepared and delivered to the client side. The server updates the created maps whenever a new data is submitted. By this, a real time damage and buried people maps are accessible for official managers to conduct a goal-oriented emergency operation and a preliminary earth quake damages on city building blocks.
After the technical frame work has been designed, it was tested in Oshanvieh city by 132 volunteers on the scene for an earthquake.

Results and discussion
To investigate the capability of volunteer geographic information for earth quake afterwards, the designed service mentioned in the methodology was utilized on Oshnavieh city. It was assumed that an earthquake has occurred. 132 volunteers participated for the data collection process. According to the crisis management organization experts, 102 reports of the total 132 reports are correct that shows the accuracy of 76.52 percent. Besides the building damage level based on the defined guideline, the citizens also select their vital needs after the earthquake.
  the most requested vital needs are warm stuffs, medicine, water and foods respectively. Unfortunately, the participation rate is ranged from some seconds after the earthquake to three days. This means that some citizens have filled and transmitted their data three days after the earthquake.
In the following, a comparison between the designed service and traditional earthquake damage estimation methods (in situ) was carried out. The result shows that field-based methods for a city like Oshnavieh need about 20 days. However, the designed volunteer-based service what is programmed and implemented in the current research does this job by 3 days.

Conclusion
As the results show, the proposed service designed in this research implements the damage estimation process 6.5 times faster than the governmental procedures. This proves the efficiency of the research achievements. Besides the velocity, traditional damage estimation methods are expensive compare to volunteer-based data collection and processing which are almost free, scalable and pervasive.

Keywords: Volunteer Geographic Information (VGI), earthquake damage estimation, heatmap, oshnavieh city.



 

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Determination of flood-prone areas using Sentinel-1 Radar images
(Case study: Flood on March 2019, Kashkan River, Lorestan Province)

Introduction
Although natural hazards occur in all parts of the world, their incidence is higher in Asia than in any other part of the world. Natural phenomena are considered as natural hazards when they cause damage or financial losses to human beings. Iran is also one of the high-risk countries in terms of floods. Until 2002, about 467 floods have been recorded by the country's hydrometric stations. In addition to natural factors such as rainfall, researchers consider human impacts such as destruction of vegetation cover, soil destruction, inefficient management, destruction of pastures and forests, and encroachment on the river are the most important factors for the occurrence and damage of floods in the country. One of the most efficient and emerging tools in flood surveys is the use of radar images. SAR images and flood maps produced by radar images provide researchers valuable and reliable information. Moreover, maps obtained from SAR images help officials to manage the crisis and take preventive measures against floods. The Sentinel-1 satellite is part of the Copernicus program, launched by the European Space Agency, and is widely used in mapping flood-prone areas. The contribution of Sentinel-1 to the application of flood mapping arises from the sensitivity of the backscatter signal to open water. This study aims to determine high-risk and flood-prone areas along the Kashkan River using Sentinel-1 radar images.
Data and Methods
 The study area includes a part of the Kashkan river from Mamolan city to the connection point of this river to Seymareh river, after Pol-dokhtar city. The average annual discharge of the Kashkan river is 33.2 cubic meters per second based on the data of the Pole-Kashkan Station. The length of the river in the study area is about 100 km. To investigate flood-prone areas, we applied pre-processing and image-processing steps to each flood event including SAR images belonging to March 25^th, 2019, March 31^st 2019, and April 2^nd, 2019. SAR images were acquired from ESA Copernicus Open Access Hub. climatic data was downloaded from power.larc.nasa.gov. To create meander cross-sections, the Digital Elevation Model of the studied area was utilized. Cross-sections were created using QGIS software. Pre-processing steps include: applying orbit data, removing SAR thermal noise, calibration of SAR images, de-speckling and topographic correction. In image processing, we applied the Otsu thresholding method to distinguish water pixels from land pixels. In thresholding methods, the histogram of each image is divided into two parts according to the amount of gray composition. The higher the amount of gray (i.e., the pixel tends to be darker), the more pixels represent water, and conversely, the lighter-toned pixels (i.e., pixels that tend to whiten) represent land. The Otsu thresholding method is a commonly used method for water detection in SAR images. It uses an image histogram to determine the correct threshold. The most important feature of the Otsu method is that it is capable of determining the threshold automatically. The Otsu algorithm was applied to all images using MATLAB.
Results
According to the flood maps, on March 25th, 6.51 percent of the study area was flooded, while on March 31th, only 3.96 percent was flooded. This is mainly due to less precipitation on the 31st. On March 25^th the average daily precipitation was 47.46 mm while on 31^st of March the average daily precipitation was 31.64 mm. On April 2nd, however, there was no rainfall, on the day before more than 63 mm of precipitation has occurred. This massive amount of precipitation on the previous day has led to more than 25km2 being flooded in the studied area.
Conclusion
Results showed that meanders and their surrounding areas are the most dangerous sections in terms of flooding. The meander's dynamic and the river's hydrologic processes are essential factors affecting flooding in those sections. Generally, various factors affect flooding and the damage caused by it. This study aimed to determine flooded and flood-prone areas (according to flooded areas in previous events) using new methods in a short time and with high accuracy to use this tool for more accurate zoning and efficient planning in the future. The results showed that radar images are practical, robust, and reliable tools for determining flooded areas, especially for rapid and near-real-time studies of flood events.
Keywords: Floods, Radar images, Sentinel-1Satelitte, Kashkan river



 

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Nowadays, deep learning as a branch of artificial intelligence acts as an alternative for human with hopeful outcomes. Open Street Map as the biggest open source data is used as a complementary data sources for spatial projects. It is notable that is some advanced counties the accuracy of VGI data is higher than governmental official data. This research aims to use artificial intelligence to produce and subsequently promote completeness of OSM data. Res_UNet architecture was utilized to train landuse categories to the network. The result shows that IoU metric is about 83 percent that implies a high accuracy paradigm. Then, united-based method was used to calculated completeness of OSM data. The unit-based results show that completeness of building blocks, forest, fruits garden and agriculture land are: 3.6, 9.7, 90.4 and 81.88 respectively. It shows the low volunteer  participation rate to produce OSM data. On the other side the high accuracy achieved by deep learning leads us to complete OSM data by artificial intelligence instead of human prepared data. The advantage of using machine rather than human may be utilized in undeveloped countries or low density population regions as well as inaccessible areas.