National Geographical Organization Scientific- Research Quarterly of Geographical Data (SEPEHR) 2588-3860 33 132 2025 02 19 Investigating the effect of the processing method and accurate ground control points on the quality of the digital surface model obtained from UAV Images in forest areas Investigating the effect of the processing method and accurate ground control points on the quality of the digital surface model obtained from UAV Images in forest areas 7 24 713906 10.22131/sepehr.2024.2020063.3051 FA Hava Hasanvand PhD student in forestry, Faculty of natural resources, Sari University of agricultural sciences and natural resources, Sari, Iran 0009-0002-3286-288X Hassan Akbari Associate professor Department of forestry,Faculty of natural resources, Sari University of agricultural sciences and natural resources, Sari, Iran 0000-0002-5482-5521 Shaban Shataee Professor, Department of forestry, Gorgan University of agricultural sciences and natural resources, Gorgan, Iran 0000-0002-3868-8475 Majid Lotfalian Professor, Department of forestry, Faculty of natural resources, Sari University of agricultural sciences and natural resources, Sari, Iran 0000-0002-3868-8475 Alireza Hoseinpour Ph.D. in forestry, Sari University of agricultural sciences and natural resources ,Sari, Iran 0009-0002-4434-6815 Journal Article 2024 01 10 Extended Abstract Introduction One of the road quality control methods is the management and planning system based on the use of UAV, which, in addition to being comprehensive, highly accurate, very low-cost, and of course fast, compared to the old methods where the road surface is measured by workers and experts technical and is done in the form of on-site and field visit, it is much more economical (Zhang et al., 2015:38). (Jafari et al., 1401:2) evaluated the accuracy of the longitudinal profile of the road using the UAV system and mapping cameras. The results of the research showed that the digital model of the surface obtained by overlapping the UAV images is capable of evaluating the accuracy of the longitudinal profile of the road and the quality of the images taken by the UAV is very high and provides better and more details and saves time. Forlani et al., 2022:13 evaluated the influence of ground and aerial control points and their quality on the accuracy of the 3D model obtained from the UAV in the southern part of the University of Parma campus. The results showed that by increasing the quality of the coordinates of the lens centers, the accuracy of the 3D point increases, and the height accuracy of the 3D model of the surface increases twice if a ground control point is added. Due to the great importance of forest roads for optimal management and exploitation of forests, new methods should be sought using remote sensing capabilities. Due to being expensive and time-consuming, traditional methods increase the measurement error and decrease the accuracy in the preparation of information and data obtained at the network and research levels. The use of remote sensing data and drone images with high spatial resolution reduces the cost and facilitates the monitoring of the condition of forest roads. The purpose of this research is to use the images received by Phantom 3 UAV and ground control points with different numbers and distribution as well as without ground control points to check and measure the technical and geometric characteristics of roads and also compare the effect of DSM production quality processing method on The improvement of the quality of the digital model of the earth is the result of UAV images. Materials and Methods UAV images in suitable weather conditions with a flight height of 100 meters from the ground, overlap length of 85% and width of 75%, and a speed of 5 meters per second by the Quadcopter Phantom 3 Pro UAV in the winter season and the condition of forest trees without leaves in January 2023 in a part of The area of Darabkola forests, about 2 km long and 200 meters wide around the road, was received in three separate flight projects during different days. In this research, first, the detailed field measurements of the depth and width of some technical specifications and geometry of forest roads (side channels, gabions, and ditches), surface defects of roads (potholes), and waterways leading to the roads were measured with precise meters and the location of the measurement points was done with DGPS. In addition, several ground control points were made for accurate georeferencing of images and preparation of accurate and integrated orthophoto mosaics of the area using differential GPS and processed using the PPK method. Digital surface models of the region in several modes in the form of processed images in two processing methods with high and medium quality, without accurate GCPs and using accurate GCPs and separate and integrated flight projects were prepared, and technical specifications were extracted from the obtained models and compared with ground observations. Results and Discussion The results of the whole area with quality control points (high and medium) compared to the whole area without quality control points (high and medium) showed that the square root of the average error is lower and has the best height accuracy. Ground control points should be evenly distributed throughout the study area (ideally in the form of a triangulated grid). In this case, the maximum distance of each control point to other control points will be as small as possible. For a certain number of control points, the accuracy obtained by using an optimal distribution was twice better than when the control points had an inappropriate distribution. The best results for accuracy were obtained by considering the control points in the present study. These results are with the studies of Heydari Mozafar et al. (1401:3), Ghafari Thabit et al. (2018: 6), Abbaspour et al. (2017: 4), Zhang et al. (2015: 38) and Rock et al. (2022: 34) are consistent. Also, flight plan areas 1, 2, and 3 with quality control points (high and medium) have a lower mean square root of error than flight plan areas 1, 2, and 3 without quality control points (high and medium). The dispersion of ground control points is more effective than the number of ground control points on the accuracy of the 3D surface model. These findings are in agreement with the results of some researchers, including Ruzgienė et al. (2015: 33), and Gindraux et al. (2017:16) who concluded in their studies that proper distribution of control points has a significant effect on the accuracy of the 3D model up to a certain range Is Consistent. The addition of control points of the flight plan area 1, 2, and 3 in the present study increased the accuracy of the 3D model In this regard Forlaniet al (2022:13) Adding a ground control point roughly doubles the elevation accuracy of the 3D surface model, noted. Conclusion The results showed that the DSM produced from UAV images could extract some technical and geometrical characteristics of forest roads. Overall, the results of the surveys showed that the DSM generated from drone imagery is capable of extracting some technical and geometrical specifications of forest roads and forest land micro topography, but requires the use of precise ground control points and high-quality image processing. Extended Abstract Introduction One of the road quality control methods is the management and planning system based on the use of UAV, which, in addition to being comprehensive, highly accurate, very low-cost, and of course fast, compared to the old methods where the road surface is measured by workers and experts technical and is done in the form of on-site and field visit, it is much more economical (Zhang et al., 2015:38). (Jafari et al., 1401:2) evaluated the accuracy of the longitudinal profile of the road using the UAV system and mapping cameras. The results of the research showed that the digital model of the surface obtained by overlapping the UAV images is capable of evaluating the accuracy of the longitudinal profile of the road and the quality of the images taken by the UAV is very high and provides better and more details and saves time. Forlani et al., 2022:13 evaluated the influence of ground and aerial control points and their quality on the accuracy of the 3D model obtained from the UAV in the southern part of the University of Parma campus. The results showed that by increasing the quality of the coordinates of the lens centers, the accuracy of the 3D point increases, and the height accuracy of the 3D model of the surface increases twice if a ground control point is added. Due to the great importance of forest roads for optimal management and exploitation of forests, new methods should be sought using remote sensing capabilities. Due to being expensive and time-consuming, traditional methods increase the measurement error and decrease the accuracy in the preparation of information and data obtained at the network and research levels. The use of remote sensing data and drone images with high spatial resolution reduces the cost and facilitates the monitoring of the condition of forest roads. The purpose of this research is to use the images received by Phantom 3 UAV and ground control points with different numbers and distribution as well as without ground control points to check and measure the technical and geometric characteristics of roads and also compare the effect of DSM production quality processing method on The improvement of the quality of the digital model of the earth is the result of UAV images. Materials and Methods UAV images in suitable weather conditions with a flight height of 100 meters from the ground, overlap length of 85% and width of 75%, and a speed of 5 meters per second by the Quadcopter Phantom 3 Pro UAV in the winter season and the condition of forest trees without leaves in January 2023 in a part of The area of Darabkola forests, about 2 km long and 200 meters wide around the road, was received in three separate flight projects during different days. In this research, first, the detailed field measurements of the depth and width of some technical specifications and geometry of forest roads (side channels, gabions, and ditches), surface defects of roads (potholes), and waterways leading to the roads were measured with precise meters and the location of the measurement points was done with DGPS. In addition, several ground control points were made for accurate georeferencing of images and preparation of accurate and integrated orthophoto mosaics of the area using differential GPS and processed using the PPK method. Digital surface models of the region in several modes in the form of processed images in two processing methods with high and medium quality, without accurate GCPs and using accurate GCPs and separate and integrated flight projects were prepared, and technical specifications were extracted from the obtained models and compared with ground observations. Results and Discussion The results of the whole area with quality control points (high and medium) compared to the whole area without quality control points (high and medium) showed that the square root of the average error is lower and has the best height accuracy. Ground control points should be evenly distributed throughout the study area (ideally in the form of a triangulated grid). In this case, the maximum distance of each control point to other control points will be as small as possible. For a certain number of control points, the accuracy obtained by using an optimal distribution was twice better than when the control points had an inappropriate distribution. The best results for accuracy were obtained by considering the control points in the present study. These results are with the studies of Heydari Mozafar et al. (1401:3), Ghafari Thabit et al. (2018: 6), Abbaspour et al. (2017: 4), Zhang et al. (2015: 38) and Rock et al. (2022: 34) are consistent. Also, flight plan areas 1, 2, and 3 with quality control points (high and medium) have a lower mean square root of error than flight plan areas 1, 2, and 3 without quality control points (high and medium). The dispersion of ground control points is more effective than the number of ground control points on the accuracy of the 3D surface model. These findings are in agreement with the results of some researchers, including Ruzgienė et al. (2015: 33), and Gindraux et al. (2017:16) who concluded in their studies that proper distribution of control points has a significant effect on the accuracy of the 3D model up to a certain range Is Consistent. The addition of control points of the flight plan area 1, 2, and 3 in the present study increased the accuracy of the 3D model In this regard Forlaniet al (2022:13) Adding a ground control point roughly doubles the elevation accuracy of the 3D surface model, noted. Conclusion The results showed that the DSM produced from UAV images could extract some technical and geometrical characteristics of forest roads. Overall, the results of the surveys showed that the DSM generated from drone imagery is capable of extracting some technical and geometrical specifications of forest roads and forest land micro topography, but requires the use of precise ground control points and high-quality image processing.

https://www.sepehr.org/article_713906_32e86b59df61e6f759fee355292841a6.pdf

National Geographical Organization Scientific- Research Quarterly of Geographical Data (SEPEHR) 2588-3860 33 132 2025 02 19 Modeling of ionosphere TEC using gated recurrent unit neural network model and comparison against other models Modeling of ionosphere TEC using gated recurrent unit neural network model and comparison against other models 25 43 715635 10.22131/sepehr.2024.2005444.2989 FA Seyyed Reza Ghaffari-Razin Associate professor,, Department of surveying engineering, Faculty of geoscience engineering, Arak University of Technology 0000-0002-5579-5889 Navid Hooshangi Assistant professor, ,Department of surveying engineering, Faculty of geoscience engineering, Arak University of Technology 0000-0001-9929-8908 Journal Article 2023 07 01 Extended Abstract Introduction: The ionosphere is a layer of the earth's atmosphere that extends from an altitude of 80 km to more than 1000 km above the earth. Due to its electrical properties, this layer of the atmosphere has very important and fundamental effects on the waves passing through it. The ionosphere exhibits temporary and intermittent variations such as daily, 27-day, seasonal, six-monthly, annual and 11-year changes. Ionosphere disturbances can cause distance error, cycle slips and phase fluctuations of satellite systems signals, which leads to degradation of the performance, accuracy and reliability of these systems. A parameter that can be used to study the ionosphere is the total electron content (TEC). This parameter is the sum of free electrons in a cylinder with a cross section of one square meter between the satellite and the receiver in the ground and its unit is ele./m2. If the TEC is along the vertical (zenith direction), it is called VTEC. Usually, TEC is expressed in terms of TECU, which is equal to 1016 ele/m2. Various methods have been developed to model the TEC. The simplest and at the same time the most practical method is to use observations of two-frequency receivers. If there is a proper station distribution, it is possible to obtain accurate TEC and model the ionosphere. Materials & Methods In this paper, the idea of using the gated recurrent unit (GRU) for spatio-temporal modeling of the ionospheric total electron content (TEC) is proposed as a new model. In this type of neural network model, unlike normal neural networks, there is no gradient vanishing problem and it is very simple in terms of computations. The efficiency of the new model has been evaluated using the observations of 15 global positioning system (GPS) stations in the northwest of Iran. To calculate the accuracy of the GRU model, two interior and three exterior control stations are considered. It should be noted that the training of GRU model is done using the parameters of longitude and latitude of the GPS station, day of year (DOY), time (universal time), geomagnetic indices AP, KP and DST and solar activity index (F10.7). Also, the TEC in the direction of the zenith (VTEC) related to the input parameters are considered as the desired output. The results of the new model are compared with the results of artificial neural network (ANN), global ionosphere maps (GIM) and IRI2016 model. Also, the effect of the modeled TEC in precise point positioning (PPP) has been investigated. Results & Discussion After training ANN and GRU models and selecting the optimal structure, these models can be used to estimate of VTEC. In this step, with the trained models, the VTEC is estimated at interior control stations and compared with the VTEC obtained from GPS. In the evaluation step of interior control stations, the averaged value of root mean square error (RMSE) of ANN, GRU, GIM and IRI models is to 2.42, 1.76, 3.02 and 6.91 TECU, respectively. Also, the averaged relative error of the models is 12.93%, 10.75%, 16.82% and 26.56%, respectively. In the control stations outside the GPS network area (exterior control stations), two scenarios were investigated: using the observations of these stations in the training step and not using the observations in the training. The evaluations showed that if the observations of exterior control stations are used in the training step of ANN and GRU models, the error of these models will be reduced. In all three exterior control stations, the accuracy of GRU model was higher than other models. The analysis of positioning error by PPP method also showed that by using the GRU model, positioning accuracy has improved by 7 to 45 mm. After evaluating the accuracy of the new model in interior and exterior control stations, the VTEC time series is estimated with the new model and compared with the time series obtained from other models and GPS. This comparison showed that the time series obtained from the GRU model correctly models the VTEC variations in both high and low solar and geomagnetic activities. Conclusion In this paper, the gated recurrent unit (GRU) neural network model was used for the first time in Iran for the spatio-temporal modeling of the total electron content of the ionosphere. In this model, unlike standard neural network models, there is no gradient vanishing problem, and as a result, the computation speed and accuracy of the model have increased. The results of this paper showed that the GRU model has the ability to estimate the spatio-temporal variations of VTEC with very high accuracy and can replace global and empirical models in the study area of this research. Extended Abstract Introduction: The ionosphere is a layer of the earth's atmosphere that extends from an altitude of 80 km to more than 1000 km above the earth. Due to its electrical properties, this layer of the atmosphere has very important and fundamental effects on the waves passing through it. The ionosphere exhibits temporary and intermittent variations such as daily, 27-day, seasonal, six-monthly, annual and 11-year changes. Ionosphere disturbances can cause distance error, cycle slips and phase fluctuations of satellite systems signals, which leads to degradation of the performance, accuracy and reliability of these systems. A parameter that can be used to study the ionosphere is the total electron content (TEC). This parameter is the sum of free electrons in a cylinder with a cross section of one square meter between the satellite and the receiver in the ground and its unit is ele./m2. If the TEC is along the vertical (zenith direction), it is called VTEC. Usually, TEC is expressed in terms of TECU, which is equal to 1016 ele/m2. Various methods have been developed to model the TEC. The simplest and at the same time the most practical method is to use observations of two-frequency receivers. If there is a proper station distribution, it is possible to obtain accurate TEC and model the ionosphere. Materials & Methods In this paper, the idea of using the gated recurrent unit (GRU) for spatio-temporal modeling of the ionospheric total electron content (TEC) is proposed as a new model. In this type of neural network model, unlike normal neural networks, there is no gradient vanishing problem and it is very simple in terms of computations. The efficiency of the new model has been evaluated using the observations of 15 global positioning system (GPS) stations in the northwest of Iran. To calculate the accuracy of the GRU model, two interior and three exterior control stations are considered. It should be noted that the training of GRU model is done using the parameters of longitude and latitude of the GPS station, day of year (DOY), time (universal time), geomagnetic indices AP, KP and DST and solar activity index (F10.7). Also, the TEC in the direction of the zenith (VTEC) related to the input parameters are considered as the desired output. The results of the new model are compared with the results of artificial neural network (ANN), global ionosphere maps (GIM) and IRI2016 model. Also, the effect of the modeled TEC in precise point positioning (PPP) has been investigated. Results & Discussion After training ANN and GRU models and selecting the optimal structure, these models can be used to estimate of VTEC. In this step, with the trained models, the VTEC is estimated at interior control stations and compared with the VTEC obtained from GPS. In the evaluation step of interior control stations, the averaged value of root mean square error (RMSE) of ANN, GRU, GIM and IRI models is to 2.42, 1.76, 3.02 and 6.91 TECU, respectively. Also, the averaged relative error of the models is 12.93%, 10.75%, 16.82% and 26.56%, respectively. In the control stations outside the GPS network area (exterior control stations), two scenarios were investigated: using the observations of these stations in the training step and not using the observations in the training. The evaluations showed that if the observations of exterior control stations are used in the training step of ANN and GRU models, the error of these models will be reduced. In all three exterior control stations, the accuracy of GRU model was higher than other models. The analysis of positioning error by PPP method also showed that by using the GRU model, positioning accuracy has improved by 7 to 45 mm. After evaluating the accuracy of the new model in interior and exterior control stations, the VTEC time series is estimated with the new model and compared with the time series obtained from other models and GPS. This comparison showed that the time series obtained from the GRU model correctly models the VTEC variations in both high and low solar and geomagnetic activities. Conclusion In this paper, the gated recurrent unit (GRU) neural network model was used for the first time in Iran for the spatio-temporal modeling of the total electron content of the ionosphere. In this model, unlike standard neural network models, there is no gradient vanishing problem, and as a result, the computation speed and accuracy of the model have increased. The results of this paper showed that the GRU model has the ability to estimate the spatio-temporal variations of VTEC with very high accuracy and can replace global and empirical models in the study area of this research.

https://www.sepehr.org/article_715635_6fc39e11d7ad8d8a01c71aaaef096989.pdf

National Geographical Organization Scientific- Research Quarterly of Geographical Data (SEPEHR) 2588-3860 33 132 2025 02 19 Evaluation of seismic risk and structural and population vulnerability a case study of Haji Abad city - Hormozgan Province Evaluation of seismic risk and structural and population vulnerability a case study of Haji Abad city - Hormozgan Province 45 64 716041 10.22131/sepehr.2024.2020908.3052 FA Maryam Mirshekarpour M.Sc. Student in Geographic Information System, Graduate University of Advanced Technology, Kerman, Kerman, Iran 0009-0002-2959-9734 Reza Hassanzadeh Assistant professor, Department of Ecology, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran 0000-0002-4567-4450 Amin Hossinpour Assistant professor ,Department of Surveying, Graduate University of Advanced Technology, Kerman, Iran 0009-0006-6782-0654 Journal Article 2024 01 26 Extended Abstract Introduction Earthquake is one of the natural disasters that occurs suddenly and directly affects human life and urban and rural environment. Among the earthquake damages, we can mention human casualties, destruction of buildings and bridges, accumulation of building debris in the boundaries of roads and streets, destruction of electric poles, disruption of movement in the transportation system (Rikalovic, 2014). In order to determine the level of earthquake risk in a region, conducting seismicity studies has a high priority. Also, in order to identify vulnerable places in a city in order to make major decisions in the field of building improvement and retrofitting, it is necessary to carry out structural and demographic seismic vulnerability research (Ansal et al., 2009; Coburn & Spence, 2002). The occurrence of severe earthquakes in the region (two earthquakes with a magnitude of 6.4 and 6.3 on the Richter scale on November 14, 2021 near the city of Fin, Hormozgan province) and the presence of active faults such as Main Zagros and Zagros Trust in the vicinity of Haji Abad city showed the region is exposed to the vey high risk of an earthquake occurnece that can cause the destruction of buildings and population losses in this city. Therefore, the purpose of this research is to assess the seismic risk, buildings and population vulnerability of the city due to a probable earthquake in order to determine the vulnerable areas against earthquake hazard. Materials & Methods In order to carry out this research, geological, topographical and hydrological data and demographic data were collected from related organizations in Hajiabad city. Based on field studies, the number of buildings and the type of structures in each neighborhood were collected, and a map of the distribution of buildins and their types was depicted. Then, these data were prepared in the GIS system and prioritized and weighted using multi-criteria decision-making methods such as Analytical Network Process (ANP) and Fuzzy Logic. The sub-geological criteria include: distance from the fault, thickness of alluvium and the type of soil and sediments, hydrology includes: depth of underground water and topography includes: slope and irregularity of topography. After weighting these criteria and sub-criteria of each, they were ombined using weighted linear combination (WLC) method, and an earthquake hazard map considering an earthquake scenario with a magnitude of 1.7 on the Richter scale was produced in the city. Later, the degree of buildings vulnerability based on the fragility curves that were developed based on past research in Iran were estimated in the classes of without destruction to completely collopsed, and the vulnerability of the population was calculated based on the statistics of the Bam earthquake in the classes of the number of healthy people, injured, injured and hospitalized, and dead people. Results & Discussion The results of seismic microzonation map showed that 3.68 square kilometers of the city is in a very high risk area. Then, based on building vulnerability assessment methods and fragility curves, the destruction level of buildings in the city was evaluated, and it was found that due to an earthquake with a magnitude of 7.1 on the Richter scale, about 80% of the buildings in the city were destroyed over 70% destruction level, and about 11,000 people from the city's population were seriously injured or killed as a result of this earthqauke occurence. Conclusion According to the results of this research, we found that the city of Hajiabad is surrounded by two main faults inclusing Main Zagros and the Trust Zagros faults, which has made it impossible to imagine any safe area in the city. On the other hand, the increase in population and urbanization has caused the extensive development of the city. Therefore, we need efficient disaster and urban management from the relevant organizations to prevent damage and overcome these crises. These measures inculdes rehabilitating worn-out buildings with low-quality materials, preventing construction in the high-risk areas of the city, making suitable plans to increase the resistancy against earthquakes in the city. Moreover, in order to increase security and speed up relief and response operations, in the areas where the risk is very high, according to the regulations, medical and fire stations should be built. In the vulnerable areas of the city where the population density is high, parks and open spaces should be built for temporary and safe accommodation after the earthquake. Therefore, the results of this research can help experts and urban planners in the field of urban management and crisis management to implement macro policies to reduce the risk of earthquakes, improve preparedness against earthquakes, and prioritize the retrofitting of buildings in this city. Extended Abstract Introduction Earthquake is one of the natural disasters that occurs suddenly and directly affects human life and urban and rural environment. Among the earthquake damages, we can mention human casualties, destruction of buildings and bridges, accumulation of building debris in the boundaries of roads and streets, destruction of electric poles, disruption of movement in the transportation system (Rikalovic, 2014). In order to determine the level of earthquake risk in a region, conducting seismicity studies has a high priority. Also, in order to identify vulnerable places in a city in order to make major decisions in the field of building improvement and retrofitting, it is necessary to carry out structural and demographic seismic vulnerability research (Ansal et al., 2009; Coburn & Spence, 2002). The occurrence of severe earthquakes in the region (two earthquakes with a magnitude of 6.4 and 6.3 on the Richter scale on November 14, 2021 near the city of Fin, Hormozgan province) and the presence of active faults such as Main Zagros and Zagros Trust in the vicinity of Haji Abad city showed the region is exposed to the vey high risk of an earthquake occurnece that can cause the destruction of buildings and population losses in this city. Therefore, the purpose of this research is to assess the seismic risk, buildings and population vulnerability of the city due to a probable earthquake in order to determine the vulnerable areas against earthquake hazard. Materials & Methods In order to carry out this research, geological, topographical and hydrological data and demographic data were collected from related organizations in Hajiabad city. Based on field studies, the number of buildings and the type of structures in each neighborhood were collected, and a map of the distribution of buildins and their types was depicted. Then, these data were prepared in the GIS system and prioritized and weighted using multi-criteria decision-making methods such as Analytical Network Process (ANP) and Fuzzy Logic. The sub-geological criteria include: distance from the fault, thickness of alluvium and the type of soil and sediments, hydrology includes: depth of underground water and topography includes: slope and irregularity of topography. After weighting these criteria and sub-criteria of each, they were ombined using weighted linear combination (WLC) method, and an earthquake hazard map considering an earthquake scenario with a magnitude of 1.7 on the Richter scale was produced in the city. Later, the degree of buildings vulnerability based on the fragility curves that were developed based on past research in Iran were estimated in the classes of without destruction to completely collopsed, and the vulnerability of the population was calculated based on the statistics of the Bam earthquake in the classes of the number of healthy people, injured, injured and hospitalized, and dead people. Results & Discussion The results of seismic microzonation map showed that 3.68 square kilometers of the city is in a very high risk area. Then, based on building vulnerability assessment methods and fragility curves, the destruction level of buildings in the city was evaluated, and it was found that due to an earthquake with a magnitude of 7.1 on the Richter scale, about 80% of the buildings in the city were destroyed over 70% destruction level, and about 11,000 people from the city's population were seriously injured or killed as a result of this earthqauke occurence. Conclusion According to the results of this research, we found that the city of Hajiabad is surrounded by two main faults inclusing Main Zagros and the Trust Zagros faults, which has made it impossible to imagine any safe area in the city. On the other hand, the increase in population and urbanization has caused the extensive development of the city. Therefore, we need efficient disaster and urban management from the relevant organizations to prevent damage and overcome these crises. These measures inculdes rehabilitating worn-out buildings with low-quality materials, preventing construction in the high-risk areas of the city, making suitable plans to increase the resistancy against earthquakes in the city. Moreover, in order to increase security and speed up relief and response operations, in the areas where the risk is very high, according to the regulations, medical and fire stations should be built. In the vulnerable areas of the city where the population density is high, parks and open spaces should be built for temporary and safe accommodation after the earthquake. Therefore, the results of this research can help experts and urban planners in the field of urban management and crisis management to implement macro policies to reduce the risk of earthquakes, improve preparedness against earthquakes, and prioritize the retrofitting of buildings in this city.

https://www.sepehr.org/article_716041_fe96f675ed4dbff64c2853fecc6fb76b.pdf

National Geographical Organization Scientific- Research Quarterly of Geographical Data (SEPEHR) 2588-3860 33 132 2025 02 19 Evaluation of destruction of historical cities and ancient monuments due to earthquakes using radar images and interferometric techniques - Study area: the ancient province of Gaziantep, Türkiye Evaluation of destruction of historical cities and ancient monuments due to earthquakes using radar images and interferometric techniques - Study area: the ancient province of Gaziantep, Türkiye 65 83 719776 10.22131/sepehr.2025.2014531.3031 FA Leily Zamany Master's student of Faculty of Civil, Water and environmental engineering, Shahid Beheshti University of Tehran 0009-0005-2348-9499 Saied Sadeghian Associate professor of Faculty of Civil, Water and environmental engineering, Shahid Beheshti University of Tehran 0000-0002-9566-172X Journal Article 2023 11 24 Extended Abstract Introduction Ancient cities and cultural heritage are the lasting works of past generations that make us familiar with our identity, so our duty in the present era is to preserve these precious treasures and take care of them. Buildings undergo frequent changes and damages over time. Therefore, in this article, we decided to monitor the changes and destruction of one of the important ancient provinces of Turkey, named Ghazi Ayantep. The method that was used in this research is the radar interferometric method which was obtained by using the radar data of Sentinel 1 satellite and processing them in Snap software. In the first stage, four images were collected in a period of 24 days before and after the earthquake and about 9 aftershocks at very close distances from the Sentinel 1 satellite. Points to Anatolian faults have subsided more than half a meter. The information obtained from the Geological Organization of Turkey and the images obtained from the map of the affected areas in this province provided by the United Nations Satellite Center were used as a basis for comparison. In the second stage, by overlapping the obtained map and the topographic map of the region, which was collected from the information of the Geological Organization of Turkey, we found in the GIS software that, on average, the highest amount of changes is related to the high areas of this province. The topography of ancient areas and the slope of the areas where ancient cities or valuable monuments are located will have a direct effect on the displacement and subsidence of these areas. And in the third stage, by examining the results and comparing the map obtained from the displacement with the fault map of the studied area, it can be concluded that after the earthquake in this area, the greatest amount of destruction of historical cities is related to the areas that are close to the sea and lakes. have in the end, the investigations showed that the humidity and the distance of the areas from the sea had a direct effect on the amount of destruction and damage caused to this province. 1- Data and research method 1-1-Study area The study area in this project is Gazi Ayantep province of Türkiye. Gaziantep province is located in the southeast of Turkey at the geographical position of 37 degrees and 4 minutes north and 37 degrees and 23 minutes east and 250 kilometers from the Anatolian fault. On February 6, 2023 (Bahman 17, 1401), a powerful earthquake measuring 7.8 on the Richter scale shook central and southern Turkey and northern and western Syria for 75 seconds. This earthquake occurred 30 km away from Ghazi Ayantep city and at a depth of 17.9 km and left irreparable damages. Also, 9 hours later, another earthquake with a magnitude of 7.5 on the Richter scale occurred 105 km from the epicenter of the first earthquake and 10 km deep, which was the largest earthquake in the Anatolian region in the last 2000 years. 1-2-Research method In order to receiving data, 4 images were collected at a time interval of 8 days from each other. The first image was taken on February 4, 2023, two days before the first earthquake, the second image was taken on February 12, the third image was on February 20, and the final image was taken on February 28, 2023. The information obtained from the Geological Organization of Turkey and the images obtained from the map of the affected areas in this province provided by the United Nations Satellite Center were used as a basis for comparison. It should be noted that the purpose of this research is to investigate the changes and destruction of the affected areas. It is historical as well as the prediction of high-risk points in valuable ancient areas and places, so there is no need for very accurate figures of land subsidence in these areas to match the obtained map with land use maps and other related information maps. However, due to the elimination of many errors and accurate processing of images, as well as the basis for comparing the results, the obtained numbers can be cited in most cases. The interferogram is the result of displaying the phase difference caused by the change of the distance between the ground phenomenon and the sensor in two consecutive passes. This step is simply done to obtain the phase difference between two images in consecutive passes. (Wright & et al, 1999 p. 2) In all radar images, the interference of waves as well as the topographical factor of the earth's surface creates an adverse effect on the images, which is known as speckle noise. The process of reducing image noise causes changes that require a filter to be applied to minimize the degradation of the image, which Goldstein filter is used here. The last step is to convert the obtained phase resulting from the application of filters to the amount of displacement. In other words, it is the quantification of the obtained phases. And after that, it is necessary that the obtained image of the ground be used as a reference and a small and accurate amount of displacement is extracted. In this paper, SRTM digital model is used for ground referencing of images. The Geological Organization of Turkey and the United Nations Satellite Center provided pictures and maps of the most damaged areas in the research conducted after the earthquake in this province. Finally, by examining and comparing the maps and information extracted from these institutions as a basis for comparison, the correctness of the results was determined, and after the observations, the areas were ranked from the most to the least in terms of damage, as well as the areas exposed to earthquakes, respectively. They were classified from the most dangerous to the least dangerous. 2-Discussion and conclusion The most important achievement of this project is to obtain the amount of destruction of ancient cities and to study high-risk areas exposed to earthquakes. By overlapping the topographic map of the region with the obtained displacement, it was found that the highest displacement is related to the western cities of the province, and the closer we get to the eastern cities, the destruction rate decreases. The city of Islahiyeh with an average height of 490 meters and displacement of 0.55 to 0.57 meters witnessed the highest amount of displacement. After that, the city of Noordai with an average height of 516 meters has the highest displacement of about 0.53 to 0.55 meters, and then the cities of Shahin Bey, Shahid Kamal, Yavuzli, Ogozli, Araban, Nizip and Karmamish respectively witness the highest displacement. They were the least amount of displacement. Also, by examining the land use map and examining the texture of the urban area and matching the vegetation map of the province with the extracted displacement map, it was found that the areas with agricultural texture and high humidity as well as the areas close to the rivers and water areas had the highest displacement. According to the fact that the area of Issahiyeh with its agricultural context and agricultural lands and numerous villages had the highest level of destruction compared to the highland cities, it was found that the humidity of the study area and its distance from the sea and water areas have a direct effect on the amount of displacement and subsidence of the land. and then the height of the studied area will be the next influencing factor directly. Investigations showed that as we move from Issahiye agricultural area to Nordai area, the height of the area will increase, and after this area, the height of the areas will decrease as we continue towards the eastern areas of the province. Interferometry using radar data is an efficient method to investigate changes, especially in the study of ancient artifacts, so the use of this method can greatly reduce possible future risks. According to the results and observations obtained from the land use map of this province, in order to prevent severe damage to ancient monuments and loss of life, it is necessary to take the most precautions in areas with high humidity and areas that have the least distance from seas and rivers and the most Renovation should be done for ancient monuments located in high areas. Considering the amount of changes in Ghazi Ayantep province, the obtained numbers are worth considering and indicate the dangers that still threaten this city. However, if it is possible to detect faults and dangerous areas in the coming years using this method and make the necessary preparations according to the mentioned recommendations, many lives can be saved when such natural disasters occur and many losses can be avoided. Sang, which threatens the ancient monuments, was prevented. Also, by increasing the accuracy of these radar images and having more advanced equipment, the details of the destruction of historical buildings can be obtained uniquely and with more accuracy and detail, which will greatly help the restoration and restoration of these buildings in the future. Extended Abstract Introduction Ancient cities and cultural heritage are the lasting works of past generations that make us familiar with our identity, so our duty in the present era is to preserve these precious treasures and take care of them. Buildings undergo frequent changes and damages over time. Therefore, in this article, we decided to monitor the changes and destruction of one of the important ancient provinces of Turkey, named Ghazi Ayantep. The method that was used in this research is the radar interferometric method which was obtained by using the radar data of Sentinel 1 satellite and processing them in Snap software. In the first stage, four images were collected in a period of 24 days before and after the earthquake and about 9 aftershocks at very close distances from the Sentinel 1 satellite. Points to Anatolian faults have subsided more than half a meter. The information obtained from the Geological Organization of Turkey and the images obtained from the map of the affected areas in this province provided by the United Nations Satellite Center were used as a basis for comparison. In the second stage, by overlapping the obtained map and the topographic map of the region, which was collected from the information of the Geological Organization of Turkey, we found in the GIS software that, on average, the highest amount of changes is related to the high areas of this province. The topography of ancient areas and the slope of the areas where ancient cities or valuable monuments are located will have a direct effect on the displacement and subsidence of these areas. And in the third stage, by examining the results and comparing the map obtained from the displacement with the fault map of the studied area, it can be concluded that after the earthquake in this area, the greatest amount of destruction of historical cities is related to the areas that are close to the sea and lakes. have in the end, the investigations showed that the humidity and the distance of the areas from the sea had a direct effect on the amount of destruction and damage caused to this province. 1- Data and research method 1-1-Study area The study area in this project is Gazi Ayantep province of Türkiye. Gaziantep province is located in the southeast of Turkey at the geographical position of 37 degrees and 4 minutes north and 37 degrees and 23 minutes east and 250 kilometers from the Anatolian fault. On February 6, 2023 (Bahman 17, 1401), a powerful earthquake measuring 7.8 on the Richter scale shook central and southern Turkey and northern and western Syria for 75 seconds. This earthquake occurred 30 km away from Ghazi Ayantep city and at a depth of 17.9 km and left irreparable damages. Also, 9 hours later, another earthquake with a magnitude of 7.5 on the Richter scale occurred 105 km from the epicenter of the first earthquake and 10 km deep, which was the largest earthquake in the Anatolian region in the last 2000 years. 1-2-Research method In order to receiving data, 4 images were collected at a time interval of 8 days from each other. The first image was taken on February 4, 2023, two days before the first earthquake, the second image was taken on February 12, the third image was on February 20, and the final image was taken on February 28, 2023. The information obtained from the Geological Organization of Turkey and the images obtained from the map of the affected areas in this province provided by the United Nations Satellite Center were used as a basis for comparison. It should be noted that the purpose of this research is to investigate the changes and destruction of the affected areas. It is historical as well as the prediction of high-risk points in valuable ancient areas and places, so there is no need for very accurate figures of land subsidence in these areas to match the obtained map with land use maps and other related information maps. However, due to the elimination of many errors and accurate processing of images, as well as the basis for comparing the results, the obtained numbers can be cited in most cases. The interferogram is the result of displaying the phase difference caused by the change of the distance between the ground phenomenon and the sensor in two consecutive passes. This step is simply done to obtain the phase difference between two images in consecutive passes. (Wright & et al, 1999 p. 2) In all radar images, the interference of waves as well as the topographical factor of the earth's surface creates an adverse effect on the images, which is known as speckle noise. The process of reducing image noise causes changes that require a filter to be applied to minimize the degradation of the image, which Goldstein filter is used here. The last step is to convert the obtained phase resulting from the application of filters to the amount of displacement. In other words, it is the quantification of the obtained phases. And after that, it is necessary that the obtained image of the ground be used as a reference and a small and accurate amount of displacement is extracted. In this paper, SRTM digital model is used for ground referencing of images. The Geological Organization of Turkey and the United Nations Satellite Center provided pictures and maps of the most damaged areas in the research conducted after the earthquake in this province. Finally, by examining and comparing the maps and information extracted from these institutions as a basis for comparison, the correctness of the results was determined, and after the observations, the areas were ranked from the most to the least in terms of damage, as well as the areas exposed to earthquakes, respectively. They were classified from the most dangerous to the least dangerous. 2-Discussion and conclusion The most important achievement of this project is to obtain the amount of destruction of ancient cities and to study high-risk areas exposed to earthquakes. By overlapping the topographic map of the region with the obtained displacement, it was found that the highest displacement is related to the western cities of the province, and the closer we get to the eastern cities, the destruction rate decreases. The city of Islahiyeh with an average height of 490 meters and displacement of 0.55 to 0.57 meters witnessed the highest amount of displacement. After that, the city of Noordai with an average height of 516 meters has the highest displacement of about 0.53 to 0.55 meters, and then the cities of Shahin Bey, Shahid Kamal, Yavuzli, Ogozli, Araban, Nizip and Karmamish respectively witness the highest displacement. They were the least amount of displacement. Also, by examining the land use map and examining the texture of the urban area and matching the vegetation map of the province with the extracted displacement map, it was found that the areas with agricultural texture and high humidity as well as the areas close to the rivers and water areas had the highest displacement. According to the fact that the area of Issahiyeh with its agricultural context and agricultural lands and numerous villages had the highest level of destruction compared to the highland cities, it was found that the humidity of the study area and its distance from the sea and water areas have a direct effect on the amount of displacement and subsidence of the land. and then the height of the studied area will be the next influencing factor directly. Investigations showed that as we move from Issahiye agricultural area to Nordai area, the height of the area will increase, and after this area, the height of the areas will decrease as we continue towards the eastern areas of the province. Interferometry using radar data is an efficient method to investigate changes, especially in the study of ancient artifacts, so the use of this method can greatly reduce possible future risks. According to the results and observations obtained from the land use map of this province, in order to prevent severe damage to ancient monuments and loss of life, it is necessary to take the most precautions in areas with high humidity and areas that have the least distance from seas and rivers and the most Renovation should be done for ancient monuments located in high areas. Considering the amount of changes in Ghazi Ayantep province, the obtained numbers are worth considering and indicate the dangers that still threaten this city. However, if it is possible to detect faults and dangerous areas in the coming years using this method and make the necessary preparations according to the mentioned recommendations, many lives can be saved when such natural disasters occur and many losses can be avoided. Sang, which threatens the ancient monuments, was prevented. Also, by increasing the accuracy of these radar images and having more advanced equipment, the details of the destruction of historical buildings can be obtained uniquely and with more accuracy and detail, which will greatly help the restoration and restoration of these buildings in the future.

https://www.sepehr.org/article_719776_a1701b6d1d093f8527845d8743131a7a.pdf

National Geographical Organization Scientific- Research Quarterly of Geographical Data (SEPEHR) 2588-3860 33 132 2025 02 19 Spatio-temporal analysis of accidents along Kandovan road using Geostatistical methods Spatio-temporal analysis of accidents along Kandovan road using Geostatistical methods 85 101 711957 10.22131/sepehr.2024.2019597.3050 FA Jalal Samia Assistant professor , Department of geography, Faculty of humanities and social sciences, University of Mazandaran, Babolsar, Iran 0000-0002-3339-6801 Manouchehr Ranjbar Shoobi Red crescent relief and rescue organization of Babolsar 0009-0008-4150-8528 Amer Nikpour Associate professor, Department of geography, Faculty of humanities and social sciences, University of Mazandaran, Babolsar, Iran 0000-0003-2839-4526 Journal Article 2024 01 12 Extended abstract Introduction Visiting Mazandaran province could be a fascinating and memorable trip due to its amazing natural touristic attractions such as Caspian Sea and mount Damavand. The three main roads naming Kandovan, Haraz and Firoozkooh can be used to access Mazandaran province. Among them, passing through Kandovan road is fascinating with its beautiful natural landscapes. At the same time, this road is also known as one of the most dangerous roads of Iran due to its mountainous location and the potential occurrence of different types of climatic and geomorphologic hazards. Apart from these dangers, the occurrence of accidents in Kandovan road is one of the main concerns of tourists visiting west parts of Mazandaran province and also the local governments providing relief and rescue services and facilities to injured people. Therefore, it is crucial to identifying the dangerous sections of this road in order to minimize fatalities and socio-economic losses. The purpose of this research is to investigate the spatio-temporal density pattern of road accidents and also to identify accidents clusters along Kandovan road. Material and methods To this end, we used road accidents information along Kandovan road, collected by the relief and rescue bases of Red Crescent organization of Mazandaran province in the period of 2016 to 2022. Information like location, date, and the number of death and injuries in the road accidents along this road were used in this research. First, we used GIS, spatial and statistical analyses in order to get insight from road accidents distribution and statistics. In the next step, Kernel Density Estimation – a Geostatitical measure – was used to investigate the general spatial density pattern of road accidents in the period of 2016-2022 and also the spatio-temporal density pattern of road accidents in every year from 2016 to 2022. Furthermore, the hot spot analysis was implemented to the distribution of road accidents in this period in order to find out whether accidents are clustered, dispersed or randomly distributed. Both general spatial pattern and annual spatio-temporal patterns of accidents were investigated using hot spot analysis. With this, accidents clusters reflected as hot spots were identified based on the Getis-Ord Gi*index and the associated Z-score, P-value and Gi-bin statistics. In this context, the number of accident clusters, the length of road in the accident clusters and the percentage of observed accidents in the clusters were computed from 2016 to 2022. Results and discussion Results show that 2084 accidents were occurred in the period of 2016-2022 with 9076 injuries and 52 deaths. The most number of accidents was occurred in 2022 following the end of Corona lockdown in 2021. Also, several parts of Kandovan road indicated to contain the highest number of accidents density. Besides, the accident density pattern changes spatially and temporarily with an increasing trend in the number of accidents density from the end year of Corona disease epidemic in 2020. Results from hot spot analysis also identified several accidents clusters along this road in the period of 2016-2022. In this context, road accidents clusters were identified in Zangouleh Bridge, Majlar, Siah bisheh, Knadovan tunnel and Ushen Bridge with average Z-score value of 3.12, average P-value smaller than 0.05 and confidence interval of 90 to 99%. The total length of road in these clusters was more than 14 kilometer which contains around 60 % of the total accidents. The spatio-temporal distribution pattern of accidents clusters and also road lengths in the identified clusters change decreasingly in the period of 2016-2022. The results of this research can be used to investigate the reasons behind the occurrence of road accidents in the high accidents density sections and also in accidents clusters identified along the road. Taking proper preparation and mitigation strategies can be beneficial in proper crisis management of road accidents in order to avoid human causalities and socio-economic losses. Conclusion We conclude that kernel density estimation and hot spot analysis are effective geostatistical approaches to investigate the density pattern of road accidents and also to identify accidents clusters. In order to increase the safety of Kandovan road, the factors contributing to accidents occurrence in highly dense accidents sections of road and also in accidents clusters need to be identified, and with implementing proper measures, their effects can be minimized. Extended abstract Introduction Visiting Mazandaran province could be a fascinating and memorable trip due to its amazing natural touristic attractions such as Caspian Sea and mount Damavand. The three main roads naming Kandovan, Haraz and Firoozkooh can be used to access Mazandaran province. Among them, passing through Kandovan road is fascinating with its beautiful natural landscapes. At the same time, this road is also known as one of the most dangerous roads of Iran due to its mountainous location and the potential occurrence of different types of climatic and geomorphologic hazards. Apart from these dangers, the occurrence of accidents in Kandovan road is one of the main concerns of tourists visiting west parts of Mazandaran province and also the local governments providing relief and rescue services and facilities to injured people. Therefore, it is crucial to identifying the dangerous sections of this road in order to minimize fatalities and socio-economic losses. The purpose of this research is to investigate the spatio-temporal density pattern of road accidents and also to identify accidents clusters along Kandovan road. Material and methods To this end, we used road accidents information along Kandovan road, collected by the relief and rescue bases of Red Crescent organization of Mazandaran province in the period of 2016 to 2022. Information like location, date, and the number of death and injuries in the road accidents along this road were used in this research. First, we used GIS, spatial and statistical analyses in order to get insight from road accidents distribution and statistics. In the next step, Kernel Density Estimation – a Geostatitical measure – was used to investigate the general spatial density pattern of road accidents in the period of 2016-2022 and also the spatio-temporal density pattern of road accidents in every year from 2016 to 2022. Furthermore, the hot spot analysis was implemented to the distribution of road accidents in this period in order to find out whether accidents are clustered, dispersed or randomly distributed. Both general spatial pattern and annual spatio-temporal patterns of accidents were investigated using hot spot analysis. With this, accidents clusters reflected as hot spots were identified based on the Getis-Ord Gi*index and the associated Z-score, P-value and Gi-bin statistics. In this context, the number of accident clusters, the length of road in the accident clusters and the percentage of observed accidents in the clusters were computed from 2016 to 2022. Results and discussion Results show that 2084 accidents were occurred in the period of 2016-2022 with 9076 injuries and 52 deaths. The most number of accidents was occurred in 2022 following the end of Corona lockdown in 2021. Also, several parts of Kandovan road indicated to contain the highest number of accidents density. Besides, the accident density pattern changes spatially and temporarily with an increasing trend in the number of accidents density from the end year of Corona disease epidemic in 2020. Results from hot spot analysis also identified several accidents clusters along this road in the period of 2016-2022. In this context, road accidents clusters were identified in Zangouleh Bridge, Majlar, Siah bisheh, Knadovan tunnel and Ushen Bridge with average Z-score value of 3.12, average P-value smaller than 0.05 and confidence interval of 90 to 99%. The total length of road in these clusters was more than 14 kilometer which contains around 60 % of the total accidents. The spatio-temporal distribution pattern of accidents clusters and also road lengths in the identified clusters change decreasingly in the period of 2016-2022. The results of this research can be used to investigate the reasons behind the occurrence of road accidents in the high accidents density sections and also in accidents clusters identified along the road. Taking proper preparation and mitigation strategies can be beneficial in proper crisis management of road accidents in order to avoid human causalities and socio-economic losses. Conclusion We conclude that kernel density estimation and hot spot analysis are effective geostatistical approaches to investigate the density pattern of road accidents and also to identify accidents clusters. In order to increase the safety of Kandovan road, the factors contributing to accidents occurrence in highly dense accidents sections of road and also in accidents clusters need to be identified, and with implementing proper measures, their effects can be minimized.

https://www.sepehr.org/article_711957_7aa600ae1548889364fc61288d728138.pdf

National Geographical Organization Scientific- Research Quarterly of Geographical Data (SEPEHR) 2588-3860 33 132 2025 02 19 Determining the suitable area for the development of defense heritage tourism in Galugah city, Mazandaran Province, Iran Determining the suitable area for the development of defense heritage tourism in Galugah city, Mazandaran Province, Iran 103 125 719710 10.22131/sepehr.2025.2011700.3019 FA Bahram Nekouie Sadry PhD; An adjunct senior lecturer at the faculty of tourism sciences, University of Science and Culture, Tehran, Iran 0000-0003-1476-0898 Zahra Tavazo Ph.D candidate,, Dep. of geology at the faculty of science, University of Birjand, Birjand, Southern Khorasan Province, Iran 0009-0008-8727-6291 Parisa Safarbeyranvand Master's degree in GIS, Expert in Iranian mining engineering organization 0000-0002-7860-2621 Hosein Nemati Lojandi Master's degree, Expert in tourism and handicrafts office, Mazandaran cultural heritage, Iran 0009-0007-4735-4948 Journal Article 2023 09 16 Extended Abstract Introduction In the last ten years in the world, the phrase "defense heritage tourism" instead of "War tourism" has attracted again the attention of scientific circles. The development of defense heritage tourism in Iran, which is several thousand years old, has not been paid attention to till now. This new approach among researchers, considering the existence of many historical castles, forts and battlefields in Iran, can help to identify and introduce many neglected points and areas of our country, and make them protected and exploited through the development of sustainable tourism in Iran. Meanwhile, Golugah city is a place where the fate of two historical dynasties was determined, but such historical heritage has not been considered for tourism development. Methods and Materials The main purpose of this research is to investigate the potential of defense heritage tourism development in Galugah region located in the east of Mazandaran province by using descriptive-analytical research method. To carry out this research, numerous data were used, including archaeological, demographic, economic, social, urban infrastructure, location of villages, and distribution of historical military points. The main method of the research was based on documentary studies, field observations, interviews with experts, and using spatial data analysis in Arc GIS system, and it was carried out to provide a zoning map for the development of defense heritage tourism sites in Galugah city. Also, with the aforementioned data and the use of some secondary data, it was decided to determine the evaluation criteria of the defense heritage sites in the study area and priority of the determined sites in the area were valued, and shown on the map based on predetermined criteria. Discussion and Findings In Golugah city, a general area with six main sites such as Jarkalbad defense wall (trench), Gravdin Tepe, GalePayan, and Lemarask and Nameneh barracks and the main historical battlefield zone were identified. Finally, according to the determined evaluation criteria and detailed field observations, the Kolbad defensive wall is the first priority, Golugah main historical battlefield in the second priority, the ancient castle of GalePayan in the third priority of investment for physical reconstruction and development of tourism infrastructure were recognized. The interpretation center was also placed next to the battlefield so that, in addition to this battlefield, it can also provide interpretation services to the other three suitable and very suitable sites in the study area. Conclusion Golugah region is very important for the development of defense heritage tourism due to the occurrence of many wars. The existence of this defense heritage along with the recreation and the use of methods of bringing the past alive in the main historical battlefield - if the infrastructure is created - will be among the attractions of Golugah city for defense heritage tourists. Three defense heritage sites: Kolbad defensive wall, Gravdin Tepe Castle and the main historical battlefield needs accurate identification, restoration and re-habilitation in the future, and in case of government investment to build a defense heritage interpretation center next to the interpretation museum and use advanced technological tools and ICT to tell the stories of the battlefields to tourists - according to Beck and Cable's principles, 1998 - can attract tourists and generate employment in the region. The rest of identified defense heritage sites, before any development measures, need archaeological excavations by experts, and after completing these measures, they can be used and invested for other aforementioned uses. Extended Abstract Introduction In the last ten years in the world, the phrase "defense heritage tourism" instead of "War tourism" has attracted again the attention of scientific circles. The development of defense heritage tourism in Iran, which is several thousand years old, has not been paid attention to till now. This new approach among researchers, considering the existence of many historical castles, forts and battlefields in Iran, can help to identify and introduce many neglected points and areas of our country, and make them protected and exploited through the development of sustainable tourism in Iran. Meanwhile, Golugah city is a place where the fate of two historical dynasties was determined, but such historical heritage has not been considered for tourism development. Methods and Materials The main purpose of this research is to investigate the potential of defense heritage tourism development in Galugah region located in the east of Mazandaran province by using descriptive-analytical research method. To carry out this research, numerous data were used, including archaeological, demographic, economic, social, urban infrastructure, location of villages, and distribution of historical military points. The main method of the research was based on documentary studies, field observations, interviews with experts, and using spatial data analysis in Arc GIS system, and it was carried out to provide a zoning map for the development of defense heritage tourism sites in Galugah city. Also, with the aforementioned data and the use of some secondary data, it was decided to determine the evaluation criteria of the defense heritage sites in the study area and priority of the determined sites in the area were valued, and shown on the map based on predetermined criteria. Discussion and Findings In Golugah city, a general area with six main sites such as Jarkalbad defense wall (trench), Gravdin Tepe, GalePayan, and Lemarask and Nameneh barracks and the main historical battlefield zone were identified. Finally, according to the determined evaluation criteria and detailed field observations, the Kolbad defensive wall is the first priority, Golugah main historical battlefield in the second priority, the ancient castle of GalePayan in the third priority of investment for physical reconstruction and development of tourism infrastructure were recognized. The interpretation center was also placed next to the battlefield so that, in addition to this battlefield, it can also provide interpretation services to the other three suitable and very suitable sites in the study area. Conclusion Golugah region is very important for the development of defense heritage tourism due to the occurrence of many wars. The existence of this defense heritage along with the recreation and the use of methods of bringing the past alive in the main historical battlefield - if the infrastructure is created - will be among the attractions of Golugah city for defense heritage tourists. Three defense heritage sites: Kolbad defensive wall, Gravdin Tepe Castle and the main historical battlefield needs accurate identification, restoration and re-habilitation in the future, and in case of government investment to build a defense heritage interpretation center next to the interpretation museum and use advanced technological tools and ICT to tell the stories of the battlefields to tourists - according to Beck and Cable's principles, 1998 - can attract tourists and generate employment in the region. The rest of identified defense heritage sites, before any development measures, need archaeological excavations by experts, and after completing these measures, they can be used and invested for other aforementioned uses.

https://www.sepehr.org/article_719710_b2e1afa0f421cdbfbdab48380b70c6bb.pdf

National Geographical Organization Scientific- Research Quarterly of Geographical Data (SEPEHR) 2588-3860 33 132 2025 02 19 Analysis of earth surface temperature changes with MODIS satellite images and its relationship with climatic factors - Case study: Kerman Province Analysis of earth surface temperature changes with MODIS satellite images and its relationship with climatic factors - Case study: Kerman Province 127 142 712988 10.22131/sepehr.2024.2022761.3060 FA Ahmad Mazidi Associate professor in Climatalogy , Department of Geography, Yazd University 0000-0003-4558-9907 Foroogh Mohammadi Ravari PhD student of Climatology, Yazd University, Yazd, Iran 0000-0001-9989-4910 Journal Article 2024 02 20 Extended Abstract Introduction: Time series analysis is a suitable tool that is used in mathematical modeling, predicting future events, revealing trends, investigating diffraction in climate data, as well as reconstructing incomplete data, and expanding information. Climatic changes are mainly caused by fluctuations, fluctuations, or changes in climatic elements, especially temperature and precipitation. These developments leave undeniable effects on local phenomena, hence the evidence of the past climate can be traced in all wet and dry, hot and cold environments, and biological areas (Ghayour, 2006:85). The temperature of the earth's surface is an important parameter for evaluating the energy budget of the earth's surface (Trigo et al, 2008:1). With the change in climate (temperature and rainfall), many changes are made on the surface of the earth, including vegetation. In fact, with the increase in temperature and decrease in rainfall, vegetation in the region decreases. Considering the importance of the issue and the relationship between climatic indicators and vegetation, by determining the relationship between them, one can predict the changes based on the other, which leads to an increase in the speed and accuracy of the work. Therefore, it seems important to use satellite images and extract and investigate the relationship between temperature and rainfall factors as well as vegetation in different areas, especially watersheds (Zhu et al, 2016:792). With the expansion of satellite technology, satellite images have widely provided access to information on land resources, and remote sensing tools have taken an important role in obtaining information about climate phenomena, because multi-spectral satellite images have important advantages, including They have the availability and ability of digital interpretation (Lillesand and Kiefer, 1994:750). Materials & Methods: In this research, using monthly rainfall data from a CHIRPS sensor with a spatial resolution of five kilometers, NDVI vegetation index from a MODIS sensor for 16 days, with a resolution of 250 meters, and day and night surface temperature of 8 days from a MODIS sensor with a resolution of one kilometer, to analyze the changes in surface temperature and its relationship with climatic factors in Kerman province during a statistical period of 22 years (2001-2022) were studied. In the investigation of the annual precipitation fluctuations of Kerman province, standardized values of Z have been used, and these values have varied between -1.5 and +1.5. After receiving the data, first the CHIRPS images, then the NDVI and LST images were processed in the ArcGIS software environment and the values were extracted for Kerman province and then analyzed in the Excel software environment. Results & Discussion: According to SPI results, drought is observed in 2010, 2016, 2018, and 2021, and drought in 2004, 2009, 2017, 2019 and 2020. In the rest of the years, the SPI index has been normal. Also, the seasonal rainfall showed that the highest rainfall was in the winters of 2005, 2017, and 2019 with an amount of 90 mm and more and the lowest rainfall was in the summer of 2019 with an amount of less than 1.04 mm. The value of the vegetation cover index (NDVI) is also in the spring season with a value of 1.05, which has an increasing trend, and the lowest value of the vegetation cover index (NDVI) in the autumn and winter seasons, whose lowest value is 0.35 and 0.42 on December 19 and November 17 with a trend A decrease is shown. The seasonal vegetation also shows that as we move from the west of the region to the east, the amount of vegetation decreases. The seasonal changes in the temperature of the surface of the earth during the day in Kerman province show that the hottest seasons are summer and spring and the coldest season is winter. The seasonal changes in the earth's surface temperature at night also show that the highest surface temperature is related to summer and spring, and the lowest is in autumn and winter. Conclusion: In general, the results show that according to temperature fluctuations, there is a positive and significant relationship between the temperature of the earth's surface and vegetation (P-value at the 0.01 level). And there is a negative and significant relationship between the temperature of the earth's surface and precipitation. So precipitation has the greatest effect on the variability of the earth's surface temperature and vegetation has the least effect on the surface temperature changes. The increase in day and night temperatures in the spring and summer seasons causes an increase in evaporation and a subsequent decrease in water resources throughout the province and pressure on underground water. On the other hand, with the increase in temperature, the amount of evaporation and transpiration (plants' water needs) will also increase and will lead to a potential decrease in water resources, especially in the eastern regions of the province, but the presence of vegetation can almost reduce the temperature of the earth's surface. In the autumn and winter seasons, during the last decades, with the increase in temperature, the amount of precipitation and vegetation has decreased. Also, an increase in temperature can increase the water demand, which in turn leads to more extraction of surface and underground water resources. This means that the surface temperature has increased significantly in the mentioned statistical period. Also, the different conditions of each region are important factors in determining the type of relationship between temperature, vegetation, and precipitation. The results of this research on the relationship between the earth's surface temperature and climatic factors with the research of Mianabadi et al (2023), and Mazidi et al (2023) based on the method of the experimental relationship between surface temperature and other factors are consistent. According to the findings, the temperature trend in Kerman province is significant and the possibility of heat stress will increase in the future. Extended Abstract Introduction: Time series analysis is a suitable tool that is used in mathematical modeling, predicting future events, revealing trends, investigating diffraction in climate data, as well as reconstructing incomplete data, and expanding information. Climatic changes are mainly caused by fluctuations, fluctuations, or changes in climatic elements, especially temperature and precipitation. These developments leave undeniable effects on local phenomena, hence the evidence of the past climate can be traced in all wet and dry, hot and cold environments, and biological areas (Ghayour, 2006:85). The temperature of the earth's surface is an important parameter for evaluating the energy budget of the earth's surface (Trigo et al, 2008:1). With the change in climate (temperature and rainfall), many changes are made on the surface of the earth, including vegetation. In fact, with the increase in temperature and decrease in rainfall, vegetation in the region decreases. Considering the importance of the issue and the relationship between climatic indicators and vegetation, by determining the relationship between them, one can predict the changes based on the other, which leads to an increase in the speed and accuracy of the work. Therefore, it seems important to use satellite images and extract and investigate the relationship between temperature and rainfall factors as well as vegetation in different areas, especially watersheds (Zhu et al, 2016:792). With the expansion of satellite technology, satellite images have widely provided access to information on land resources, and remote sensing tools have taken an important role in obtaining information about climate phenomena, because multi-spectral satellite images have important advantages, including They have the availability and ability of digital interpretation (Lillesand and Kiefer, 1994:750). Materials & Methods: In this research, using monthly rainfall data from a CHIRPS sensor with a spatial resolution of five kilometers, NDVI vegetation index from a MODIS sensor for 16 days, with a resolution of 250 meters, and day and night surface temperature of 8 days from a MODIS sensor with a resolution of one kilometer, to analyze the changes in surface temperature and its relationship with climatic factors in Kerman province during a statistical period of 22 years (2001-2022) were studied. In the investigation of the annual precipitation fluctuations of Kerman province, standardized values of Z have been used, and these values have varied between -1.5 and +1.5. After receiving the data, first the CHIRPS images, then the NDVI and LST images were processed in the ArcGIS software environment and the values were extracted for Kerman province and then analyzed in the Excel software environment. Results & Discussion: According to SPI results, drought is observed in 2010, 2016, 2018, and 2021, and drought in 2004, 2009, 2017, 2019 and 2020. In the rest of the years, the SPI index has been normal. Also, the seasonal rainfall showed that the highest rainfall was in the winters of 2005, 2017, and 2019 with an amount of 90 mm and more and the lowest rainfall was in the summer of 2019 with an amount of less than 1.04 mm. The value of the vegetation cover index (NDVI) is also in the spring season with a value of 1.05, which has an increasing trend, and the lowest value of the vegetation cover index (NDVI) in the autumn and winter seasons, whose lowest value is 0.35 and 0.42 on December 19 and November 17 with a trend A decrease is shown. The seasonal vegetation also shows that as we move from the west of the region to the east, the amount of vegetation decreases. The seasonal changes in the temperature of the surface of the earth during the day in Kerman province show that the hottest seasons are summer and spring and the coldest season is winter. The seasonal changes in the earth's surface temperature at night also show that the highest surface temperature is related to summer and spring, and the lowest is in autumn and winter. Conclusion: In general, the results show that according to temperature fluctuations, there is a positive and significant relationship between the temperature of the earth's surface and vegetation (P-value at the 0.01 level). And there is a negative and significant relationship between the temperature of the earth's surface and precipitation. So precipitation has the greatest effect on the variability of the earth's surface temperature and vegetation has the least effect on the surface temperature changes. The increase in day and night temperatures in the spring and summer seasons causes an increase in evaporation and a subsequent decrease in water resources throughout the province and pressure on underground water. On the other hand, with the increase in temperature, the amount of evaporation and transpiration (plants' water needs) will also increase and will lead to a potential decrease in water resources, especially in the eastern regions of the province, but the presence of vegetation can almost reduce the temperature of the earth's surface. In the autumn and winter seasons, during the last decades, with the increase in temperature, the amount of precipitation and vegetation has decreased. Also, an increase in temperature can increase the water demand, which in turn leads to more extraction of surface and underground water resources. This means that the surface temperature has increased significantly in the mentioned statistical period. Also, the different conditions of each region are important factors in determining the type of relationship between temperature, vegetation, and precipitation. The results of this research on the relationship between the earth's surface temperature and climatic factors with the research of Mianabadi et al (2023), and Mazidi et al (2023) based on the method of the experimental relationship between surface temperature and other factors are consistent. According to the findings, the temperature trend in Kerman province is significant and the possibility of heat stress will increase in the future.

https://www.sepehr.org/article_712988_2241350b27fa8caab6ac3fac977042bd.pdf

National Geographical Organization Scientific- Research Quarterly of Geographical Data (SEPEHR) 2588-3860 33 132 2025 02 19 An innovative algorithm for detecting buildings in forest areas using Lidar point cloud An innovative algorithm for detecting buildings in forest areas using Lidar point cloud 143 156 719759 10.22131/sepehr.2025.2013720.3030 FA Safa Khazaei Associate professor, Research center of signature, Imam Hussein University, Tehran, Iran 0000-0003-2982-2078 Mohammad Reza Seif Assistance professor, Department of surveying engineering, Faculty of Civil Engineering, Imam Hussein University, Tehran, Iran 0000-0001-6032-6377 Behnam Asghari Beirami Researcher, Department of surveying engineering, Faculty of Civil engineering, Imam Hussein University, Tehran, Iran 0000-0002-0314-1912 Journal Article 2023 10 17 Extended Abtract Introduction lidar data are raw point clouds that include three-dimensional coordinates and are taken by laser. These three-dimensional data can automatically produce the digital surface model (DSM), which plays an important role in earth-related applications. In practice, the processing of huge point clouds with the aim of modeling systematic errors, filtering, extracting complications, etc., requires a large amount of human interaction. In recent years, the use of this technology has made significant progress in revealing targets. The ability of the laser pulse to penetrate through the leaves of the trees makes it possible to detect the targets located under the cover of the trees by LIDAR. Chang et al. (2010) for the first time presented a method for detecting objects located under trees. In this method, which operates based on the feature of multi-pulse LIDAR, statistical methods are used to reveal and extract the target points located under the trees. In the algorithm, the removal of the forest cover is done based on the morphological filter. The results of this algorithm show that the filtering process in this way has worked well in removing the tree cover and revealing the targets under the tree cover. The American Defense Advanced Study Agency (DARPA) in a project, called JIGSAW, has demonstrated the ability of lidar to identify targets located under trees. Methodology In this study, a new method called band filtering algorithm is presented to use LIDAR point cloud data to detect buildings located under the cover of trees. This method includes two general steps; segmentation and disclosure of the targets. In the segmentation stage, first the cloud points are segmented into different segments based on height and distance parameters in windows with specific dimensions. Division is done in two directions with angles of zero and thirty degrees and is evaluated as an intermediate goal. Then, the ground and plant candidate points are separated from the building points, and in the next step, by comparing the height of the ground under the tree cover and its surroundings, the non-ground effects located under the tree cover are identified. Finally, using an innovative algorithm, edges are detected. Experimental results In this study, the effectiveness of the proposed method was evaluated on lidar data related to an area of Santa Catarina state in Brazil. Due to the characteristic of receiving more than one pulse by the lidar sensor, the lidar pulses have the ability to penetrate under dense tree. This capability allows the sensor to detect targets located under tree. Considering the very high height accuracy of lidar data, it is possible to detect the targets located under the trees by comparing the height of the points under the tree cover and the points around the tree cover. In the proposed method in this article, first, the cloud points are segmented in different directions and appropriate labels are assigned to the segments. Then, by stacking the sections, the number of sections is optimized. Then it enters the edge detection stage in order to extract the targets located under the tree and if there is a target under the tree, by detecting the edges of the target, the desired target is extracted with the desired accuracy. to be Based on the experimental results of this study, the level under the receiver operating characteristic curve (ROC) of the proposed method is equal to 91%, which is 4% higher than the morphological filtering method. This evaluation shows the better performance of this method compared to the morphology filtering method. In this study, in the available data, only buildings could be investigated as targets located under trees, and therefore, the threshold used in the proposed method is considered to be 2.7 to 3 meters, which the values are usually the height of the shortest buildings. By changing these threshold limits, it is possible to reveal other targets with different sizes. Therefore, as a suggestion, it is recommended to investigate and evaluate the proposed method for other possible purposes such as cars in other studies. It is also suggested to investigate and evaluate the detection of targets located under trees in sloping forest areas. Extended Abtract Introduction lidar data are raw point clouds that include three-dimensional coordinates and are taken by laser. These three-dimensional data can automatically produce the digital surface model (DSM), which plays an important role in earth-related applications. In practice, the processing of huge point clouds with the aim of modeling systematic errors, filtering, extracting complications, etc., requires a large amount of human interaction. In recent years, the use of this technology has made significant progress in revealing targets. The ability of the laser pulse to penetrate through the leaves of the trees makes it possible to detect the targets located under the cover of the trees by LIDAR. Chang et al. (2010) for the first time presented a method for detecting objects located under trees. In this method, which operates based on the feature of multi-pulse LIDAR, statistical methods are used to reveal and extract the target points located under the trees. In the algorithm, the removal of the forest cover is done based on the morphological filter. The results of this algorithm show that the filtering process in this way has worked well in removing the tree cover and revealing the targets under the tree cover. The American Defense Advanced Study Agency (DARPA) in a project, called JIGSAW, has demonstrated the ability of lidar to identify targets located under trees. Methodology In this study, a new method called band filtering algorithm is presented to use LIDAR point cloud data to detect buildings located under the cover of trees. This method includes two general steps; segmentation and disclosure of the targets. In the segmentation stage, first the cloud points are segmented into different segments based on height and distance parameters in windows with specific dimensions. Division is done in two directions with angles of zero and thirty degrees and is evaluated as an intermediate goal. Then, the ground and plant candidate points are separated from the building points, and in the next step, by comparing the height of the ground under the tree cover and its surroundings, the non-ground effects located under the tree cover are identified. Finally, using an innovative algorithm, edges are detected. Experimental results In this study, the effectiveness of the proposed method was evaluated on lidar data related to an area of Santa Catarina state in Brazil. Due to the characteristic of receiving more than one pulse by the lidar sensor, the lidar pulses have the ability to penetrate under dense tree. This capability allows the sensor to detect targets located under tree. Considering the very high height accuracy of lidar data, it is possible to detect the targets located under the trees by comparing the height of the points under the tree cover and the points around the tree cover. In the proposed method in this article, first, the cloud points are segmented in different directions and appropriate labels are assigned to the segments. Then, by stacking the sections, the number of sections is optimized. Then it enters the edge detection stage in order to extract the targets located under the tree and if there is a target under the tree, by detecting the edges of the target, the desired target is extracted with the desired accuracy. to be Based on the experimental results of this study, the level under the receiver operating characteristic curve (ROC) of the proposed method is equal to 91%, which is 4% higher than the morphological filtering method. This evaluation shows the better performance of this method compared to the morphology filtering method. In this study, in the available data, only buildings could be investigated as targets located under trees, and therefore, the threshold used in the proposed method is considered to be 2.7 to 3 meters, which the values are usually the height of the shortest buildings. By changing these threshold limits, it is possible to reveal other targets with different sizes. Therefore, as a suggestion, it is recommended to investigate and evaluate the proposed method for other possible purposes such as cars in other studies. It is also suggested to investigate and evaluate the detection of targets located under trees in sloping forest areas.

https://www.sepehr.org/article_719759_e74618b1ce5643f4a4a55d8b61af2553.pdf

National Geographical Organization Scientific- Research Quarterly of Geographical Data (SEPEHR) 2588-3860 33 132 2025 02 19 The monitoring of physical development of the city of Kerman and the consequences of urban sprawl using satellite data The monitoring of physical development of the city of Kerman and the consequences of urban sprawl using satellite data 157 172 719317 10.22131/sepehr.2024.2009422.3012 FA Behnaz Sheykh Shariati Kermani Ph.D student, Geography and urban planning, Yazd University, Yazd, Iran 0000-0001-7074-5428 Mohammad Hossein Saraei Professor, Department of geography and urban planning, Yazd University, Yazd, Iran 0000-0003-3449-3969 Journal Article 2023 11 30 Extended Abstract Introduction: With the rapid increase of the urban population, the changes related to the body and urban spaces are accelerating; These developments lead to the emergence of horizontal growth, change of use, destruction and destruction of green spaces, gardens and agricultural lands around the city, and the phenomenon of urban creep and ultimately urban growth. Materials and methods: In the current research, which is practical in terms of its purpose and descriptive-analytical in terms of its method; In order to calculate the rapid growth of Kerman city, Landsat 7 and 8 satellite images during the periods of 2000, 2013 and 2023 and their analysis in ENVI software were used. Results and Discussion: The first period (year 2000): The results of the surveys showed that Kerman city had 5319 hectares of physical urban growth in 2000, but this physical growth shows the direction of the urban growth pattern towards the east and parts of it. It is from the southeast. The second period (year 2013): The results of the surveys showed that after 13 years, the city of Kerman has increased by 2508 hectares to the amount of 7827 hectares. The third period (year 2023): The results of the surveys showed that after 10 years, the city of Kerman has increased by 3464 hectares to the amount of 11291 hectares. Conclusion: The results showed that the city of Kerman has grown sporadically in all directions. But most of this growth has taken place towards the east and south of Kerman along the main entrance and exit routes of the city. Also, the growth of urban development has increased during the study periods and the study period of 2023 has shown more urban growth compared to 2013. Extended Abstract Introduction: With the rapid increase of the urban population, the changes related to the body and urban spaces are accelerating; These developments lead to the emergence of horizontal growth, change of use, destruction and destruction of green spaces, gardens and agricultural lands around the city, and the phenomenon of urban creep and ultimately urban growth. Materials and methods: In the current research, which is practical in terms of its purpose and descriptive-analytical in terms of its method; In order to calculate the rapid growth of Kerman city, Landsat 7 and 8 satellite images during the periods of 2000, 2013 and 2023 and their analysis in ENVI software were used. Results and Discussion: The first period (year 2000): The results of the surveys showed that Kerman city had 5319 hectares of physical urban growth in 2000, but this physical growth shows the direction of the urban growth pattern towards the east and parts of it. It is from the southeast. The second period (year 2013): The results of the surveys showed that after 13 years, the city of Kerman has increased by 2508 hectares to the amount of 7827 hectares. The third period (year 2023): The results of the surveys showed that after 10 years, the city of Kerman has increased by 3464 hectares to the amount of 11291 hectares. Conclusion: The results showed that the city of Kerman has grown sporadically in all directions. But most of this growth has taken place towards the east and south of Kerman along the main entrance and exit routes of the city. Also, the growth of urban development has increased during the study periods and the study period of 2023 has shown more urban growth compared to 2013.

https://www.sepehr.org/article_719317_8a916ce9aeec956af918254c4b47dbef.pdf

National Geographical Organization Scientific- Research Quarterly of Geographical Data (SEPEHR) 2588-3860 33 132 2025 02 19 Evaluating the seismic potential of megacities in Iran Evaluating the seismic potential of megacities in Iran 173 188 715929 10.22131/sepehr.2024.2019284.3047 FA Hamid Ganjaeian Ph.D. of Geomorphology, Tehran University, Tehran, Iran 0000-0001-5611-4160 Journal Article 2024 01 01 Extended Abstract 1-Introduction Iran is one of the countries that is prone to natural hazards due to its geographical situation. One of the risks that has always threatened Iran is the risk of earthquakes. The land of Iran, as a part of the active tectonic zone of the Alps-Himalayas, has been affected by many tectonic activities over time, such as the appearance of the Zagros-Makran and Alborz-Kope Dagh mountain ranges in the Iranian plateau as a result of subduction of the Arabian plates. The Indian Ocean is one of the landforms resulting from this convergence. According to the geological situation of the Iranian plateau, this plateau is facing many disturbances and this problem has caused Iran to be one of the earthquake-prone countries in the world. Earthquake is the most important natural hazard that is always associated with a lot of human and financial losses. Due to its unpredictability and its power, this hazard has faced serious challenges in the seismic regions of the world. In fact, large earthquakes are one of the most destructive natural disasters, which often lead to widespread casualties and many deaths, and many cities are vulnerable to large earthquakes. Among the areas that are vulnerable to the risk of earthquakes are the metropolises because they house a large part of the country's population. According to the statistics of 2015, the metropolitan cities of Tehran, Mashhad, Isfahan, Karaj, Shiraz, Tabriz, Qom, Ahvaz and Kermanshah include about 27% of the country's population. Due to the importance of the subject, in this research, the seismic status of Iran's metropolises has been evaluated. 2-Materials and methods In this research, information related to the epicenter of earthquakes recorded in Iran during the years 1286 to 1402 (1907 to 2023), demographic information of Iranian metropolises, statistical information related to the state of constructions of metropolises, and also The information obtained from satellite images has been used as the most important research data. The most important research tools are ArcGIS (to prepare the required maps) and SPSS (to analyze the data). Also, in this research, the Analytical Hierarchy (AHP) model was used in order to weight the parameters. According to the desired goals, this research has been done in two general stages. In the first stage, a 100 km boundary is defined for each metropolis, and then the earthquakes that occurred in this area are identified. In the following, the earthquakes that occurred in metropolitan areas have been analyzed in terms of number and size. In the second stage, based on 6 parameters, the state of vulnerability of metropolises has been evaluated. After evaluating the metropolises in terms of the desired parameters, first the parameters were normalized and then the parameters were weighted using the AHP model. 3-Discussion and results The results of the evaluation of earthquakes that occurred in the outskirts of 100 kilometers of metropolises have shown that the largest number of earthquakes with 390 recorded cases was related to the outskirts of Shiraz metropolis, and Isfahan and Qom metropolises recorded 19 and 20 respectively. Have the least number of earthquakes. Also, the results of the survey of the number of earthquakes with a magnitude greater than 6 on the Richter scale have shown that the outskirts of the metropolises of Shiraz and Kermanshah had the largest number of earthquakes with 4 earthquakes, and the outskirts of the metropolises of Isfahan and Ahvaz There has been no earthquake with a magnitude greater than 6 on the Richter scale. Considering that in addition to earthquakes, other factors are also effective in determining the vulnerability of metropolises against earthquake hazards, in this study, population parameters, population density, percentage of open space and percentage of worn-out fabric are also used. Has been According to the results, the largest population was related to Tehran city. The highest population density was related to the city of Mashhad. The highest percentage of worn out fabric was related to the city of Tehran and the lowest percentage of open space was related to the city of Tehran. 4-Conclusion The results of this research have shown that Iran's metropolises have different seismic potentials due to their geo-structural position, and also, under the influence of various population factors and constructions, different potentials in terms of damage. They are resistant to earthquakes. In this research, in order to investigate the seismic status of metropolises, the earthquakes that occurred within 100 kilometers of them have been analyzed. According to the results, during the years 1286 to 1402, 999 earthquakes with a magnitude of more than 3 on the Richter scale occurred within a radius of 100 km from these metropolises, 15 of which had a magnitude of more than 6 on the Richter scale. Is. The results of the analysis of earthquakes have shown that the largest number of earthquakes occurred in the metropolitan areas of Shiraz, Ahvaz and Kermanshah, so that 390, 186 and 147 earthquakes occurred in these metropolitan areas, respectively. The lowest number of earthquakes with 19 and 20 cases respectively was related to the metropolitan areas of Isfahan and Qom. Also, the largest number of earthquakes with a magnitude greater than 6 on the Richter scale was related to the metropolitan areas of Shiraz and Kermanshah. The results of this section have shown that the seismic status of Iran's metropolises has been very different, and considering that in addition to the number of earthquakes, various human parameters are also effective in the degree of vulnerability to earthquakes, in this research Based on different parameters, the state of vulnerability of metropolises was evaluated. Based on the results, Shiraz metropolis with a total score of 17.68 is considered the most vulnerable metropolis in the country against earthquake risk. After this metropolis, Kermanshah and Tehran metropolises have the highest vulnerability potential with 13.12 and 10.87 points, respectively. Also, Isfahan metropolis with a total of 2.75 points has the lowest vulnerability potential among the metropolises of the country, and after that, Ahvaz and Qom metropolises have the lowest with 5.72 and 6.66 points, respectively. They are potential vulnerabilities. Extended Abstract 1-Introduction Iran is one of the countries that is prone to natural hazards due to its geographical situation. One of the risks that has always threatened Iran is the risk of earthquakes. The land of Iran, as a part of the active tectonic zone of the Alps-Himalayas, has been affected by many tectonic activities over time, such as the appearance of the Zagros-Makran and Alborz-Kope Dagh mountain ranges in the Iranian plateau as a result of subduction of the Arabian plates. The Indian Ocean is one of the landforms resulting from this convergence. According to the geological situation of the Iranian plateau, this plateau is facing many disturbances and this problem has caused Iran to be one of the earthquake-prone countries in the world. Earthquake is the most important natural hazard that is always associated with a lot of human and financial losses. Due to its unpredictability and its power, this hazard has faced serious challenges in the seismic regions of the world. In fact, large earthquakes are one of the most destructive natural disasters, which often lead to widespread casualties and many deaths, and many cities are vulnerable to large earthquakes. Among the areas that are vulnerable to the risk of earthquakes are the metropolises because they house a large part of the country's population. According to the statistics of 2015, the metropolitan cities of Tehran, Mashhad, Isfahan, Karaj, Shiraz, Tabriz, Qom, Ahvaz and Kermanshah include about 27% of the country's population. Due to the importance of the subject, in this research, the seismic status of Iran's metropolises has been evaluated. 2-Materials and methods In this research, information related to the epicenter of earthquakes recorded in Iran during the years 1286 to 1402 (1907 to 2023), demographic information of Iranian metropolises, statistical information related to the state of constructions of metropolises, and also The information obtained from satellite images has been used as the most important research data. The most important research tools are ArcGIS (to prepare the required maps) and SPSS (to analyze the data). Also, in this research, the Analytical Hierarchy (AHP) model was used in order to weight the parameters. According to the desired goals, this research has been done in two general stages. In the first stage, a 100 km boundary is defined for each metropolis, and then the earthquakes that occurred in this area are identified. In the following, the earthquakes that occurred in metropolitan areas have been analyzed in terms of number and size. In the second stage, based on 6 parameters, the state of vulnerability of metropolises has been evaluated. After evaluating the metropolises in terms of the desired parameters, first the parameters were normalized and then the parameters were weighted using the AHP model. 3-Discussion and results The results of the evaluation of earthquakes that occurred in the outskirts of 100 kilometers of metropolises have shown that the largest number of earthquakes with 390 recorded cases was related to the outskirts of Shiraz metropolis, and Isfahan and Qom metropolises recorded 19 and 20 respectively. Have the least number of earthquakes. Also, the results of the survey of the number of earthquakes with a magnitude greater than 6 on the Richter scale have shown that the outskirts of the metropolises of Shiraz and Kermanshah had the largest number of earthquakes with 4 earthquakes, and the outskirts of the metropolises of Isfahan and Ahvaz There has been no earthquake with a magnitude greater than 6 on the Richter scale. Considering that in addition to earthquakes, other factors are also effective in determining the vulnerability of metropolises against earthquake hazards, in this study, population parameters, population density, percentage of open space and percentage of worn-out fabric are also used. Has been According to the results, the largest population was related to Tehran city. The highest population density was related to the city of Mashhad. The highest percentage of worn out fabric was related to the city of Tehran and the lowest percentage of open space was related to the city of Tehran. 4-Conclusion The results of this research have shown that Iran's metropolises have different seismic potentials due to their geo-structural position, and also, under the influence of various population factors and constructions, different potentials in terms of damage. They are resistant to earthquakes. In this research, in order to investigate the seismic status of metropolises, the earthquakes that occurred within 100 kilometers of them have been analyzed. According to the results, during the years 1286 to 1402, 999 earthquakes with a magnitude of more than 3 on the Richter scale occurred within a radius of 100 km from these metropolises, 15 of which had a magnitude of more than 6 on the Richter scale. Is. The results of the analysis of earthquakes have shown that the largest number of earthquakes occurred in the metropolitan areas of Shiraz, Ahvaz and Kermanshah, so that 390, 186 and 147 earthquakes occurred in these metropolitan areas, respectively. The lowest number of earthquakes with 19 and 20 cases respectively was related to the metropolitan areas of Isfahan and Qom. Also, the largest number of earthquakes with a magnitude greater than 6 on the Richter scale was related to the metropolitan areas of Shiraz and Kermanshah. The results of this section have shown that the seismic status of Iran's metropolises has been very different, and considering that in addition to the number of earthquakes, various human parameters are also effective in the degree of vulnerability to earthquakes, in this research Based on different parameters, the state of vulnerability of metropolises was evaluated. Based on the results, Shiraz metropolis with a total score of 17.68 is considered the most vulnerable metropolis in the country against earthquake risk. After this metropolis, Kermanshah and Tehran metropolises have the highest vulnerability potential with 13.12 and 10.87 points, respectively. Also, Isfahan metropolis with a total of 2.75 points has the lowest vulnerability potential among the metropolises of the country, and after that, Ahvaz and Qom metropolises have the lowest with 5.72 and 6.66 points, respectively. They are potential vulnerabilities.

https://www.sepehr.org/article_715929_acd0a7179b8fd5f59f5854c7a778dcc5.pdf