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Hayedeh Ara, Zahra Gohari, Hadi Memarian,
Volume 10, Issue 3 (9-2023)
Volume 10, Issue 3 (9-2023)
Abstract
Introduction
Desertification is one of the major environmental, socio-economic problems in many countries of the world (Breckle, et.al., 2001). Desertification is actually called land degradation in dry, semi-arid and semi-humid areas, the effects of human activities being one of the most important factors (David and Nicholas, 1994). Sand areas are one of the desert landforms, whose progress and development can threaten infrastructure facilities. The timely and correct identification of the changes in the earth's surface creates a basis for a better understanding of the connections and interactions between humans and natural phenomena for better management of resources. To identify land cover changes, it is possible to use multi-temporal data and quantitative analysis of these data at different times (Lu, et.al., 2004), therefore, one of the accurate management tools that causes the application of management based on current knowledge, these studies Monitoring is done using the mentioned data. The use of satellite data and ground information in such studies has caused many temporal and spatial changes of phenomena to be well depicted, which can be beneficial in better understanding and interaction with the environment and ultimately its sustainable management and development. To obtain and extract basic information, the best tool is to use telemetry technologies, which by using satellite data, in addition to reducing costs, increases accuracy and speed, and its importance is increasing day by day in the direction of sustainable development (Alavi Panah, 1385). Since field studies in the field of spatial changes of sandy areas of this city are difficult and expensive to repeat, facilities such as simulating these areas with expert algorithms and artificial intelligence can be used to investigate and monitor critical areas at regular intervals. Accurate and economically appropriate. Therefore, in this research, with the aim of investigating the effectiveness of these models in the periodic changes of the sandy plains of Ferkhes plain, two algorithms, perceptron neural network and random forest, were chosen, and the reason for choosing these models is the ability to model according to the existing uncertainties, interference Fewer users and insensitivity of the model to how the data is distributed.
Materials and Methods
The progress and development of the sandy areas of the Fern Plain depends on three factors, climatic, environmental and human. Therefore, the input variables to the expert and artificial intelligence models were chosen to cover these three factors. Therefore, factors such as drought, the number of dusty days, as well as vegetation index were entered into the model as dynamic variables, and environmental factors such as soil, elevation and altitude, geology, slope and direction were entered into the model as static variables. The statistical period investigated for the changes of wind erosion zones was considered to be 15 years from 2000 to 2015, based on this time base, qualitatively homogeneous and reconstructed meteorological data and images A satellite was selected and processed in 5-year periods (2000, 2005, 2010 and 2015). Modeling of the changes of sandy areas was done using two algorithms of perceptron neural network and random forest in MATLAB software environment. To choose the best neural network structure, a large number of neural networks with different structures were designed and evaluated. These neural networks were built and implemented by changing adjustable parameters (including transfer function, learning rule, number of middle layer, number of neurons of middle layer, number of patterns). One of the most common types of neural networks is multilayer perceptron (MLP). This network consists of an input layer, one or more hidden layers and an output. MLP can be trained by a back propagation algorithm. Typically, MLP is organized as a set of interconnected layers of input, hidden, and output artificial. The accuracy of these networks was checked by the statistical criteria calculated in the test stage, and finally the network that had the closest result to the reality was selected as the main network. The main active function used in this research is sigmoid, which is a logistic function. Then by comparing the network output and the actual output, the error value is calculated, this error is returned in the form of back propagation (BP) in the network to reset the connecting weights of the nodes (Chang and Liao, 2012). Other evaluation indices MSE, RMSE and R were used as network performance criteria in training and validation. The selection of Fern plain as a study area is due to the high potential of this area in the advancement of sand areas, for this purpose, 8 effective factors in the development of these areas were investigated. These factors were entered into the model in the form of three dynamic indices and five static indices.
Results and Discussion
In evaluating the results of modeling algorithms, dynamic variables in all periods were introduced as the most important factors in the occurrence of wind erosion and the advancement of sand areas. The diagram of the importance of predictor variables is presented in Figure 7. The results show that the vegetation cover index ranks first in all periods, the drought index ranks second in 2000 and 2015, and the dust days index ranks third in these two years. Meanwhile, in 2005 and 2010, the dust index and drought index ranked second and third respectively. Among the static variables used in this research, the height digital model variable was ranked fourth in 2000 and 2010, and in 2005 and 2015, geological and soil variables were important. In almost all studied periods, the direction factor is less important than other factors, which can be removed from the set of variables required for modeling to predict sand areas.
Desertification is one of the major environmental, socio-economic problems in many countries of the world (Breckle, et.al., 2001). Desertification is actually called land degradation in dry, semi-arid and semi-humid areas, the effects of human activities being one of the most important factors (David and Nicholas, 1994). Sand areas are one of the desert landforms, whose progress and development can threaten infrastructure facilities. The timely and correct identification of the changes in the earth's surface creates a basis for a better understanding of the connections and interactions between humans and natural phenomena for better management of resources. To identify land cover changes, it is possible to use multi-temporal data and quantitative analysis of these data at different times (Lu, et.al., 2004), therefore, one of the accurate management tools that causes the application of management based on current knowledge, these studies Monitoring is done using the mentioned data. The use of satellite data and ground information in such studies has caused many temporal and spatial changes of phenomena to be well depicted, which can be beneficial in better understanding and interaction with the environment and ultimately its sustainable management and development. To obtain and extract basic information, the best tool is to use telemetry technologies, which by using satellite data, in addition to reducing costs, increases accuracy and speed, and its importance is increasing day by day in the direction of sustainable development (Alavi Panah, 1385). Since field studies in the field of spatial changes of sandy areas of this city are difficult and expensive to repeat, facilities such as simulating these areas with expert algorithms and artificial intelligence can be used to investigate and monitor critical areas at regular intervals. Accurate and economically appropriate. Therefore, in this research, with the aim of investigating the effectiveness of these models in the periodic changes of the sandy plains of Ferkhes plain, two algorithms, perceptron neural network and random forest, were chosen, and the reason for choosing these models is the ability to model according to the existing uncertainties, interference Fewer users and insensitivity of the model to how the data is distributed.
Materials and Methods
The progress and development of the sandy areas of the Fern Plain depends on three factors, climatic, environmental and human. Therefore, the input variables to the expert and artificial intelligence models were chosen to cover these three factors. Therefore, factors such as drought, the number of dusty days, as well as vegetation index were entered into the model as dynamic variables, and environmental factors such as soil, elevation and altitude, geology, slope and direction were entered into the model as static variables. The statistical period investigated for the changes of wind erosion zones was considered to be 15 years from 2000 to 2015, based on this time base, qualitatively homogeneous and reconstructed meteorological data and images A satellite was selected and processed in 5-year periods (2000, 2005, 2010 and 2015). Modeling of the changes of sandy areas was done using two algorithms of perceptron neural network and random forest in MATLAB software environment. To choose the best neural network structure, a large number of neural networks with different structures were designed and evaluated. These neural networks were built and implemented by changing adjustable parameters (including transfer function, learning rule, number of middle layer, number of neurons of middle layer, number of patterns). One of the most common types of neural networks is multilayer perceptron (MLP). This network consists of an input layer, one or more hidden layers and an output. MLP can be trained by a back propagation algorithm. Typically, MLP is organized as a set of interconnected layers of input, hidden, and output artificial. The accuracy of these networks was checked by the statistical criteria calculated in the test stage, and finally the network that had the closest result to the reality was selected as the main network. The main active function used in this research is sigmoid, which is a logistic function. Then by comparing the network output and the actual output, the error value is calculated, this error is returned in the form of back propagation (BP) in the network to reset the connecting weights of the nodes (Chang and Liao, 2012). Other evaluation indices MSE, RMSE and R were used as network performance criteria in training and validation. The selection of Fern plain as a study area is due to the high potential of this area in the advancement of sand areas, for this purpose, 8 effective factors in the development of these areas were investigated. These factors were entered into the model in the form of three dynamic indices and five static indices.
Results and Discussion
In evaluating the results of modeling algorithms, dynamic variables in all periods were introduced as the most important factors in the occurrence of wind erosion and the advancement of sand areas. The diagram of the importance of predictor variables is presented in Figure 7. The results show that the vegetation cover index ranks first in all periods, the drought index ranks second in 2000 and 2015, and the dust days index ranks third in these two years. Meanwhile, in 2005 and 2010, the dust index and drought index ranked second and third respectively. Among the static variables used in this research, the height digital model variable was ranked fourth in 2000 and 2010, and in 2005 and 2015, geological and soil variables were important. In almost all studied periods, the direction factor is less important than other factors, which can be removed from the set of variables required for modeling to predict sand areas.
Sediqeh Mozaffari Qarah Bolagh, Brhrooz Mozaffari Qarah Bolagh, Mehdi Cheraghi,
Volume 10, Issue 3 (9-2023)
Volume 10, Issue 3 (9-2023)
Abstract
Providing food to achieve food security is considered one of the important goals of development in all countries, reducing food insecurity is considered an important political and social achievement for governments. One of the effects of food insecurity in rural areas is the number of patients and deaths caused by the corona epidemic. In this regard, the current research seeks to answer the following questions: What is the level of food insecurity in the studied villages? And what effect does food insecurity have on the spatial distribution of corona patients and deaths? The type of research is applied and descriptive-analytical in nature. The statistical population of this research is all the villages in the central part of Zanjan city, which were surveyed in full. The method of collecting information is in the form of a library and the method of data analysis is in the form of descriptive statistics and spatial analysis. The findings of the research show that the average food insecurity of the studied villages is equal to 36.08%, the highest level of food insecurity is related to Taham district with 40.76% and the lowest level of food insecurity is related to Mirizat district. In order to analyze the effects of food insecurity on the mortality caused by Corona, geographic weighted regression has been used, based on the results obtained from this spatial analysis tool, the width is equal to 0.172, the remaining squares are equal to 2836, the effective number is equal to 16.86, Sigma is equal to 5.64 and the coefficient of determination, which measures the degree of linear relationship between two variables, has been calculated as equal to 0.72, so it can be said that with the increase in food insecurity, the death rate due to Corona will also increase.
Parastou Darouei , Parviz Zeaiean, Farhad Azizpour, Vahid Riahi,
Volume 10, Issue 3 (9-2023)
Volume 10, Issue 3 (9-2023)
Abstract
Introduction
Agricultural activities, as a foundation of growth and development and part of the rural development process, guarantee the economic life of many villages in the country. However, in recent years, other products' water scarcity and resource limitations have affected these activities. This issue has severely challenged the sustainability and life of rural settlements.
In this regard, organizing and developing an optimal cropping pattern is necessary to achieve the goals of sustainable agricultural and rural development in Iran. To achieve this goal, the cultivation of crops must be commensurate with the capabilities of production resources, especially water resources.
Therefore, determining the appropriate spatial distribution of agricultural lands for the cultivation of various crops is one of the primary foundations for implementing optimal cropping pattern. Accordingly, the present study seeks to identify suitable spatial zoning for wheat and barley cultivation as the main crops in agricultural lands in traditional Lenjanat regions, which are exposed to a growing water crisis.
Data and Methodology
According to the main purpose of the research, the data obtained from spatial distribution maps of current cropping patterns and spatial distribution of suitable lands for crop cultivation.
This study prepared the suitability maps of the major agricultural products at a distance of 10 km on both sides of Zayandeh Rud River in Lenjanat region using multi-criteria decision-making methods.
Thus, the agronomic-ecological needs of the two major crops in the area (wheat and barley) were determined, and a standard map for each crop was classified using ArcGIS software. Then, the digital layers were combined by allocating the weight obtained from the Analytical Hierarchy Process and the Simple Additive Weighting method. Finally, talent assessment and land zoning was performed in four categories from unsuitable to very suitable for cultivating wheat and barley crops. Using the analytical hierarchy process method and experts' opinions led to high accuracy results.
Results and Discussion
The results of the land suitability map showed that 90.6% of the agricultural lands in the study area are very suitable and relatively suitable for the cultivation of the wheat crop. The northern and eastern regions, located in Falavarjan county and the north part of Mobarakeh county, are the most suitable areas for wheat cultivation. As we move from the north and east to the west of the study area, the capability areas for wheat cultivation decrease. Limiting factors in these areas are unsuitable soil texture, low temperature, shallow soil, high slope, low rainfall and drainage.
As for barley cultivation, a large part of the area, equal to 30635.3 hectares (more than 91%), is very suitable and relatively suitable. In these areas, in the northern and eastern parts of Lenjanat, unsuitable soil texture, shallow soil, high slope and low drainage are the most critical limiting factors for barley cultivation.
A comparison of "spatial distribution of land suitability" with "spatial distribution of cropping pattern" shows that the crops in this study (wheat and barley) have been cultivated in a suitable area in terms of the ecological potential of lands.
Conclusion
The results of this evaluation can be used in the spatial distribution of the optimal cropping pattern to select a suitable cultivation site for these two crops and other existing and alternative crops.
Wheat and barley are the major crops usually used in planning optimal cropping patterns, regardless of the economic issues. Considering suitable spatial distribution for wheat and barley, they should be distributed in such a way with the slightest difference compared to the current cropping pattern. On the other hand, a large area of the Lenjanat region is suitable for cultivating wheat and barley. In addition, an agricultural unit may have different capacities for other crops, so it is necessary to pay attention to the ecological potential of other crops. Wheat and barley should be cultivated in lands which are unsuitable or semi-suitable for other crops.
Accordingly, it is necessary to provide spatial zoning of existing and alternative crops in the Lenjanat area with fewer water requirements and higher economic benefits to be introduced in the optimal cropping pattern.
In this study, only agronomic-ecological criteria and needs with available data were examined due to data limitations in assessing crop suitability. Therefore, completing land suitability maps by considering more evaluation criteria such as evapotranspiration and the amount of water available is recommended.
Also, to have a "spatial distribution of the optimal cropping pattern", paying attention to the ecological potential of the lands, also considering other criteria and priorities such as natural, socio-cultural, economic and political criteria is necessary. So, we can develop a cropping pattern that provides a basis for desirable space dynamics.
Agricultural activities, as a foundation of growth and development and part of the rural development process, guarantee the economic life of many villages in the country. However, in recent years, other products' water scarcity and resource limitations have affected these activities. This issue has severely challenged the sustainability and life of rural settlements.
In this regard, organizing and developing an optimal cropping pattern is necessary to achieve the goals of sustainable agricultural and rural development in Iran. To achieve this goal, the cultivation of crops must be commensurate with the capabilities of production resources, especially water resources.
Therefore, determining the appropriate spatial distribution of agricultural lands for the cultivation of various crops is one of the primary foundations for implementing optimal cropping pattern. Accordingly, the present study seeks to identify suitable spatial zoning for wheat and barley cultivation as the main crops in agricultural lands in traditional Lenjanat regions, which are exposed to a growing water crisis.
Data and Methodology
According to the main purpose of the research, the data obtained from spatial distribution maps of current cropping patterns and spatial distribution of suitable lands for crop cultivation.
This study prepared the suitability maps of the major agricultural products at a distance of 10 km on both sides of Zayandeh Rud River in Lenjanat region using multi-criteria decision-making methods.
Thus, the agronomic-ecological needs of the two major crops in the area (wheat and barley) were determined, and a standard map for each crop was classified using ArcGIS software. Then, the digital layers were combined by allocating the weight obtained from the Analytical Hierarchy Process and the Simple Additive Weighting method. Finally, talent assessment and land zoning was performed in four categories from unsuitable to very suitable for cultivating wheat and barley crops. Using the analytical hierarchy process method and experts' opinions led to high accuracy results.
Results and Discussion
The results of the land suitability map showed that 90.6% of the agricultural lands in the study area are very suitable and relatively suitable for the cultivation of the wheat crop. The northern and eastern regions, located in Falavarjan county and the north part of Mobarakeh county, are the most suitable areas for wheat cultivation. As we move from the north and east to the west of the study area, the capability areas for wheat cultivation decrease. Limiting factors in these areas are unsuitable soil texture, low temperature, shallow soil, high slope, low rainfall and drainage.
As for barley cultivation, a large part of the area, equal to 30635.3 hectares (more than 91%), is very suitable and relatively suitable. In these areas, in the northern and eastern parts of Lenjanat, unsuitable soil texture, shallow soil, high slope and low drainage are the most critical limiting factors for barley cultivation.
A comparison of "spatial distribution of land suitability" with "spatial distribution of cropping pattern" shows that the crops in this study (wheat and barley) have been cultivated in a suitable area in terms of the ecological potential of lands.
Conclusion
The results of this evaluation can be used in the spatial distribution of the optimal cropping pattern to select a suitable cultivation site for these two crops and other existing and alternative crops.
Wheat and barley are the major crops usually used in planning optimal cropping patterns, regardless of the economic issues. Considering suitable spatial distribution for wheat and barley, they should be distributed in such a way with the slightest difference compared to the current cropping pattern. On the other hand, a large area of the Lenjanat region is suitable for cultivating wheat and barley. In addition, an agricultural unit may have different capacities for other crops, so it is necessary to pay attention to the ecological potential of other crops. Wheat and barley should be cultivated in lands which are unsuitable or semi-suitable for other crops.
Accordingly, it is necessary to provide spatial zoning of existing and alternative crops in the Lenjanat area with fewer water requirements and higher economic benefits to be introduced in the optimal cropping pattern.
In this study, only agronomic-ecological criteria and needs with available data were examined due to data limitations in assessing crop suitability. Therefore, completing land suitability maps by considering more evaluation criteria such as evapotranspiration and the amount of water available is recommended.
Also, to have a "spatial distribution of the optimal cropping pattern", paying attention to the ecological potential of the lands, also considering other criteria and priorities such as natural, socio-cultural, economic and political criteria is necessary. So, we can develop a cropping pattern that provides a basis for desirable space dynamics.
Tajdin Karami, Ali Shamaei, Fateme Mohebi,
Volume 10, Issue 4 (12-2023)
Volume 10, Issue 4 (12-2023)
Abstract
Abstract
Ecological resilience is a concept that implies the reversibility of ecological structures and functions against the shocks experienced. The northern zone of Tehran, as the most important ecological support of this city, has undergone many land-use changes in recent decades. The present study has analyzed the role of land-use change in the ecological resilience of green infrastructure (as one of the pillars of ecological structure) in District 1 of Tehran Municipality. This study is an applied one in terms of purpose and is considered a descriptive-analytical one in terms of the method used. In this study Landsat satellite data (1976-2021) were used to detect the changes of interest, and landscape metrics were used to analyze the ecological resilience conditions. Based on the results of this study period, the Number of Patches (NP) has significantly increased and the Class Area (CA) has decreased during the period covered by this study. These changes indicate the fragmentation process and loss of structural cohesion of the green patches. The measurement results for the connectivity metrics (ENN and GYRATE) also showed a small connectivity between the green patches in the area. In addition, the results for CONTAG (Contagion Landscape metrics) measure indicated that, due to low connectivity, the transmission rate is low. Therefore, it can be said that the green infrastructure of the region has lost its structural cohesion in the face of land-use change, and as a result, the expected ecological functions and services have also failed. According to the results, the green infrastructure of the study area is vulnerable to land-use changes and their ecological resilience has been significantly reduced.
Understanding the mechanism of the atmospheric anomalies governing the summer dust in northeast Iran
Ms. Tahmineh Chehreara, Miss Somayeh Hajivand Paydari,
Volume 10, Issue 4 (12-2023)
Volume 10, Issue 4 (12-2023)
Abstract
Identification of dust centers and, of course, the behavior of this phenomenon in different regions creates one of the problems of the last few decades, which is investigated as a hazard. To this end, statistics from 15 meteorological stations in the northeastern region of Iran, including North Khorasan, Razavi Khorasan, and South Khorasan provinces, were used over a 17-year period (2016-2000). To clarify the mechanisms governing dusty days, the meridional and zonal wind components and geopotential height were obtained by referring to the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR). HYSPLIT model and MODIS AOD values were used to track and identify dust centers. The results showed that during the warm season, due to the establishment of a strong quasi-stationary blocking system in the lower levels of the atmosphere, negative vorticity increased in the maximum air descent area, ultimately leading to the dominance of a northern flow for the region. Anomalies in geopotential height and vorticity were identified, and three dominant abnormal patterns were found in the occurrence of maximum dust storms in the region. An increase in geopotential height of more than 5 to 10 geopotential meters and an increase in negative vorticity are considered major conditions. By examining the tracking model and using satellite data, five main centers that affect over 90% of the region's dust storms were identified, among which Turkmenistan has a significant role with two separate centers and one common center with Uzbekistan in the occurrence of summer dust storms in northeastern Iran.
Arastoo Yari, Mehdi Feyzolahpour, Neda Kanani,
Volume 10, Issue 4 (12-2023)
Volume 10, Issue 4 (12-2023)
Abstract
Earth surface temperature provides important information on the role of land use and land cover on energy balance processes. Therefore, the purpose of this research is to evaluate the LST patterns due to changes in land use (LULC). The studied area is located in Talesh region with an area of 300.6 square kilometers. For this purpose, Landsat images were downloaded in dry and wet seasons from 1365 to 1401. Four user classes were identified by maximum likelihood classification (MLC) and support vector machine (SVM) in 36-year intervals. The Kappa coefficient values for the SVM model were equal to 0.7802 and for the MLC model it was equal to 0.5328. NDVI, NDSI, and NDWI spectral indices were calculated for vegetation, barren soil, and water and were compared with LST in the above years. Changes in land use during the years 1365 to 1401 were an important factor in changes in the temperature of the earth's surface, which averaged from 13.7 degrees Celsius to 39.5 degrees Celsius in the wet season and -0.37 to 41.07 degrees Celsius in the dry season has been variable. Water areas and vegetation have the lowest and barren soil have the highest LST values. The highest negative correlation of -0.74 belongs to the NDVI index in 1365 and the highest positive correlation of 0.79 belongs to the NDSI index in 1365. The area of the forest area has decreased by 20.3% and agricultural land has increased by 217% in 36 years. Barren lands have changed the most and decreased from 2.68 square kilometers to 12 square kilometers. In general, LST has increased due to the increase of human activities such as the expansion of agricultural land and deforestation in the studied period.
Dr Sara Kiani, Dr Morad Kavyani, Dr Amirali Tavasoli,
Volume 10, Issue 4 (12-2023)
Volume 10, Issue 4 (12-2023)
Abstract
The Namak Lake is situated between three provinces: Isfahan, Qom, and Semnan. However, the functioning of Namak Lake and its susceptibility to environmental, ecological, economic, and social influences not only affect the immediate surroundings but also impact other provinces. Naturally, a crisis in this lake can have negative effects on human communities and the residents of the surrounding areas in terms of environmental, economic, and social aspects. Therefore, the aim of this research is to identify the temporal-spatial changes in the salinity of Namak Lake and, subsequently, to investigate and analyze the effects of these changes on the environmental security of the surrounding regions. To achieve this goal, salt zones were identified using soil salinity indices, including the Normalized Difference Salinity Index (NDSI), Salinity Index 1 (SI1), Salinity Index 2 (SI2), and Brightness Index (BI), over a 30-year period (1992-2021) with five-year intervals. Then, using the maximum likelihood method, the salt zones were classified into four land cover types, including water zone, moist zone, salt zone, and other uses. The results of this study indicate that due to the reduction in water inflow into the lake as a result of dam construction in the upstream basin and the effects of climate change, the water zone, or seasonal lake, of Namak Lake has disappeared and the salt zone has expanded in this area. The most significant changes in the lake are related to the northwestern part of the lake, where major rivers such as Jajrood, Shur, Qarechai, and Qamaroud flow into this part of the lake, contributing to its drainage. Therefore, dam construction on these rivers has led to a downward trend in water flow into the lake. Furthermore, the results suggest that due to the absence of settlements and human communities near Namak Lake and the natural and climatic conditions of the region, it is not expected that environmental incidents that could have security and political implications will occur in the short term.
Fahimeh Pourfarrashzadeh, Fariba Beyghipour Motlagh, Mortaza Gharachorlu,
Volume 11, Issue 1 (5-2024)
Volume 11, Issue 1 (5-2024)
Abstract
This study aimed to systematically explain the potential of the landslide occurrence to provide a prediction model of the possibility of this phenomenon in the Yamchi catchment in Ardebil province. In this regard, both approaches of discrete and continuous variables were used by means of overlay and logistic regression, respectively. Independent variables included elevation, slope, aspect, lithology, annual rainfall, roughness, general curvature, topographic wetness index, vegetation index, distance to fault, distance to stream and distance to road. The results, firstly, revealed the areas with high landslide potential by the matching layers of independent variables with the landslide layer in the geographical information system (GIS). These areas were in the middle elevation, high slopes, northern slope, high roughness, erodible formations, high rainfall, medium vegetation, surroundings of faults and rivers. Secondly, the results of the logistics regression model by providing a prediction equation of probability of landslide occurrence showed that the resulting model with pseudo r2 and ROC 0.22 and 0.86, respectively, had good power and efficiency to predict landslide through the catchment. In addition, the resulting beta coefficients for independent variables indicated that the importance of the variables was as follows: vegetation index distance to road, rain, lithology, distance to fault, elevation, topographic wetness index, roughness index, aspect, slope, and distance to river. In the end, the need to pay serious attention to the supporting and protection of vegetation cover of the mid -range and upstream of the catchment was determined because of unstable geomorphic conditions of these areas.
Mrs Mozhgan Shahriyari, Dr Mostafa Karampoor, Dr Hoshang Ghaemi, Dr Dariush Yarahmadi, Dr Mohammad Moradi,
Volume 11, Issue 1 (5-2024)
Volume 11, Issue 1 (5-2024)
Abstract
Flash floods are one of the most dangerous natural events and often cause loss of life and damage to infrastructure and the environment. This research investigated the occurrence of the most intense continuous monthly floods (October-March) from 1989 to 2021. Precipitation data from 115 synoptic stations were selected. Then, the total rainfall of 1 to 9 days was sorted according to intensity. Using Minitab statistical software and the Andersen-Darling index, heavy rains were extracted based on the 95th percentile. Then, based on the criteria of the highest and lowest number of rainy days, the highest and lowest accumulated rainfall, the wettest and driest months were determined. Considering the three criteria of intensity, continuity, and rainfall coverage, the strongest storms in the wettest months were selected. The data used for synoptic analysis include the average sea level pressure data, the height and vertical component of the wind at 500 hPa, the wind and humidity field specific to the pressure levels 925, 850, and 700 hPa, and the horizontal moisture flux values specific to the pressure level 925, 850 and 700 hPa. The probability of the occurrence of atmospheric rivers was identified by the moisture flux extracted from the specific, meridional, and meridional wind components. The results showed that the storms of October 27-31, 2015, November 5-7, 1994, December 12-16, 1991, January 11-15, 2004, February 3-9, 1993, and March 13-15, 1996 were the strongest in the wettest months. During the storms of October, November, February, and March, moisture has been transported from the southwest of the Red Sea by atmospheric rivers to the western, southwestern, southern, and southeastern regions of Iran.
Mousa Kamanroudi Kojouri, Habibolah Fashi, Sgahla Barati Sadeh,
Volume 11, Issue 2 (8-2024)
Volume 11, Issue 2 (8-2024)
Abstract
Developing roads and constructing new highway are urban policices contributing to solve transportation problems in cities. These projects often being passed through urban fabrics, so it is nessessery to buy and demolish buildings from their owners including individuals or governmental and public institutions to imply the projects. However, acquiring land is not an easy task and completing these projects may hit with long-term delays. This paper aimed to analyze the impacts of delaying in constructing Shoosh Highway in Tehran. The investigated impacts originate from land acquisition problems. The research data was obtained from many sources including documents and research reports, a survey, and interviews with Tehran Municipality managers. The One Sample T-Test in SPSS software was performed to analyze the data obtained form the survey. Findings indicate that the residents are often dissatisfied with the project because since the beginning of the project, social security decreased a lot and people are less likely to respect citizens' rights than before, recreational sites are often demolished, the value of residential buildings slowed down significantly, living costs incresed, and businesses were stagnant. In conclusion, if urban highways are not contributing to proper planning and site selection, they will disrupt the physical, social, and economic structures of urban neighborhoods and cause to many environmental problemes including air pollution. To avoid these adverse outcomes, it should be thought in advance about sufficient financial resources and possible practical methods to acquire land for projects. These consequences are reduced by studying and managing the risk of projects.
Negar Hamedi, Ali Esmaeily, Hassan Faramarzi, Saeid Shabani, Behrooz Mohseni,
Volume 11, Issue 2 (8-2024)
Volume 11, Issue 2 (8-2024)
Abstract
Forest fire in many ecosystems is a natural phenomenon, but also a serious and dangerous threat with environmental, ecological, and physical effects. Therefore, this research investigated the risk areas of fire in Zagros forests identification to evaluate the changes in the time series of deals with a potential fire hazard. To achieve this goal fuzzy layers of analysis network process and order weighted average method were used regularly. For this purpose, fire Zagros forests using satellite images Landsat and MODIS Lordegan city in the period between 2000, 2007, and 2014 and the factors affecting fire are examined. The high-risk areas based on classification utility area and the number of zones were identified as fire-prone areas. In the analytical network process procedure, the largest weighs were assigned to the distance from residential areas and roads, GVMI index, and maximum daily air temperature factors which were 0.209, 0.198, 0.09, and 0.0716, respectively. Time series analysis map showing the extent of critical areas from 2000 to 2014 decreased by investigating the factors affecting fire occurrence in critical areas, distance for roads and residential areas, slope, aspect, GVMI index, and NDVI and maximum temperatures have the greatest impact were on fire. The low-risk scenario and a small amount of compensation with the ROC higher than 0.7 as the best model was the estimated risk of forest fires. The preparation of a map of areas susceptible to fire, as well as analyzing and analyzing the time series of factors affecting the fire in different years, is an effective step in helping forest managers to plan and implement preventive operations in high-risk areas.
Omid Ashkriz, Fatemeh Falahati, Amir Garakani,
Volume 11, Issue 3 (12-2024)
Volume 11, Issue 3 (12-2024)
Abstract
The growth of settlements and the increase of human activities in the floodplains, especially the banks of rivers and flood-prone places, have increased the amount of capital caused by this risk. Therefore, it is very important to determine the extent of the watershed in order to increase risk reduction planning, preparedness and response and reopening of this risk. The present study uses the common pattern of the machine and the classification of Sentinel 2 images to produce land cover maps, in order to construct sandy areas and determine land issues affected by the flood of March 2018 in Aqqla city. Also, in order to check and increase the accuracy of the algorithms, three software indices of vegetation cover (NDVI), water areas (MNDWI) and built-up land (NDBI) were used using images. The different sets of setting of each algorithm were evaluated by cross-validation method in order to determine their effect on the accuracy of the results and prevent the optimistic acquisition of spatial correlation from the training and test samples. The results show that the combination of different indices in order to increase the overall accuracy of the algorithms and to produce land cover maps, the forest algorithm is used with an accuracy of 83.08% due to the use of the collection method of higher accuracy and generalizability than compared to. Other algorithms of support vector machine and neural network with accuracy of 79.11% and 75.44% of attention respectively. After determining the most accurate algorithm, the map of flood zones was produced using the forest algorithm in two classes of irrigated and non-irrigated lands, and the overall accuracy of the algorithm in the most optimal models and by combining vegetation indices (MNDWI) was 93.40%. Then, with overlapping maps of land cover and flood plains, the surface of built-up land, agricultural land and green space covered by flood was 4.2008 and 41.0772 square kilometers, respectively.
Mr Mehran Mahmoodi, Dr Tajeddin Karami, Dr Vahid Amini Parsa, Dr Ahmad Zanganeh, Dr Seyed Jalil Alavi,
Volume 11, Issue 3 (12-2024)
Volume 11, Issue 3 (12-2024)
Abstract
This research employs a systematic review approach to comprehensively evaluate environmental inequalities in Middle East cities. The Middle East, due to rapid urbanization and unsustainable development, faces complex environmental challenges that disproportionately affect low-income and marginalized populations. In this study, 60 scientific articles published between 2013 and 2023 from Scopus, Web of Science, and Google Scholar databases were examined. Statistical analyses revealed that environmental inequalities in this region have been exacerbated by weaknesses in coordinated policymaking and cultural-geographical differences. Temporal patterns indicated an increasing trend in these inequalities over the past decade, while thematic analyses uncovered detrimental impacts on public health, air quality, and access to water resources.Geographical assessments demonstrated that specific areas are more vulnerable to environmental hazards due to climatic and economic conditions. By identifying gaps in existing scientific literature and current policies, this research proposes strategies to enhance environmental justice and improve conditions in Middle Eastern cities. The results of this study can serve as a foundation for developing effective policy strategies and future research in the field of environmental justice in the region. By presenting a comprehensive analytical framework, this research contributes to a deeper understanding of the dynamics of environmental inequalities in the Middle East and paves the way for targeted interventions
Arastoo Yari Hesar, Vakil Heidarysarban, Bahram Imani, Samaneh Sarani,
Volume 11, Issue 4 (2-2025)
Volume 11, Issue 4 (2-2025)
Abstract
he spread of Covid-19 in the rural areas of the country has caused more dangers due to the common rural cultures, and the ignorance and lack of efficient management of this crisis in the villages has caused irreparable consequences for these areas. In such cases, the existence of social capital can be very vital in creating national consensus and successful policies to pass this critical stage. Leading research is applied in terms of purpose and based on descriptive-analytical nature. To determine the sample size of villagers, using Cochran's formula, from the total of 6903 households in sample villages, 362 households were calculated as sample households to complete the questionnaire. In order to investigate the effects of social capital on economic and social indicators that are effective in reducing the vulnerability of the outbreak of Covid-19 in the border villages of Sistan, a wide range of indicators was determined, and from the one-sample T-test and the analysis of variance of the regression model to measure the The evaluation of the effects of social capital on socio-economic indicators effective in reducing the vulnerability of the outbreak of Covid-19 in the border villages of Sistan was used. The results of the research showed that the higher the level of people's participation and their trust towards each other, the higher the level of responsibility and knowledge of people, it has a positive role and effect on social and economic indicators in order to reduce the vulnerability of the spread of the covid disease. has had 19
Dr Sayyad Asghari Sarasekanrood, Zahra Sharifi, Zahra Shahbazi,
Volume 11, Issue 4 (2-2025)
Volume 11, Issue 4 (2-2025)
Abstract
Landslides, as one of the most dangerous natural hazards in mountainous regions, continuously threaten human infrastructure, especially roads and transportation routes. Their occurrence often results in significant loss of life and property, making it crucial to study and assess landslide hazards for effective zoning. The purpose of this research is to zone the landslide hazard along the Masal to Gilvan road using a neural network algorithm. The neural network algorithm is recognized as one of the most effective machine learning models, capable of solving complex problems in prediction and classification despite its simplicity. For this zoning analysis, nine influencing factors were considered: (1) geology, (2) vegetation cover, (3) slope, (4) land use, (5) distance from the road, (6) slope aspect, (7) elevation, (8) distance from fault lines, and (9) distance from rivers. The data were prepared, preprocessed, and then entered into MATLAB 2018. A neural network model was designed and implemented with 9 input neurons, 8 hidden neurons, and 1 output neuron. The results indicated that the four most influential factors, ranked by weight, were: slope (0.24), vegetation cover (0.17), distance from fault lines (0.14), and geology (0.11). Final validation using the ROC curve showed that the AUC values were 0.854 for the training phase and 0.971 for the testing phase, both of which reflect highly favorable results. The error rate was found to be very low.
Dr Maryam Ghasemi, Mr Hadi Ebrahimi Darbandi, Mrs Mitra Yarahmadi,
Volume 12, Issue 1 (8-2025)
Volume 12, Issue 1 (8-2025)
Abstract
Drought is one of the most important challenges faced by pastoralists around the world. This phenomenon can have significant negative effects on livestock health, production, and livelihoods. However, pastoralists can adapt to drought and reduce its negative effects by adopting various strategies. Semi-nomadic people in Darbandi, Kalat-Naderi County, have been facing drought since 2007 due to their livestock farming. Since livestock farming has profound impacts on the lifestyle and livelihoods of these communities, the present study examines their experience in facing drought and identifies their management strategies in these conditions. The research method is qualitative and the research tool is in-depth interviews with 20 semi-nomadic people in Darbandi, Kalat-Naderi. Sampling was purposeful and carried out until theoretical saturation was reached to ensure that a wide range of perspectives and experiences were collected. The data from the interviews were analyzed using a qualitative grounded theory approach to extract key patterns and concepts. According to the findings, the semi-nomadic Darbandi people of Kalat County have adopted various strategies in the face of drought, which are classified into four categories: rangeland and grazing management strategies, livestock nutrition management, water consumption management, and livelihood diversification. These results can be used as a basis for formulating better policies in the field of crisis management and rural development. Also, these results can be used for more effective planning to reduce the vulnerability of nomads to drought.
Mehranjani Mohammad Soleimani, Tahereh Nemati, Tajeddin Karami, Ahmad Zanganeh, Taher Parizadi,
Volume 12, Issue 1 (8-2025)
Volume 12, Issue 1 (8-2025)
Abstract
Aging is one of the most prominent indicators of demographic decline that most modern societies experience. At this stage of demographic decline, alongside a decrease and stabilization of mortality rates, birth rates also sharply decline. The development of technology and the mechanization of tasks, the improvement of quality of life and health-related indicators, individual-centered lifestyles, and increased economic inflation are significant factors in this issue. Iran is also among the countries on the verge of entering the stage of demographic decline. However, the intensity of this trend varies in different regions of the country. This article examines and analyzes the state of aging in the neighborhoods of the metropolis of Tehran. This research falls into the category of applied research in terms of purpose and is descriptive-analytical in terms of method. The research is based on the census data from 2016 and utilizes spatial statistical analyses. The positive values of Moran's autocorrelation analysis for each of the indices: aging (0.664), old-age dependency ratio (0.644), youth ratio (0.653), aging ratio (0.664), and aging index (0.665) in the neighborhoods of Tehran indicate a clustered pattern. This means that the issue of aging is more acute in some neighborhoods and areas of Tehran. Accordingly, the density of the elderly population is higher in most neighborhoods of the central and northern parts of the city. The final result shows that the distribution of the elderly space follows the logic of the social macro-ecology of Tehran and is relatively consistent with its natural-social topography. Furthermore, the spatial analysis of aging in the neighborhoods of this city shows that although all neighborhoods generally grapple with the issue of aging, planning and management should be based on the patterns and nature of the spatial distribution of this issue.
Saeid Shabani, Behrooz Mohseni, Aiding Kornejady, Akram Ahmadi, Hassan Faramarzi, Esmaeil Silakhori,
Volume 12, Issue 1 (8-2025)
Volume 12, Issue 1 (8-2025)
Abstract
Deforestation is one of the primary challenges and environmental threats facing forest ecosystems, including the Hyrcanian forests, and occurs under the influence of various natural and anthropogenic drivers. This study aimed to model the probability of deforestation occurrence within the Loveh forest management district located in northern Iran. The dataset comprised 104 documented deforestation points and 14 explanatory variables, derived through spatial analysis using GIS and environmental, topographic, and anthropogenic data. To assess the relationships among variables and predict the likelihood of deforestation, two statistical models were employed: logistic regression and the Generalized Additive Model (GAM). The results revealed that the GAM outperformed the logistic regression model, achieving a higher Kappa coefficient (0.84) and Area Under the Curve (AUC) value (0.956), and providing a more realistic spatial distribution of deforestation risk. The most influential variables included distance from roads, slope, wind effect, and elevation. Based on the GAM output, approximately 20% of the study area was categorized as high and very high risk. These findings underscore the pivotal role of access infrastructure, human pressure, and climatic factors in accelerating deforestation processes. The results of this study can serve as a scientific basis for prioritizing conservation interventions, reassessing road development policies, and enhancing spatial planning for sustainable forest management in northern Iran.
Mis Vajihe Gholizade, Dr Amir Saffari, Dr Ali Ahmadabadi, Dr Amir Karam,
Volume 12, Issue 46 (9-2025)
Volume 12, Issue 46 (9-2025)
Abstract
Introduction: Assessing the vulnerability and pollution of the aquifer is necessary for the management, development and allocation of land use, quality monitoring, prevention and protection of groundwater pollution. The purpose of this research is to identify and analyze the qualitative vulnerability of the Mashhad plain aquifer in order to monitor and manage underground water resources and prevent its future pollution.
Methodology: Mashhad plain is located in the northeast of Iran between Binaloud and Hezarmasjed mountains and in the watershed of the Kasfroud river, and its area is 2527 square kilometers. In this research, the vulnerability of the Mashhad Plain aquifer was evaluated with DRASTIC and SI models, and ArcGIS was used to analyze the parameters and prepare the vulnerability map. DRASTIC model is one of the overlap and index methods. In this method, the seven measurable parameters for the hydrogeological system include the depth of the groundwater level(D), net recharge(R), aquifer environment(A), soil environment(S), topography(T), Impact of the unsaturated Zone(I) and hydraulic conductivity(C) is used. The ratings for the sub-layers of each criterion vary from one to ten depending on their impact on the vulnerability potential. In SI method, five parameters of groundwater depth(D), net recharge (R), aquifer lithology(A), topography(T) and landuse(LU) are used for aquifer vulnerability. After preparing the SI model layers and weighting each of the layer classes using the functions available in the ArcGIS, the sensitivity index is obtained from the weighted sum of the mentioned parameters.
Conclusion: Study area is divided into four zones with very low vulnerability(21.85%), low(32.09%), medium to low(31.05%) and medium to high vulnerability(14.59%). Also, based on the results of the SI model, the study area is divided into five areas with very low vulnerability(0.4%), low(24.63%), medium to low(23.98%), medium to high(18.71%) and high vulnerability(32.25%). In general, the vulnerability of the aquifer increases from the southeast to the northwest.For verification, statistical method and calculation of correlation coefficient between vulnerability maps and TDS layer was used in TerrSet software and the results showed that both DRASTIC and SI models have high accuracy in zoning the vulnerability of Mashhad plain aquifer, so that the correlation coefficient of vulnerability maps with index The quality of TDS in Drastic model is (0.996) and in SI model (0.995); Therefore, the results of the following research can be used in environmental assessments and analysis of various pollutions and can be used as a basis for management decisions.
Dr Saeedmohammad Sabouri, Dr Sayed Amirhossien Garakani,
Volume 12, Issue 46 (9-2025)
Volume 12, Issue 46 (9-2025)
Abstract
Objective: Investigating the occurrence of land subsidence in the country and the extent to which rural settlements are exposed to the phenomenon of land subsidence. Methods: The present study was based on library surveys and studies, field observations and impressions. Using information received from the National Mapping Organization, a map of the country's subsidence zones and the degree of risk of each zone, including very low, low, medium, high and very high risk, was drawn, and the aforementioned maps were compared with the location of the villages. Results: According to the analysis of the available data, 302 villages are at very high risk, 768 villages are at high risk, 834 villages are in the medium risk zone, and 573 villages are in the low risk zone. In terms of percentage weight, about 4 percent of the country's villages are at medium to very high risk of subsidence, of which 1,904 villages are at medium to very high risk, and 573 villages are at low risk. Conclusions: The highest provincial distribution of villages at risk of subsidence in the country with a very high degree is in the provinces of Alborz, Tehran, Khorasan Razavi, Qazvin, Kerman, Golestan and Hamedan, and the highest provincial distribution with a high degree is in the provinces of West Azerbaijan, Isfahan, Alborz, Tehran, Khorasan Razavi, Semnan, Qazvin, Kerman, Golestan, East Azerbaijan, Hamedan and Yazd. Also, the highest provincial distribution of villages at risk of medium-level subsidence is in the provinces of East and West Azerbaijan, Isfahan, Alborz, Tehran, Semnan, Qazvin, Kerman, Golestan, Mazandaran, Markazi, Hormozgan, Hamedan, and Yazd.
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