Kazem Borhani; Ashraf Azimzadeh Irany; Amirhosein Elhami
Abstract
Extended Abstract Introduction Emergency shelters built based on multifunctional spaces are one of the main components of crisis management, which is carried out for various purposes by transferring people from hazardous or damaged areas to safe areas. Providing suitable spaces for the accommodation ...
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Extended Abstract Introduction Emergency shelters built based on multifunctional spaces are one of the main components of crisis management, which is carried out for various purposes by transferring people from hazardous or damaged areas to safe areas. Providing suitable spaces for the accommodation of refugees, establishing safe routes, warning and informing people about the possibility of danger, transfer and return planning and supporting are the main components of multi-purpose spaces. These components are defined according to the dimensions and scope of danger. Building multi-purpose land uses and paying special attention to them in urban development projects will help in optimization of crisis management processes, and create mechanisms to guarantee citizen security and achieve sustainable urban development. Paying attention to emergency shelters built based on multi-purpose land uses in military towns is of more importance and should be planned during peacetime. In fact, special attention should be paid to selecting and organizing multi-purpose spaces in these cities. Saravan, the center of Saravan city, is a town in Sistan and Baluchestan Province. It is a military town in southeastern Iran with a strategic importance from security and military point of view. Given its strategic location, the necessity of security and defense planning of the city based on the principles of passive defense is quite clear. Aspreviously mentioned,utilizing multi-purpose land uses as a strategy based on passive defensecan be considered an appropriate solution for defense planning of the city. Due to the spatial nature of data as well as multi-objective and multi-criteria nature of decision making, spatial analysis and site selection of multi-purpose land uses needs to be performed using a combination of geographic information system and multi-criteria decision making methods. Materials & Methods The presentapplied studyis performed using descriptive-analytical method. Data was collected from library and documentary sources and land use maps. Some information was also collected from the Statistical Center of Iran. ArcGISwas used to analyze collected data and produce relatedmaps including land use maps, mapsof sensitive urban centers such as military barracks, etc. According to the nature of the research and its field of study,geographical information system (GIS) was integrated with fuzzy multi-criteria decision making methods in the information analysis phase. Results & Discussion In order to analyze collected data, various criteria and indicators were first determined for selection of spaces and multi-purpose land uses based on studies conducted. Then, a special weight is allocated to each criterionusing verbally generated fuzzy methods andaccording to experts’ opinions and then SAW model was used to combine related GIS layers. Finally, the zoning map of Saravan city has been presented as an appropriate example for creating multi-purpose spaces and land uses. Indicators of site selection for multi-purpose land uses have been scored by experts to determine their effect and importance in spatial analysis of multi-purpose spaces in Saravan city. The opinions of 26 experts have been collected to determine this weight. The indicators were converted to GIS layers and presented after the integration of the final map. Conclusion Due to its strategic location and security-related issues, Saravan needs defense planning. Undoubtedly, shelters are needed to protect people againstthe enemy’s attacks in case of war. The necessity of paying attention to this issue has increased the importance of research on defense planning and passive defense in the field of urban planning. Passive defense in border towns focuses on defense planning and reduces the number of casualties. Shelters and multi-purpose spaces are also of this type. With the aim of spatial analysis and site selection for multi-purpose land uses, and in order toutilize existing land uses for urban defense planning, the present study has identified multi-purpose land uses in Saravan. Using geographic information system and multi-criteria decision making methods, these land uses have been located and appropriate situations have been identified for creation of multi-purpose spaces. Results indicated that usingexperts’ views, along with geographic information system, and multi-criteria decision making methods could be an appropriate way fordefense planning and site selecting for multi-purpose land uses. According to the final map which is produced using SAW model for locating and planning multi-purpose land uses, different appropriate areas exist for the location of multi-purpose uses. These areas are specified in the final map of Saravan. According to this map, northeastern areas of the city is considered to be suitablebased on all criteria. It can be concluded that the areas obtained fromGIS are scattered throughout the city and responsible organizations can use the final map for site selection. The largest area with the most suitable condition is located in the northeasternregion, and the southeastern, southern and southwestern regions seem appropriate. A vast region of the city (beginning in the northwestern region and reaching southeastern region) is in poor condition in terms of the criteria examined. Due to the 10 levels of classification used in the final map, the map shows different conditions even in this region, and more suitable situationscan be selected for multi-purpose land usescompared to other regions.
Majid Fakhri; Amin Faraji; Mehdi Aliyan
Abstract
Extended Abstract
Introduction
In recent years, protecting infrastructure, especially critical infrastructure, has become increasingly important because the economy of a region and the well-being of its inhabitants depend on the continuous and reliable operation of its infrastructure. These infrastructures ...
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Extended Abstract
Introduction
In recent years, protecting infrastructure, especially critical infrastructure, has become increasingly important because the economy of a region and the well-being of its inhabitants depend on the continuous and reliable operation of its infrastructure. These infrastructures are like arteries for survival of urbanism damaging .Some of infrastructures can have devastating effects on security, economy, and society at the regional and national levels. There are different systems and infrastructures in different countries, including Communication, electricity, gas and oil, banking and finance, transportation, water supply and government services infrastructure, which are critical infrastructures.
A review of various types of infrastructures shows that energy infrastructure is more important and plays a more significant role in comparing with other types of infrastructure.
Maintaining the security of this infrastructure against attacks and threats is one of the priorities of securing a country. One way to ensure security is to measure the spatial vulnerability of infrastructure. This article assesses the capacity of Yazd province against the vulnerability of energy infrastructure.
Materials & Methods
The information for this research has been extracted by documentary methods (including books, scientific articles, reports, etc.) as well as using the country's infrastructure database. Then, GIS layers of the energy infrastructure of Yazd province, including electric transmission network, electric plant, gas transmission lines, gas pressure regulation stations, oil transmission lines, oil products transmission lines, oil and gas storage tank and gas stations were examined.
The next step was ranking the importance of infrastructure elements with the DEMATEL model. Then, the infrastructure elements of Yazd province were prioritized with the analytic network process(ANP) model.
The next step was to prepare maps and GIS layers for each of the infrastructure elements ,by preparing them in Arc GIS and the priorities of the network analysis process model ;sothe final vulnerability map of the province was prepared.
Results& Discussion
After calculations of supermatrix coefficients, the results show the importance of these infrastructures in providing services to people and other infrastructures, as well astheattractiveness for each infrastructure element. Gas transmission network with the value of 0.1003, oilproducts transmission lines with the value of 0.0988, oil and gas tank with the value of 0.0995, have the most weight and importance, and gas stations with the value of 0.0485 has the least importance in comparing to other energy infrastructures in the Yazd province.
The results show that the central part of Yazd province is more vulnerable thanthe other part of province, because moreenergy infrastructuresareestablished inthe central part of Yazd province. Examination of the results on a smaller scale show thatthe vulnerability of energy network infrastructure inYazd,Meybod, Mehriz and Sadooghis high,butinBahabad, Khatam, and Abarkoohis low.
Conclusion
The results show that distribution of infrastructure in the Yazd province has not beenin a good model. The central part of the province is more vulnerable than the peripheralareas so that more than half of the infrastructure of the energy network (55%) is in very vulnerable zone and 18% of the infrastructure is in highly vulnerable zone;thus, observing the teachings of passive defense in the province deserves more importance.
Aboozar Vafaei; Kamran Dolatyarian
Abstract
Extended AbstractIntroduction Due to its particular natural, economic and social situation, Kashan as a second-rate city confronts a variety of problems such as horizontal and scattered expansion, unbalanced development of the city in different directions, the spread of marginalization and unauthorized ...
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Extended AbstractIntroduction Due to its particular natural, economic and social situation, Kashan as a second-rate city confronts a variety of problems such as horizontal and scattered expansion, unbalanced development of the city in different directions, the spread of marginalization and unauthorized constructions. These problems have become the basis for major changes in land use and land use incompatibility. Land use evaluation of Kashan city shows that this city has been encountering uneven growth in recent years and many of the surrounding areas that used to be agricultural lands, have gone to urban infrastructure and structures, especially the residential and industrial ones. Since one of the purposes of urban land use plan is the appropriate location of land uses in conjunction with the separation of incompatible uses from each other, accordingly, the current research aims to present applicable solutions for the optimal location detection and distribution of uses throughout the city and to separate incompatible uses from each other in order to achieve the major goal of urban planning, i.e., ensuring people's welfare by creating a better, healthier, more effective and pleasant environment by applying the spatial analysis tools of the geographic information system, while answering the following questions;What is the per-capita status of existing uses in Kashan with standard per capita in urban plans?What is the status of existing uses in Kashan regarding the compatibility index? Research MethodRegarding purpose, the type of research is applied and in terms of its method it is analytical-comparative; explicitly, the literature and sources have been initially examined and the theoretical framework of the subject has been compiled. Then the base map of urban land uses was prepared and reorganized in GIS environment. Subsequently, through surveys of the amounts of surfaces, the per capita for all types of uses was determined and annexed to the information of the base map in the form of separate layers in order to provide the basis for its use in the GIS environment. Afterwards, the evaluation of urban uses was proceeded regarding per capita standards and compatibility index by applying quantitative and qualitative method. Accordingly, the amount of land required by each use in the current situation was initially calculated and determined by specifying the ratio of shortages through the per capita standard and eventually, the location of each use in relation to neighboring users was analyzed in terms of compatibility index via GIS software using the overlap model (IO) and spatial analysis. The Geographical Area of the ResearchKashan city is the geographical area of the research that is currently the second most populous and industrial city after Isfahan city in the province. Results and DiscussionSince examining the compatibility of different uses of the city is the most significant element in evaluating urban land use, therefore this research has proceeded to explain the degree of compatibility and non-disruption of one use to carry out the activities of other uses using the compatibility index. Accordingly, the degree of compatibility of city uses in relation to neighboring uses was primarily drawn using the convenient table of mutual compatibility matrix, then the quality of city uses was investigated through field studies in terms of compatibility according to the amenable fields in explaining compatibility such as land size, slope, accessibility, urban facilities and equipment, air quality, sound, light and smell. ConclusionIn this research, the uses were examined and evaluated at both quantitative and qualitative levels. In the quantitative section, the current situation of the levels and per capita uses throughout the city was discussed with the standard per capita in urban plans. Consequently, statistical calculations showed that except for tourism and religious uses, other uses are encountering a deficiency of level. In the qualitative part, the degree of compatibility of land uses was investigated using the compatibility index through acquiescent components in the explanation of compatibility such as land size, slope, accessibility, urban facilities and equipment, air quality, sound, light and smell, through field studies in the form of mutual compatibility matrix. Finally, the location of each user in relation to neighboring users was analyzed in terms of compatibility index via GIS software applying the overlap model (IO) and spatial analysis. The results of the compatibility percentage of uses with neighboring use in Kashan show that residential use of more than 40 percent, educational use with more than 37 percent, administrative use with 36 percent, medical use with 27 percent and sports use with 19 percent in stand in relatively incompatible to completely incompatible conditions with their neighboring uses, and on the other hand, tourism use with more than 90%, religious and cultural use with more than 85%, and commercial use with more than 80% are in entirely compatible and relatively compatible conditions with their neighboring uses and take the least incompatibility with other uses.
Seyyed Ghasem Rostami; Aliakbar Yahyaabadi
Abstract
Introduction In recent years, studies in seismology have mainly focused on temporal and spatial analysis of earthquakes. This is important for crisis management due to a variety of reasons, including the necessity to estimate the magnitude and the occurrence time of the main aftershock in a given periodafter ...
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Introduction In recent years, studies in seismology have mainly focused on temporal and spatial analysis of earthquakes. This is important for crisis management due to a variety of reasons, including the necessity to estimate the magnitude and the occurrence time of the main aftershock in a given periodafter the mainshock.The present study seeks to identify the relationship between the magnitude and the occurrence time of the main aftershock in the first few hours after the mainshockusing the aftershock classification patterns. Various workshave been performed to model aftershocks of whichthe last centurystudies have yielded good results. However, providing a comprehensive description of how energy is released from seismic sources during an earthquakein different regionsis not easy. As a result, modeling of aftershocks is very complex and a precise model has not yet been provided for estimatingfeatures of the main aftershocks. Material and Methods During the preliminary investigation, magnitude of the mainshock and the number of aftershocks in the initial 12 hours were identified as two important parameters affecting the magnitude and the occurrence time of the main aftershock. However, this simple model lacks sufficient accuracy (accuracy of 0.5 in magnitude estimation and 5.8 hours in the estimation of the main aftershock occurrence time). Therefore, a polynomial function with higher number ofparameterswas used in the present study to reach a more accurate modeling. A linear polynomial model with 15 different parameters was introduced. These parameters includemagnitude of the mainshock, number of aftershocks during the initial time period, and in half and quarter of the period, and the number of aftershocks and mean temporal interval between aftershocks occurringin classes of 2.5 to 3.5, 3.5 to 4.5, 4.5 to 5.5 and greater than 5.5 Richter. The initial time period refers to the minimum number of hours needed after the mainshockto collect information about the aftershocks. Coefficients of occurrence time and magnitude of the main aftershock were calculated in the two proposed modelsusing 32 earthquake events and the least square method. These earthquakeshad occurred with a magnitude of greater than 5.6 from 2006 to 2020.In order to select the best model using the least mean square error (MSE), several models have been considered with a change in their initial time period (using for classification of the aftershocks) and secondary time period(the time duration at which the features of the main aftershock are estimated). Results Based on the mean square error, three models were introduced to estimate features of the main aftershock in short, mid and long-term. These models can be used to estimate features of the main aftershocks occurring 2, 8 and 20 days after the main shock, respectively. The short-term prediction model use aftershocks occurring during the first hour after the main shock to predict the magnitude of the main aftershock with a precision of 0.21 (MN) and its occurrence time with a precision of 3.1 hours. Mid-term prediction model also useaftershocks occurring during the first 3hoursafter the main shock to predict the magnitude of the main aftershock with a precision of 0.23 (MN) and the occurrence time with a precision of 19.3 hours. Finally, the long-term prediction model use aftershocks occurring during the first9hoursafter the main shock to predict the magnitude of the main aftershock with a precision of 0.22 (MN) and the occurrence time with a precision of 38.5 hours. Conclusion To evaluate errorsof the proposed models, information collected from 9 recent earthquakes in Iran and Turkey was used. Magnitude and occurrence time of the main aftershock ineach selected earthquake were calculated using short, mid and long term prediction models. Results demonstrate that these models can predict the magnitude of the main aftershock with an average error of 0.18 (MN). They also can predict the occurrence time of the main aftershock with an average error of 18.1 hours. It is worth noting that the proposed models havepredicted themagnitudeof these recentnine earthquakes with a mean error less than their accuracy estimated using the 32 earthquake events.
Zahra Rezaee; Mohammad Hasan Vahidnia
Abstract
Extended abstract
Introduction
Population growth, urbanization and land use change in recent decades have made floods one of the most devastating natural disasters in the world. Therefore, understanding this phenomenon, its effects and methods used to deal with it is considered to be among the most ...
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Extended abstract
Introduction
Population growth, urbanization and land use change in recent decades have made floods one of the most devastating natural disasters in the world. Therefore, understanding this phenomenon, its effects and methods used to deal with it is considered to be among the most important issues crisis management planners and policymakers in urban and rural areas should pay attention to. Iran faces many natural disasters among which flood is one of the most serious ones. Monitoring and controlling accidents, assessing damages and providing relief are among the main concerns of government and crisis management experts. Continuous monitoring before the occurrence, and accurate assessment during and after the event can decrease damages to human and natural resources. Preventing flood related hazards, organizing and managing flood water in channels and ultimately improving channels require identifying and determining flood zones.
Materials & Methods
Agent-based modeling (ABM) provides simulation and abstract systems used to identify patterns of land forms in the study area. As a new approach, agent-based modeling is used to develop simulation tools for complex phenomena in various fields such as natural disasters, biological studies and relief provision in flood occurrences. In fact, agent-based modeling (ABM) has been increasingly used to confront the risk of flood and its challenges in recent years. The present study applies fuzzy inference approach (using parameters affecting the occurrence of flood and remote sensing data) and agent-based modeling to prepare a flood risk map and provide a deterrent solution for flood risk management and decision making before the occurrence. In the fuzzy inference system, various maps are prepared showing parameters affecting the occurrence of floods such as slope, soil type and rivers. Then, Fuzzy Overlay model is used to define the flood risk zones and overlay the fuzzy parameters. The present study applies fuzzy gamma operator with a coefficient of 0.8 in the final fuzzy overlay calculation.
Results & Discussion
Comparing the results obtained from overlaid maps reveals that most flood plains are located in areas covered with Affisols (clay-rich soil) and low-lying arable lands and orchards. In agent-based modeling, GIS plugin of NetLogo was used to investigate the flood phenomenon based on the digital elevation model of the area. In this model, raindrop cycle was simulated in the DEM raster layer of Gilan. DEM layer can be used to calculate the slope (vertical angle) and slope direction (horizontal angle) of the ground surface. Simulated images shows the movement and accumulation of agents along the rivers and their surroundings and in low altitude areas. Analysis confirms the risk of floods in rivers and low-lying areas. Finally, georeferenced images of points in risk of possible flood (agents in the slopes of the study area), land use map and soil cover map can be overlaid to evaluate the obtained results. Results indicate that the highest number of agents (white markings on the map) are located in agricultural land use covered with Affisols while a relatively moderate number of agents are located in agricultural lands covered with Inceptisols. As previously mentioned, these agents simulate the amount of runoff accumulation due to atmospheric precipitation. Results indicate that precipitation models simulated using artificial intelligence lead to almost the same result Fuzzy analysis method shows (regarding the prediction of flood occurrence).
Conclusion
Finally, these two approaches are compared and their functions are examined. It should be noted that multi-criteria methods such as fuzzy inference approach has a higher level of complexity and accuracy, while methods based on artificial intelligence and agent-based modeling are faster. On the other hand, agent-based modelling method use relatively ready programs and thus has a lower level of complexity. The level of accuracy in this method is also lower than the fuzzy logic method.
Arash Azimi Fard; Ali Hosseininaveh Ahmad Abadian
Abstract
Extended Abstract
Introduction
Due to the complexity of frame processing used for positioning and mapping in visual odometry (VO) and visual simultaneous localization and mapping (VSLAM) algorithms, key-frame selection methods have been introduced to improve the performance and decrease the number ...
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Extended Abstract
Introduction
Due to the complexity of frame processing used for positioning and mapping in visual odometry (VO) and visual simultaneous localization and mapping (VSLAM) algorithms, key-frame selection methods have been introduced to improve the performance and decrease the number of frames required for processing while maintaining accuracy and robustness of the algorithms. Selected key-frames in these methods make a very good representation of all available frames. The current key-frame selection methods rely on heuristic thresholds in their selection procedure. Researchers have used several datasets to find optimum values for these thresholds through trial and error. In fact, proposed methods may not work as expected with a new dataset due to changes occurring in the sensor, environment and the platform.
Materials & Method
The present study has proposed an improved geometric and photogrammetric key-frame selection method built upon ORB-SLAM3, as the state of the art visual SLAM algorithm. The proposed Photogrammetric Key-frame Selection (PKS) algorithm has replaced inflexible heuristic thresholds with photogrammetric principles and thus guaranteed the robustness of the algorithm and the quality of the point cloud obtained from the key-frames. First, an adaptive threshold decides the allowable number of points whose line of sight zone has changed on a four-zone cone built upon each point. Increased number of points whose line of sight zone has changed means increased changes and displacements of the frame and thus, increased need for a new key-frame. Then, a 3*3 grid was formed in each frame and the number of points with a more than 30-degree change in line of sight angle (effective points) in each cell were counted. Later, the Equilibrium of Center Of Gravity (ECOG) criterion decides whether the distribution of points is appropriate using the center of gravity of the points inside the frame. Appropriate distribution of effective points within the frame shows a high geometric strength and thus will improve the strength of key-frames network. IMU sensor is not dependent on the position of the frames and the camera sensor. Thus, it independently obtains the key-frame in case significant changes occur in acceleration. The threshold value of acceleration has been experimentally considered equal to 1 meter per square second, which entirely depends on the type of robot. For ground robots with slower moving speeds, this threshold must be reset.
Results & Discussion
The present study has employed data collected by the European Robotics Challenge (EuRoC) flying robot containing the information collected by the synchronized camera and IMU information, as well as the ground truth data such as the robot trajectory and point cloud formed by the laser scanner. To evaluate the proposed method, extensive experiments have been implemented on the EuRoC dataset in mono-inertial and stereo-inertial modes. Then, trajectory of each algorithm was compared with the reference trajectory and point clouds formed by the key-frames were also compared. Apart from these qualitative evaluations, absolute trajectory error (ATE) obtained from running the PKS and ORB-SLAM3 algorithm 10 times were also compared quantitatively and finally, the error histogram was used to evaluate the point clouds. The processing time of each algorithm was also evaluated for each EuRoC dataset sequence. Results indicated that the proposed algorithm has improved ORB-SLAM3 accuracy in stereo-inertial by 18.1% and in the mono-inertial mode by 20.4% producing a more complete and accurate point cloud and thus, extracting more details from the environment. Furthermore, despite higher density of the point cloud, the error histogram has not changed significantly and fewer errors were observed in the ORB-SLAM3 algorithm.
Conclusion
Findings indicated that the PKS method has succeeded in extracting key-frames using photogrammetric and geometric principles. Apart from improving the positioning accuracy of the robot, the method has produced a much more complete and dense point cloud as compared to the ORB-SLAM3 algorithm. Also, dependency of the PKS method on the environment conditions and the type of system used (stereo camera or mono camera) was greatly reduced. Future studies can expand our key-frame selection method to include fisheye cameras or visual-only systems. More geometric conditions (near and far point condition and the vertex angle in the triangle formed by the points in the current frame, the camera and the corresponding points in the last key-frame) can also be added to the key-frame selection method.
Mohammad Karimi Firozjaei; Amir Sedighi; Najmeh Neisany Samany
Abstract
Introduction Remote sensing data provide valuable information for the agricultural section and natural resources managers. Nowadays, performance management and estimation via using various methods such as classification and mapping have gained great significance. An example of such data is the mapping ...
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Introduction Remote sensing data provide valuable information for the agricultural section and natural resources managers. Nowadays, performance management and estimation via using various methods such as classification and mapping have gained great significance. An example of such data is the mapping of crops cultivation and orchards at national and regional levels, which is one of the key tools in sustainable agricultural planning and management. These studies appear necessary especially in the field of strategic commodities such as rice and citrus which are among the most important food items for the Iranian people. The spatial information on agricultural lands in the field of agricultural planning and management can help the prevention of the spread of pests, management of the environmental stresses, crop performance estimation and vulnerability assessment in crop production. Field surveys and observations for crops mapping in the growing season in different years are very time-consuming, costly, and only suitable for small-scale studies. In contrast, over the past decades, remote sensing has been recognized as a suitable method for crops mapping for large areas in the shortest time and at low cost. Due to the climatic conditions of the areas in North of Iran, green spaces including vegetation and orchards, and rice fields are located near each other. At the time of the maximum growth of rice products, the spectral characteristics of these land covers are very similar. Therefore, the separation of these two land covers using satellite image classification process faces serious challenges. The aim of this study is to investigate the efficiency of the satellite images and the optimization algorithms for separating green spaces and rice fields from each other at the time of maximum growth. The present study differs from others in this field from two aspects; first, the study compares the capabilities of multispectral and hyperspectral satellite images with each other; additionally, it aims at comparing and evaluating the efficiency of the Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) so as to determine the optimal features for increasing the separation accuracy of green spaces and rice fields. Materials and methodology This research was carried out based on the two objectives of studying the capabilities of the Hyperion and Landsat images and comparing the efficiency of the PSO and GSA to determine optimal features for the separation of green spaces and rice fields. For this purpose, the two Landsat and Hyperion satellite images as well as ground data sets of the case study in North of Iran were employed. In the first step, preprocessing of the Hyperion and Landsat images was performed. In the second step, various features were extracted from the Hyperion and Landsat images using different spectral indices and transformations. In the third step, the Support Vector Machine (SVM) classifier was applied with two strategies, i.e. the usage of spectral bands and the usage of spectral bands as well as indices as the features in the classification process to extract green spaces and rice fields. In the fourth step, PSO and GSA were employed to extract optimal features from the Hyperion image to distinguish between green spaces and rice fields; then, classification was done with the extracted optimal features; and finally, the efficiency of PSO and GSA were compared to determine the optimal features for the separation of green spaces and rice fields using ground data sets. Results and discussion The results indicate that the use of Landsat image is not effective for the separation of rice fields and green spaces. In other words, due to the high spectral similarity of these land covers, a large percentage of pixels related to the two classes are mistakenly classified in another class. However, the accuracy of the producer and user relating to each class has increased by an average of 10 percent with the addition of spectral indices to the classification process. Using Hyperion image is more effective than Landsat image for the separation of rice fields and green spaces. Moreover, the accuracy for the separation of rice fields and green spaces has increased with the simultaneous consideration of the bands and spectral indices in the classification process. It should be noted that one of the key factors in the efficiency evaluation process of the classification methods is the processing time. The results of using optimization algorithms for determining the optimal features indicate that out of the 150 spectral features (including 140 Hyperion image bands and 10 spectral indices and transformations), using PSO and GSA, only 25 and 31 optimal features were selected for the separation of green spaces and rice fields, respectively.The use of optimal features in the classification increases the accuracy for the separation of green spaces and rice fields more, compared to the use of all features in the classification. Additionally, GSA is superior to PSO when used for extracting optimal features for the separation of green spaces and rice fields. Conclusion The results of this research indicate that the separation accuracy of green spaces and rice fields using Landsat image,is less than that of Hyperion image. With the addition of spectral indices to the classification process, the separation accuracy in both Landsat and Hyperion data increases. Moreover, using an optimization algorithm to determine the optimal features in the classification process will increase the separation accuracy of green spaces and rice fields. Given the overall accuracy values, the efficiency of GSA for separating green spaces and rice fields is higher than PSO.
Geographic Data
Mehran Maghsoudi; Mohamad Fathollahzadeh; Hamid Ganjaeian
Abstract
Extended Abstract
Introduction
Surface winds move and transport soil particles on the ground and thus, affect the intensity of erosion to a great degree (Tage Din et al, 1986: 118). Various studies have found a decreasing trend for surface wind speed in different parts of the world in recent years. ...
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Extended Abstract
Introduction
Surface winds move and transport soil particles on the ground and thus, affect the intensity of erosion to a great degree (Tage Din et al, 1986: 118). Various studies have found a decreasing trend for surface wind speed in different parts of the world in recent years. This decrease has been more widely reported in mid-latitudes (McVicar et al, 2008). Continuous drought in consecutive years is one of the factors that can reduce soil moisture and stop the growth of vegetation cover. (Hereher at el, 2009). Iran is located in the arid belt of the world and two thirds of its total area is located in these arid regions (Maghsoudi, 2006). Previous studies have shown that 17 provinces of the country are affected by wind erosion, among which Kerman faces a more severe conditions. Iran has more than 20 relatively large ergs and several small ergs covering an area of approximately 36,000 square kilometers (Mahmoudi, 1991). The present study investigates different characteristics of winds and its effects on morphology and displacement of sand dunes using Sentinel-2 optical and Sentinel_1 radar images.
Materials and Methods
Due to the lack of any synoptic station in the Lut Desert, related data including wind direction and speed were collected from 6 neighboring stations (Bam, Dehsalm, Zabol, Shahdad, Nusratabad and Nehbandan). Then, a wind rose and a sand rose graph were prepared for each station using WR Plot and Sand Rose Graph software. Resultant force vector acting in the displacement of sands and formation of sand dunes was determined. Following an examination of wind characteristics in the study area using Sentinel-2 optical images collected in the 2016 - 2019 reference period, changes of sand dunes and direction of their movements were also analyzed. In order to investigate vertical displacement in the region, radar interference method and SBAS time series have been used. This method only uses pairs of images in which vertical component of the baseline is less than its critical value, and also have a minimum baseline time. 45 Sentinel_1 radar images were used in the present study to measure radar interference.
Results
Recorded data in Dehsalm, Nehbandan, and Nosrat Abad stations indicate that winds blowing in these stations affect the Lut Desert. The prevailing wind recorded in Dehsalm station blows in northwest to southeast direction of the Lut Erg, while in Nehbandan station, the prevailing wind blows in north to south direction of this Erg. The prevailing wind in Nosrat Abad station blows in southeast to northwest direction of this erg. Sand rose graphs show that DPt in Dehsalam station equals 422.6 and in Nehbandan station equals 484.2. Since both DPts are more than 400, wind in this region has a high energy level and is potentially capable of sand displacement. Changes of sand dunes and direction of their movements were analyzed using Sentinel-2 and Sentinel-1 images in 2016-2019 reference period.
Discussion and Conclusion
Hourly wind speed and direction data in Nehbandan, Dehsalam, and Nosratabad stations were investigated in the present study to evaluate their impact on geomorphological changes in the Lut Erg and its sand dunes. Results indicate that the prevailing wind in these stations blows in north, northwest and southeast direction towards the Lut Erg, respectively. Investigating wind speed changes in Nehbandan station shows that during the last 34 years, average monthly wind speed in this station has decreased from 3.7 meters per second in 1986 to about 2.2 meters per second in 2020, which means a 1.5 meters per second decrease has occurred during this period. Apart from wind speed and direction data, Sentinel-2 optical images were also used to monitor changes in sand dunes of the Lut Erg. Results indicate that during the 2017 - 2018 reference period, most changes have occurred in the sand dunes of the northwest and northeast regions and the margins of this erg, while in the 2018 - 2019 reference period, most changes have occurred in the northwest and southeast regions of the Lut Erg. Analysis of satellite images indicates that the direction of wind force vectors is consistent with the direction of sand transport vector. In other words, sand dune changes in the Lut Erg have occurred under the influence of winds blowing in northwest and southeast directions, which is consistent with the direction of the sand transport vector in plots prepared for the three stations (Nehbandan, Dehsalam, and Nusrataba).
In order to validate the results of wind direction and speed analysis and remote sensing of optical images, vertical displacement of the erg surface was measured in 4-year periods using Sentinel_1 radar images and SBAS time series. In general, southern parts of the Lut Erg and especially sand dunes in these parts have experienced an increase in elevation, while the northern parts of Erg have experienced a decrease in elevation. This can be due to erosion and deposition of sediments in the southern regions of the Lut Erg, which is consistent with the sand rose and wind rose graphs prepared for the region .
Qassem Safari; Mohammad Reza Malek
Abstract
Extended Abstract
Introduction
Earthquake is one of the most frequent natural hazardsannually leading to numerous human and economic losses. Both in the planning stage and after the earthquake occurrence in the relief phase,findingappropriate sites for temporary housing is considered to be one ...
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Extended Abstract
Introduction
Earthquake is one of the most frequent natural hazardsannually leading to numerous human and economic losses. Both in the planning stage and after the earthquake occurrence in the relief phase,findingappropriate sites for temporary housing is considered to be one of the most important issues in reduction of damages caused by earthquake. Temporary housing, especially in a crisis situation is always accompanied by elements of uncertainty. Hence, definitive and classical approaches normally do not lead to acceptable results without involving elements of uncertainty. Although using methods based on fuzzy logic and fuzzy set theory are conventional and appropriate for uncertainty modeling, these methods also have their own disadvantages. For an instance, they require a certain and definitive membership function for each parameter. Moreover,fuzzy theory cannot describe verbal variables related to doubt and hesitation.
Temporary housing is always accompanied byuncertainty.Thus, fuzzy theory cannot lead to reliable results in this regard. However, in case sufficient information is not obtained using fuzzy theory, intuitionistic fuzzy logic isconsidered to be an appropriate solution for this problem and uncertaintymodeling. Despite various applications of intuitionistic fuzzy logic in uncertainty modeling, few researches have focused on this method.
Materials & Methods
Designing a qualitative model based on human knowledge requires a rule-based inference system, which is called an Expert System. This system consists of several parts. In the knowledge-based part, data and a set of rules, which are based on expert knowledgearesavedin the form of logical sentences. The input of this system is a set of numbers fuzzified in the inference engine by a set of fuzzy rules. Then,defuzzification is performed to map the fuzzy set and reach a certain point. In other words, the outputs must be readable and easy for the users.
The present study takes advantage of fuzzy and intuitionistic fuzzy approaches todetermine optimal sites for temporary housing. Furthermore, determinant factors of danger and safety followinganearthquakeare used to identify safe places for sheltering in such situations. The present study has applied layers of faults, hospitals, emergency and medical centers, fire stations, parks and green spaces, and roads as determinant factors. New spatial layers were produced for each ofthe aforementioned layers using distance and other similar functions. Then, trapezoidal functionwas used to determine membership and non-membership function of each layer in both fuzzy and intuitionistic fuzzy methods. Membership functions obtained from these methods are different in that they assign different membership values to the pixels surrounding the layer. Following the definition of membership and non-membership functions for each layer in both methods, temporary accommodation maps were obtained using the classical fuzzy as well as intuitionistic fuzzy methods.
Results and Discussion
The results obtained from these two methods were not identical. The main reason for this difference is that they treat data uncertainty differently. Furthermore, the results of membership and non-membership functions inintuitionistic fuzzy are not complementary. This provides us with a powerful tool for interpretation and, of course, decision making about the study area. As the first case, membership and non-membership degreesequal zero and one implying that the membership degree equals one and the non-membership degree equalszero. This occurs when the method identifies the area as quite appropriate for temporary housing after the earthquake. In this case,results are determinative, and data can be used in the area. In the second case, membership and non-membership degreesare low, which occurs in areas lacking enough information. It implies that more information is neededin such areas for decision making. The third condition takes place when both membership and non-membership degrees equal 0.5. In such a case,it can be conclude that either the stated variable belongs to the area with a membership degree of 0.5, or the variable doesn’t belong to the area with a non-membership degree of 0.5. In the fourth condition, the membership degree is high and the non-membership degree is low. In this case, the results can be trusted and used in decision-making. The fifth condition is in contrast with the fourth case. It occurs when the non-membership degree is high and membership degree is low. Under this condition, it can be concluded that the results are not reliable.
Conclusion
The proposed method and model were implemented in the second district of Tehran. According to the results, it can be concluded that the proposed approachperforms better than theclassical fuzzy approach, especially in the presence ofuncertainvariablesand lack of adequate data.
Saeid Hamzeh; Afshin Amiri
Abstract
Extended Abstract Introduction As a type of mass movement involving slow or rapid movement of soil, rock material or both on the lower hillsides, landslide is under the effect of gravity.Landslide is recognized as one of the most common geological disasters causing worldwide damages and casualties.Landslide ...
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Extended Abstract Introduction As a type of mass movement involving slow or rapid movement of soil, rock material or both on the lower hillsides, landslide is under the effect of gravity.Landslide is recognized as one of the most common geological disasters causing worldwide damages and casualties.Landslide susceptibility maps provide important and valuable information,including time scale of possible future landslides, which are usedfor predicting landslide hazards. Since predicting the time of landslide occurrence is beyond the capability of science and knowledge, identifying areas susceptible to landslide and ranking them can extensively restrict the damages caused by landslide. Therefore, it is essential to zone landslide risk and identify factors affecting it. Analytic Network Process(ANP) is aGIS-based Multi-Criteria Decision Analysis(GIS MCDA) method successfully applied to many decision-making systems. The present study seeks to evaluate landslide risk and achieve a zoning map for the sub-basin under study using ANP and Weighted Overlaymethods. Materials and Methods Based on the literature and using different experts’ viewpoint, criteria affecting landslide risk were identified and five major criteria including topography, land use and land cover, geology, hydrometry and infrastructure were selected. The selected criteria include the following sub-criteria: slope, slope direction, curvature, elevation, lithology, soil type, land use, vegetation density, distance from roads, distance from habitat, river and drainage density and precipitation. The effective factor layers were standardized and a specific scale was defined for their units.Then, each layer was assigned a weight based on its role and importanceusing Analytic Network Process.Proposed to modify Analytic Hierarchical Process(AHP), this method (ANP) relies on the analyses of the human brain for complex and fuzzy problems.Network Analysis Process generally includes the following steps: determining indicators, criteria and options;classifying identified criteria into clusters and elements; determining the relationship between clusters, elements and options; performing pairwise comparisons between clusters, elements and options, and finally calculating the final weight of elements and options. UsingWeightedOverlaymethod, these elements were then integrated with their related coefficients and the final landslide risk map was obtained. Results and discussion Each criteria and sub-criteria were weighted using Analytic Network Processmethod.Topographic and land cover criteria had the most and hydrographic criteria had the least impact on the landslide occurrence. According to the final map, most landslides have occurred in eastern and southern slopes at an altitude of 500 to 2,200 meters. Moreover, 17/31% of the study area was located in the very high-risk class and 33% in the high risk class (about half of the area has high potential of landslide). Previous landslide data were used to assess the landslide zoning map results. Results indicate that most landslides have occurred in the high risk class (about 35% of landslides) and only about 4% of landslides have occurred in the very low risk class. Conclusion Landslide is one of the natural hazards causing serious harms and problems for human life. Identifying the factors affecting landslide and zoning its hazard is especially important for the identification of risky and susceptible areas.So, landslides were selected as one of the main topics of the study with the aim of controlling and managing its hazards.The ANP network analysis method was used to model and predict landslide risk in this research.Each criteria and sub-criteria were weighted and overlapped to producethe map of relative landsliderisk.The lowest risk was observed in the northern parts of the region, and the highest landslide risk was observed in the northern hillsides with higher humidity.WeightedOverlaymethod and network analysis model were effective in predicting landslide susceptibility and producing landslide zoning map.
Hadi Fadaei
Abstract
Extended Abstract Introduction One of the major environmental issues and requirementsof the contemporary worldis the acquisition of knowledge and related technologies. Urban Heat Island (UHI) refers to the occurrence of higher surface temperature in urban areas compared to the surrounding rural areas ...
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Extended Abstract Introduction One of the major environmental issues and requirementsof the contemporary worldis the acquisition of knowledge and related technologies. Urban Heat Island (UHI) refers to the occurrence of higher surface temperature in urban areas compared to the surrounding rural areas due to high urbanization. Urban Heat Island (UHI) is an important ecological effect of rapid urbanization. While the temporal and spatial importance of UHIs and their causes have been discussed in previous studies, precise identification of the morphology and shape of the earth and its relation with UHIs have not been studied. Urban heat islands occur primarily due tourban developmentand changes in land surface. This has created unfavorable conditions and many problemsfor citizens. Vegetation cover can reduce the effect of heat island. Satellite data can be used to determine the distribution of urban heat islands, but new methods of measurement are still needed to get better results.Ground data can also help in validation of remote sensing analysis. The present study has investigatedurban heat islands occurring in the city of Tehran and its suburbs due to urbanization and traffic. Method The present study has been carried out in Tehran, the capital city of Iran, located in the northern part of the country,on the southern slopes of the Alborz Mountain Range, along 51⁰ to 51⁰ 40′ easternlongitudeand 35 ⁰ 30′ to 35 ⁰ 51′ northernlatitude. According to the latest population and housing census in 2011 performed by the Statistical Center of Iran, Tehran has a population of 8,154,051 and still is the most densely populated city of Iran with a clear demographic difference with other cities of the country. The study area borders with mountainous areas of the north and desertsof the south, thus the southern and northern regions of the study area have different climates. The northern regions have cold and dry climates, while the southern parts suffer from hot and dry climates. The elevation varies from 900 to 1800 meters. This huge difference inelevationis due to the vast area of the city. In Tehran metropolis, the average annual temperature varies between 18 and 15 ° C, and different parts of the city have an average temperature difference of 3 ° Cdue to the elevation difference in the city. Average monthly relative humidity including minimum and maximum relative humidity recorded at Mehrabad station shows that in in the morningof July to January, humidity changes from at least 38% to a maximum of 79%. Midnight relative humidity varies from 15% to 18% in June to 47% in February. The annual rainfall in Tehran is mainly influenced by the difference in elevation and varies between 422 mm in the north and at least 145 mm in the southeast. The number of rainy days also follows the same pattern and varies between 89 days in the north and 33 days in the south. Also in this urban area, 205 to 213 days of each yearhave a clear sky with some cloud. In this exploratory study, Landsat 8 satellite images for Tehran were obtained and processed (geometrical, radiometric and atmospheric corrections). The Operation Land Imager(OLI)with its three new bands: a deep blue band for coastal / aerosols studies (band 1), a short-wave infrared band for cirrus cloudsdetection and Band Quality Assessment (Band 9), and an Infrared Thermal Sensor (TIRS) which offers two high resolution thermal bands (approx. 30 m) (band 10, 11) were used. In addition, two of the valuable thermal bands at 10.9 µm and 12.0 µm have Landsat 8 images. In this study, spectral reflections of all terrestrial members of spectral phenomena were obtained based on the total wavelengths of Landsat 8 (wavelengths of 430-2290 nm). For UHI estimation,surface temperature can be obtained from the two thermal bandsand improved using split-window methods.The relation between thermal islands can be calculated using air pollution ground data. The present study tries to select suitable indices such as Normalized Difference Vegetation Index (NDVI). The vegetation index (NDVI) of land surface was calculated using spectral bands. Results The LST map was produced using Landsat OLI 8 satellite images. Temperature in this map was obtained using standard deviation from the classified values,and areas affected by the UHI were identified subsequently. According to the LST map, the surface temperature varies between 21.5 ° C and 57.9 ° C. On the day of imaging, the lowest average temperature of water was 35 ° C and the maximum average temperature of bare lands was 48 ° C in the study area. Recommendations It is recommended to use spectral reflectance measurements such as field spectroradiometer in natural conditions to evaluate the spectral reflectance accuracy. At a later stage, spectral reflection of different phenomena can be used to classify satellite images and examine their relationship with the urban heat islands
Amirhossein Halabian; Nader Parvin; Roya Naghibzadeh
Abstract
Extended Abstract
Introduction:
Due to the kind of its usage in a relatively long period, the analysis of temperature levels of modern cities is among the most important subjects that can be considered in the field of geography and environment, and its results can be used in promoting the science and ...
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Extended Abstract
Introduction:
Due to the kind of its usage in a relatively long period, the analysis of temperature levels of modern cities is among the most important subjects that can be considered in the field of geography and environment, and its results can be used in promoting the science and solving the problems of today’s societies. The effect of temperature on climate, is one of the crucial indexes of this procedure, especially in metropolises. The rise in the land surface temperature, which is an indicator of the heat intensity, is among the important elements for identifying theweather changes. The emergence of heat in cities is one of the most known forms of such changes. Urban heat islands are indicated by a temperature inversion and annoying temperatures throughout winters and summers. The temperature of some cities or urban areas has remarkably grown compared to the suburbs or rural areas around them. This phenomenon, called urban heat island, has caused numerous problems.
The term “heat island” was proposed by Havard for the first time almost a century ago in 1833 (Sook, 2004: 10). Afterward, numerous studies were carried out in the large and industrialized cities of the world, whoseresults demonstrated that civilization has exerted significant changes in the meteorological parameters and properties of the ground surface, and consequently, remarkable variations in local climate (Mousavi Baygi et al., 2012: 36).
Research objectives:
The present research is aimed at identifying the places with high heat, which have created the known thermal patterns in theArakcity in Iran. Assessment of the spatial-temporal variations of the urban heat islands can be used as a critical component in the management strategies of natural resources and environmental changes, whose results can be useful for environmental, regional, and urban planners.
Methodology:
The studied area, Arak, is the capital of the Markazi Province in Iran, with an area of 304.8 km2 at 1755 m above mean sea level. The city has temperate weather tending to cold and semi-arid. According to enactment in 2011, Arak has five municipal districts.
The research method was analytical-statistical, and an effort was made to evaluate the relationship between land surface temperature and land cover of the city.
In order to evaluate the development of hot places in Arak and determine its urban thermal patterns and heat islands in the long term, the data of the satellite images of the Landsat scanners 4, 5, 7, and 8, including the data of the TM scanners of Landsat’s 4 and 5, Landsat 7 (+ETM), and Landsat 8 (OLI/TIRS), during the period 1985-2017 were used. These images include two sets of reflective spectral and thermal bands. The thermal bands were used to identify the surface temperature and thermal islands, and the reflective bands were employed to apply the indexes of image processing. The data of the TM, +ETM, and OLI/TIRS scanners were provided in the bands 6, 8, and 11, respectively. The data of the thermal band 6 of Landsats 5 and 7 with wavelengths of 10.40-12.5 micrometers and the band 10 of Landsat 8 with wavelengths of 10.60-11.19 micrometers were used to calculate the surface temperature distribution patterns of Arak. The bands 3 and 4 of Landsats 5 and 7, along with bands 4 and 5 of Landsat 8, were also utilized to calculate the NDVI index (NASA, 2014). In the global imaging system, the images of the Arak areaexist in the 165th And 36th row.
Generally, the following steps were taken to analyze the urban heat islands of Arak:
Calculation of LST and spectral radiance
Conversion of the calculated radiation to Kelvin temperature
Calculation of the temperature levels of five districts of Arak
Calculation of the density percentage of the fourth level of temperature (hot points of the city)
The minimum, maximum, and average temperatures of Arak
Calculation of normalized difference vegetation index (NDVI)
Calculation of the urban thermal field variance index (UTFVI)
Results and discussion
Evaluation of the land surface temperature changes and patterns
The analysis of the vegetation variations demonstrated that depending on different uses of urban lands, vegetation is in accordance with the temperature level. Generally, the low temperature in the southwest of the city, which was observed in the land surface temperature maps, is caused by the gardens of Senejan and Karahroud cities. The eastern and southeastern parts of district 1, which has industrial uses, streets with heavy traffic, and accumulation of uses, and the north of the city, i.e., the north of district 3 with the accumulation of residential uses and heavy traffics, have higher temperatures. Generally, during the study period on vegetation, all areas having this usehad considerable changes, except for the northwestern part. Most of the vegetation in the study period was concentrated in districts 4 and 5, which included the gardens of Senejan and Karahroud. However, other parts of the city, including the northwest and, to some extent, the city center and district 1, whose vegetation includes several parks and green spaces, show decreasing changes in temperature.
Based on the results obtained from evaluating the urban thermal field variance index (UTFV) of Arak, using 20 land surface temperature (LST) maps and normalized difference vegetation index (NDVI), obtained from Landsat satellite, (TM), (ETM+), (OLI/TRS), the very hot temperature level of Arak was widely observed in the north, northeast, east, and southeast of district 1, north and northwest of district 3, west and southwest of district 2, and west ofdistrict 5.
Conclusions
The evaluation of the LST maps to identify the hot points and urban thermal patterns revealed that most of the hot points are located in the areas with idle lands in the suburbs. These lands are mostly observed in the recently developed areas of the suburbs, including districts 1 and 3. Inside the city, most of the hot places conform to the formation of thermal patterns close to industrial towns, streets with heavy traffic and high pollution, and residential areas with dense and urban decay.
The largest area of the third temperature level is observed in district 1 due to the presence of industrial towns, dense residential towns, cultural and governmental organizations, heavy traffics in the streets, the northern and southern belts in the district, and idle lands in the north and east of the district. The presence of the industrial towns and factories in the city of Arak, especially in district 1, is one of the effective factors in increasing the heat and creating thermal patterns. The thermal patterns in district 1 had the highest intensity in 1988/09/08 and 2017/01/08 during the study period.
Ilia Laaliniyat; Mousa Kamanroudi Koujori; Tajeddin Karami
Abstract
Extended AbstractIntroductionThe third millennium has been called the age of urbanization and the urban population is expected to reach about 6.25 billion by 2050. The United Nations also estimates that the urban population of developing regions will grow at an average annual rate of about 2.02 percent, ...
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Extended AbstractIntroductionThe third millennium has been called the age of urbanization and the urban population is expected to reach about 6.25 billion by 2050. The United Nations also estimates that the urban population of developing regions will grow at an average annual rate of about 2.02 percent, from 2.67 billion in 2011 to 3.92 billion in 2030. Indeed, the urbanization process is a phenomenon that has become increasingly concentrated in developing countries in recent decades. Although the pace of change varies considerably between countries and regions, in fact all developing countries are becoming increasingly urbanized. The increase in urbanization has caused many problems in urban areas. This has led to the fact that today land use management of urban infrastructure has become the main challenge of many planners and city managers. Accordingly, this study seeks to investigate the scattering around the Tehran-Eyvanekey communication axis, so Pakdasht cities with about 210 thousand people , Sharifabad with about 12,000 people and Eyvanekey with about 12,000 people, make it one of the busiest axes in the metropolitan area of Tehran. Research MethodsThe main purpose of this study is to analyze the process of space expansion and modeling in the axis of Tehran Eyvanekey between 1985 and 2020 using remote sensing data and GIS. To have a comprehensive study of spatial organization of this metropolis, a deductive or inductive approach with a practical nature has been used. The basis of the study is based on using the satellite data and images (Landsat multi-time images) related to different years. Using IDRISI, GIS and GOOGLE EARTH softwares and Fuzzy Artmap LCM, MARKOV and CA models. Discussion resultsIn this study, in order to evaluate the pattern of expansion of built areas in the corridor of Tehran to Eyvanekey, TM and ETM + images of Landsat satellite related to the years 1985, 2000, 2011, and 2020 have been used. Based on this, the amount of land use changes in the four periods is as follows: The most expansion of practical surfaces in the axis of Tehran-Eyvanekey with an area of 223250 hectares, dedicated to built areas with an increase of 30,495 hectares over the last 35 years. After identifying the urban expansion pattern of Tehran-Eyvanekey corridor, in the next stage, in order to simulate how land use changes in the axis of Tehran-Eyvanekey for the year 2031, the method of automatic cells and chains has been used. For this purpose, to simulate land use changes in the axis of Tehran Eyvanekey in 2031, land use maps in 1985 and 2020 were used. The results show that according to the trend of urban growth in the region in 2031, the land area will reach more than 50,000 hectares. Also, according to the growth rate of urban areas in this region, it can be seen that during different periods, we see a kind of exponential growth in the study area, so that for the period 1985 to 2000, about 240 hectares per year have been built. This trend of growth has expanded and in the next period, ie 2000 to 2011, this number has reached about 580 hectares, and finally in the last period, ie 2011 to 2020, we have witnessed the expansion of about 2251 hectares per year in the built lands, which can be signs of accelerative urbanization. Therefore, the strategy of increasing physical density and using related methods to guide the development of the city towards greater sustainability, should be on the agenda of planners and those in charge of urban affairs. ConclusionModeling land use changes is an effective way to obtain information about how land use changes over time as well as the factors affect it. So, in order to analyze the process of space expansion and modeling in the axis of Tehran-Eyvanekey, it was modeled over a period of 35 years. The results showed that most of the land use changes during this period are related to the built lands, which due to the location of the built areas along the main arteries has a northwest-southeast pattern that is affected by urban growth in the metropolis of Tehran. As a result, they live in these areas, which are either engaged in the urban industries of these areas or use the satellite cities in this corridor as dormitory cities. Interestingly, as we move away from the main center, the metropolis of Tehran, the rate of urban land expansion decreases, which indicates that due to the low cost of housing in satellite cities, this area is a dormitory for the metropolis of Tehran.
Homayoun Khoshravan
Abstract
Extended Abstract:
Introduction
Increased density of Co2 in the atmosphere during the Anthropocene epoch has resulted in pervasive concerns for the global environment. Global warming has resulted in sea level rise and coastal flooding. Forecasting has indicated that a vast area of coastal countries ...
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Extended Abstract:
Introduction
Increased density of Co2 in the atmosphere during the Anthropocene epoch has resulted in pervasive concerns for the global environment. Global warming has resulted in sea level rise and coastal flooding. Forecasting has indicated that a vast area of coastal countries and their economic and social infrastructureswill be damaged due to 200 cm sea level rise by2100. Sea level rise in oceans has caused coastal erosion and flooding. Thus, it is considered as a real threat to coastal environment. The Caspian Sea environment has reacted differently to climate changesduring the last 70 years and vast areas of its coastal lagoons have dried. Therefore, the present study primarily seeks toinvestigate ecological variations of coastal habitats in the Gorgan Bay during the period of 1995 to 2019.
Materials and methods
Gorgan Bay and Miankaleh Lagoon are considered to be among global biosphere reservesand the most important protected areasalong the southern coasts of the Caspian Sea. The present study has evaluated coastal variations, such as shoreline displacement, changes in the depth of sea bed, land cover and coastal habitats using satellite images and GIS processing. Shorelines of Gorgan Bay are determined usingremote sensing software Envi 5.3, while land cover and coastal habitats are evaluated through GIS processing in Arc – Map 10. 5. The shoreline is determined through the calculationsperformedonthe proportion of green and blue bands in reflected electromagnetic waves and histogram thresholding of near infrared (NIR) spectrum in Envi 5.3. The total area of Gorgan Bay was determinedusingthe Normalized Distance Water Index (NDWI).The most important land covers and coastal habitats are classified using Support Vector Machine (SVM). Finally,variations of coastal habitats are calculated using Change Detection Workflow index and the final maps areproduced in Arc Map 10.5.
Results and discussion
Results indicate that due to about 150 cm decrease in the Caspian Sea level from 1995 to 2019, the total area ofGorgan Bay has faced about 176 km decrease. Bathymetric maps shows that the depth of Gorgan Bay has decreased dramatically along the East to west side. The depth of the Ashouradeh and Chopoghlei inlets have also decreased and vast areas of these water bodies haveturned into arid islands. The Gorgan Bay is connected to the Caspian Sea through some narrow channels. The most important land covers and coastal habitats of the Gorgan Bay in 2019 include sandy beach (2%), salt marsh (7%), brackish marsh (14%), wetland (15%), mudflat (7%), coastal forest (10%) and coastal lagoons (45%). The total area of coastal lagoons, vegetation covering and sandy beaches have decreased from 1995 to 2019 and the area of the brackish marsh, salt marsh, mud flat and pit wetlands have increased at the same time. The total area of sandy beaches have decreased about 52 Km2 since 1995.Instead,the area covered by salt marshes and brackish marshes have increased by about 87 and 60 Km2 during the same period.62 Km2 of mud flat have been created during the same time,and thus, the area of Miankaleh Lagoon and Gorgan Bay have decreased by about 176 Km2. The environment of Gorgan Bay and Miankaleh Lagoon is directly related to the fluctuations in theCaspian Sea level. Survival of these coastal lagoons depends on permanent water exchange between the Caspian Sea and Gorgan Bay. Rapid fluctuations of the Caspian Sea level and high levelof deposition are considered to be among the most important factorsof coastal habitats destruction and ecosystems displacement. These natural phenomena happened twice during the Anthropocene period (1945- 1978 and 1995-2019).
Conclusion
Results have confirmed that arid ecosystems have replaced aquatic ecosystems in study area. The main results of the study have confirmed that the fluctuation in the Caspian Sea level has direct impact on coastal habitats of the study area and decreasing sea level could change marginal ecosystems. Due to the decrease in water exchange volume rate between the Caspian Sea and Gorgan Bay during the 1995- 2019 period, a 32 percent decrease has happened in the area ofGorgan Bay and salt marshes have dominated along the Gorgan Bay coastal area. Unfortunately, the continual decrease inthe Caspian Sea level can destroy biodiversity and coastal habitats in the future. Therefore,integrated coastal zone management (ICZM (is influential insaving and preserving of the Gorgan Bay.
Geographic Information System (GIS)
Zhila Yaghoubi; Ali Asghar Alesheikh; Omid Reza Abbasi
Abstract
Extended AbstractIntroductionSelecting a suitable place for a new retail store is a very important decision since new shops cost a lot and new retailers puts themselves at financial risk. Physical location of stores affects the consumer's perception of their first purchase and their subsequent loyalty ...
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Extended AbstractIntroductionSelecting a suitable place for a new retail store is a very important decision since new shops cost a lot and new retailers puts themselves at financial risk. Physical location of stores affects the consumer's perception of their first purchase and their subsequent loyalty to the store. Therefore, spatial analysis is very important for retail stores. Site selection for retail stores has always been difficult and the current competitive market has made decision making even more difficult since stores face increased competition and consumers have many options to satisfy their needs. They generally choose a suitable store in their vicinity which provides high quality, cheap, and diverse products. Therefore, markets and especially retailers shall follow an accurate and valid location strategy for new stores. Retail stores have various marketing and customer service strategies. Marketing strategies require a lot of information about different aspects such as customers, shops, competitors, and products. Many marketing strategies only provide information about consumer behavior or customer satisfaction. However, spatial aspects are more important and in fact determine future success of a store. Several methods are used for spatial analysis in retail sector. The present study use a multiplicative interaction model to forecast sales of confectionaries. This can help retailers develop strategies and find an optimal location for their new stores. Materials & MethodsThe present study has developed a location-based marketing model for online confectioneries in Tehran which can improve site selection strategies of new confectioneries. This marketing model is based on the multiplicative competitive interaction model (MCI) of the retail location theory. To do so, characteristics attracting customers to confectioneries are determined and related data are collected from the Snappfood online platform through web crawling. ArcMap software is then used to analyze and process the collected data. After data normalization, MCI model is implemented using Python programming language. The model is then calibrated using 80% of the collected data and the ordinary least squares (OLS) method. The model is then evaluated using root mean square error (RMSE) method and the remaining data. Results and DiscussionMean errors obtained for districts number 1 to 22 of Tehran municipality show high accuracy of the model. Snappfood site lacked any information about districts number 9 and 18 and thus these districts were not considered in the calculations. Depending on the available data, other districts showed different levels of accuracy. Results indicate that district number 22 had the lowest level of accuracy and district 17 had the highest level of accuracy. In general, this model predicts customer behavior with an error rate of 17.03%. Results of the present study show the probability of purchasing from each confectionery which can be used to map market potential for a new store. This map determines the best place with maximum sale and helps in site selection for new stores based on specific features of the store, competitors and the environment. ConclusionsMCI model predicts sales. From a geomarketing perspective, this model shows that distance between customers and the store and accessibility affect location strategies in new stores. Variables such as pricing and customer satisfaction (scoring) are used to improve the goodness-of- fit of the model. This precise method identifies some key factors to success in a retail strategy. It predicts the probability of purchasing in each district, the number of customers in each store, and distribution of customers in each district. Experts and new retailers can use the results to design various location and sales strategies. Using this model, new retailers in confectionary market can accurately predict their sales before even opening the store and thus protect themselves against possible financial losses. Moreover, this model predicts total sales of different stores and help retailers compare their market shares with those of their competitors. They also can enter features of a new store into the model and find several potential sales strategies. In other words, the model helps determine sales of existing and new shops. In this way, retailers can find an optimum location for their new confectioneries based on the principles of geomarketing.
Fariba Moghani Rahimi; Ahmad Mazidi; Hamid Reza Ghafarian Malamiri
Abstract
Abstract ExtendedIntroductionStudying land cover changes has a very long history which coincides with the beginning of human life. Following the formation of societies, primitive humans began to change the cover of wasteland to form suitable lands for agriculture and animal husbandry. More than half ...
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Abstract ExtendedIntroductionStudying land cover changes has a very long history which coincides with the beginning of human life. Following the formation of societies, primitive humans began to change the cover of wasteland to form suitable lands for agriculture and animal husbandry. More than half of the world's population recently lives in cities, urbanization and urbanism is rapidly increasing, and this trend will continue to reach its peak. Due to their extensive coverage, reproducibility, easy-access, high accuracy and reduction in necessary time and expenses, remote sensing data are generally considered a preferred method used to study land cover, vegetation, and their changes. Many researchers have shown an interest in land cover change in different cities of the world. The history of land cover studies dates back to the early nineteenth century and the studies performed by von Thünen (1826). Von Thünen have determined the economic benefits of different land covers based on their distance from the central city and found an optimal distribution for production and land cover in the form of a series of concentric circles. Land cover changes due to human activities are considered to be an important topic in regional and development planning. Since land cover changes and urban development in the study area have not been previously studied, Landsat time series satellite imagery and a combination of Landsat 7 and 8 panchromatic and multispectral bands were used to identify and detect changes in land cover and urban development in the urban areas of Abarkooh from 2000 to 2020. Materials & MethodsSatellite remote sensing data are used in the present study (Landsat 7 and 8 multi-temporal satellite images collected in 2000, 2010 and 2020). 3 images were retrieved from US Geological Survey website and used in the present study. Raw remote sensing images always contain errors in geometry and the measured pixel values. The former category is called geometric errors and the latter is called radiometric errors. Atmospheric corrections were performed for all images used, and stripping in the imagery collected in 2010 image was also corrected. For image enhancement and extraction of more information from the images, false color composites were used (5-4-3 infrared, red and green bands) for Landsat 8 and Landsat 7 (3-4-3 near infrared, red and green bands) images. Using this technique, vegetation is shown in red. Compared to other methods, Gram-Schmidt based pan sharpening method produced higher spatial resolution images of the study area and thus was used to combine the selected images. Maximum likelihood method is considered to have the highest efficiency among various supervised classification methods. Results & DiscussionThis method assumes the presence of a normal distribution for all training areas. The accuracy of this classification has to be calculated following the classification. To do so, the kappa coefficient and overall accuracy of each class were calculated in ENVI5.3. The results are shown in the error matrix. Overall accuracy is the average of classification accuracy. The kappa coefficient calculates the accuracy of classification as compared to a completely random classification. Based on the available data, spatial resolution of the images and the information researcher has access to, 5 classes of training data (urban constructed space, roads, barren lands, arable lands, and gardens) have been selected for each image. Results obtained from the maximum likelihood classification method in ENVI5.3 environment were changed into the vector format and then used as a shape file in GIS environment. After compiling the land database, land cover maps and its changes were extracted in three periods and the area of each land cover class was determined. Each of the land cover maps, 5 classes with different colors are determined and shown. To ensure the accuracy of the classification, the accuracy of the classification has been evaluated. ConclusionThe resulting kappa coefficient for 2000 and 2020 equaled 86% and overall accuracy equaled 89%, while for 2010 kappa coefficient equaled 90% and overall accuracy equaled 92%. Thus, the error rate is small and acceptable. Finally, post-classification comparison method was used to investigate the nature of changes. 13 square kilometers of land cover were investigated in the present study. To identify the exact type of land cover changes, categorized images collected in these years were compared. Total area of residential land use showed an increasing trend: a total 4.25 square kilometers in 2000 (32.69 percent of the total area under study) has reached 5.58 square kilometers (42.92 percent) in 2020. Overall area of arable land use did not change much in the period of 2000 to 2010. However, a declining trend was observed in 2020 changing a part of this land use into residential and barren lands. Results of satellite image processing and classification indicate that supervised classification and maximum probability algorithm were close to ground realities and had an acceptable accuracy. In general, results indicate that significant amounts of vegetation and agricultural lands have been converted into urban areas and thus, planning for urban growth in these areas should be in favor of preserving gardens and agricultural lands.
Valiollah Karimi; Eassa Kia; Mohammad Ali Maleki
Abstract
Extended AbstractIntroductionIndustrialization of communities and increased greenhouse gasses in the previous decades have resulted in increased global temperature and changes in climate parameters which are generally called climate change in scientific texts. Climate change has resulted in changes of ...
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Extended AbstractIntroductionIndustrialization of communities and increased greenhouse gasses in the previous decades have resulted in increased global temperature and changes in climate parameters which are generally called climate change in scientific texts. Climate change has resulted in changes of temporal and local precipitation patterns all around the world. Consequently, hydrological cycle has changed affecting intensity, duration and frequency of rainfall events. Intensity- duration- frequency curves are used to provide an economic and safe design for drainage facilities, check dams, urban water management structures such as culverts, surface water and sewage systems. They are also used in landslides studies. The present study seeks to compare rainfall intensities in Babolsar Synoptic Station before and after 1993 to understand the effect of climate changes on rainfall intensities during the mentioned 52-year statistical period. Materials&MethodsThe first synoptic station of Mazandaran province was set up in Babolsar city in 1952. With an elevation of -21 m from sea level and 7 m from the Caspian Sea level, it is located at the east longitude of 52o, 39̍, 30̎ and the north latitude of 36o, 43. The station has a mean annual rainfall of 928 mm and an average of 99 rainy days.To understand the effect of climate changes on rainfall intensities in different durations and return periods in Babolsar Synoptic Station, statistical period was divided into two 26-year subperiods (before: from 1968 to 1993 and after: from 1994 to 2019). Rainfall intensities were calculated separately for each of the 14 duration series (10, 20, 30, 40, 50, 60, 90 minutes and 2, 4, 6, 9, 12, 18 and 24 hours) with return periods of 2, 5, 10, 25, 50 and 100 years and compared together. Then, a paired t-test was conducted to prove the difference between two series of rainfall intensity to be significant. Moreover, 5 annual air temperature parameters including minimum absolute temperature, maximum absolute temperature, average minimum temperature, average maximum temperature and average temperature were investigated in both subperiods and analyzed using a paired t-test in SPSS software. Results were used to investigate temperature and precipitation changes during the statistical period and prove the difference between before and after time series data to be significant. Mann-Kendall test was also carried out on 5 air temperature parameters collected during the 52-year time series data to find ascending or descending trends. Results&DiscussionCompared to the first subperiod, the average rainfall intensities have increased in 10, 20, 30 minute and 12, 18 and 24-hour durations of the second statistical subperiod, while the opposite has occurred in 40, 50, 60, 90-minute, and 2, 4, 6 and 9-hour durations. However, statistical analysis has proved increased rainfall intensities in 10 and 20-minute, and 18 and 24-hour durations and decreased rainfall intensities in 50, 60, 90-minute, and 2, 4, 6 and 9-hour durations of the second statistical period to be significant. A paired t-test was conducted to compare rainfall intensity in the statistical subperiods and find out its effects on climate change. Results indicated that except for data collected in 30 and 40-minute and 12-hour durations, the difference between other paired series was significant at a less than 5% level.Moreover, except for maximum absolute air temperature, other air temperature parameters showed a significant difference at less than 0.5% level. Furthermore, all 5 parameters showed an increase in the second study period indicating a warmer climate in Babolsar.However, paired t-test results indicated that despite the reduction of mean annual rainfall in the second statistical period, difference between the two series was not significant at any acceptable level of significance. Moreover, results of the Mann-Kendall test indicated that average air temperature, average maximum air temperature, average minimum air temperature and minimum absolute air temperature have shown an ascending trend at a 1% significant level, while maximum absolute temperature lacked a specific trend and showed leap changes. Annual rainfall also showed random changes and lacked a specific trend during the 52 year statistical period. ConclusionResults of the Man-Kendall and paired t-test have shown that a significant increase have occurred in air temperature during the 52-year statistical period (1968-2019) resulting in climate changes.It can be concluded that climate change has increased the intensity of short-term (shorter than 40 minutes) and long-term (longer than 12 hours) precipitations and reduced the intensity of medium-term precipitations in Babolsar Synoptic Station. Moreover, climate change has increased the intensity of precipitations with short and long return periods while reducing the intensity of precipitations with medium-term return periods in the aforementioned Synoptic Station.
Mina Arast; Abolfazl Ranjbar; Khodayar Abdolahi; Sayed Hojjat Mousavi
Abstract
Introduction Evapotranspiration is one of the most important parts of the water cycle (Boegh and Soegaard 2004). Precise prediction of actual evapotranspiration () is essential for various fields, such as agriculture, water resource management, irrigation planning and plant growth modeling. Therefore, ...
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Introduction Evapotranspiration is one of the most important parts of the water cycle (Boegh and Soegaard 2004). Precise prediction of actual evapotranspiration () is essential for various fields, such as agriculture, water resource management, irrigation planning and plant growth modeling. Therefore, accurate determination of actual evapotranspiration has always been a major concern of experts in these fields. Due to the limited number of weather stations and the fact that collecting ground information is both time consuming and expensive, remote sensing and satellite imagerycan be a suitable tool in determination of actual evapotranspiration (Brisco et al., 2014). Satellite productions are usually divided into images with low, medium and high spatial resolution (Rao et al., 2017). Surface energy balance is a method usually used in combination withremotely sensed spatial data for estimation. Information collected from various sources, such as remotely sensedimageries and meteorological data, are used in this method. The present studyinvestigatesspatial distribution on different scales (from field- to regional-) using remotely sensed imagerieswithdifferent spatial and temporal resolution. TheSurface Energy Balance System (SEBS) is one of the most important methods used for the estimation of in remotely sensed images (Ochege et al., 2019). This model needs thermal maps produced using satellite images. Daily maps produced with RS are usually very large, and their pixelsize is usually so large that it can provide the spatial diversity found in the basins with respect to the errors (Mahour et al., 2017). Material and Methods In order to estimate the actual evapotranspirationin satellite images collected from Zayanderud basin,the effects of Co-Kriging downscaling of surface temperature (LST) were investigated in June 2017 using two different methods.To reach this aim, we first applied a co-kriging downscaling method to a low-power LST product collected from MODIS at 1000 meters. Then based on the results and using the SEBS system, the daily was obtained from images with average spatial resolution (250 m).In the second method, map produced usinghigh resoultion satellite imageswas downscaled to medium resolution (250 m). For both methods, 250 m resolutionMODIS NDVI products were used as co-variables.Then, validation was performed using Landsat-8 imagery, and land surface temperature was extracted from its thermal bands. SEBS algorithm was used to determine in Landsat 8 30-meter resolutionimagery. Accuracy of measurements wasexamined based on a comparison between down scaledLST and maps (250 meterresolution). Results and Discussion In the present study, mean LST equals 3/312 K (SD = 1.74) and average daily equals 12.5 mm / day (SD = 0.86). In the downscaling phase, the relationship between LST parameters and and vegetation index(as a co-variable)was investigated.Moreover, to investigate the relation betweenhigh resolution variables and NDVI, we re-sampled LST and variables from a 1000 mresolution to 250 mresolution.In250 mresolution, there is a negative linear relation (r=-0.85) between LST and NDVI, but the relation betweenand NDVI is positive (r = 0.80). Thus, lower LST (> 305k) indicates more vegetation (NDVI >0.3) inthe region, while higher LST results in lower NDVI or lack of vegetation. As a result, more vegetation can be observed in regions with higher(12 mm/day). Results indicated that the difference between average downscaled-SEBS (12.56 mm/day) and reference (13.11 mm/day) is negligible. The RMSE between the reference and the downscaled equaled 1.66 mm/day (r = 0.73), and RMSE between the reference LST and the downscaled LST equaled4.36 K (r = 0.78). Thus,values obtained from two downscaling methods were similar, but the obtained from downscaled LST showed a higher spatial variation. Therefore, LST has greatly influenced the production of maps using remotely sensing images, and Co-Kriging downscaling has been useful for providing daily maps with intermediate spatial resolution. Conclusion Evapotranspiration downscaling using the co-kriging method is not significantly different from the SEBS product and the results are similar. The results of -SEBS method isalso acceptable, but the derived from the SEBS algorithm is more variable due to the LST downscaling.
Ebrahim Sharifzadeh Aghdam; Mohammad Ajza Shokouhi
Abstract
Extended Abstract
Introduction
It can be argued that among the socially and culturally relevant variables affecting sustainable security and optimal control of border cities, political variables (formulation of the comprehensive plan and other urban plans), physical variables (distance between border ...
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Extended Abstract
Introduction
It can be argued that among the socially and culturally relevant variables affecting sustainable security and optimal control of border cities, political variables (formulation of the comprehensive plan and other urban plans), physical variables (distance between border cities and central or peripheral areas) and legalvariables (adaptingeconomic policies in accordance with themacroeconomic policies of the country by2025) are the basis for developingmatrix of key properties and scenario planning.In this regard, the importance and necessity of the present study lies in the fact that the future border cities research is a process of systematic and calculated effort and a long-term scientific approach toward good urban governance. It seeks to reach a sufficient understanding of strategic research areas, benefit economy of the country and especially border communities through wise management of space and the introduction of related technologiesand offer desirable scenarios for the development of border cities based on the patterns of democratic and ecosystem management.Accordingly, the present study demonstrates a kind of creativity and innovation in the field of strategic planning based on every aspects of sustainable urban development while emphasizing on the prospective and environmental aspects that are an inseparable part of geography and urban planning studies.
Materials & Methods
The present study seeks to answer the main research question which is, what are the key indicators and factors influencing the development analysis of Piranshahr border town?
In this regard, the present study takes advantage of descriptive-analyticaland documentary investigations of strategic planningalong withrelated questionnaires in the framework of Delphi model and software analysis. Based on a consultation with scholars familiar with the status and conditions of the region within the dialectical framework of urban issues, a statistical population of 50, and 23 variables were identified for the present research. The selected variables were classified in 8 general categorizations as the primary variables of the research.Getting output from the Wizards software based on the scores entered into the matrix, the normalized and the standardized matrices were calculated, and the possible scenarios were categorized based on an analysis of the descriptor compatibility. Then, the goals set for strategic planning of Piranshahr, effective factors in strategy development, a competitive map, level of competitiveness in Tamarchinborderand finally challenges and opportunities of each domain were expressed in the framework of the Meta SWOT Strategic Model.
Results & Discussion
Based on experts’ opinions and software output, it can be argued that among the socially and culturally relevant variables affecting sustainable security and optimal control of border cities, political variables (formulation of comprehensive plans and other urban plans), physical variables (distance between border cities and central or peripheral areas) and legalvariables (adaptingeconomic policies in accordance with themacroeconomic policies of the country by2025) are the basis for developingmatrix of key properties and scenario planning.
Finally, the status of key driving forces in cross-border strategic planning of Tamarchinborderand its effects on the development of Piranshahr city over the coming 15 years are explained in the form of three desirable, intermediate and disaster scenarios. Also based on the obtained results, Sairanband border in Bane had the highest score in enhancing the quality of life in border cities and adopting economic policies in accordance with the country’s macroeconomic policies by2025. Thus, Sairanbandis the most important rival of Tamarchin border.
Conclusion
The present study has proposeda desirable model for the development of Piranshahrborder town using a strategic approach toward the sustainability issue in border cities and taking advantage of indexes such as “cultural, human, political, economic, and physical development” indexes. It alsoapplies the pattern of futures studies used in wizard and strategic scenarios. Thus, factors affecting the level of urban development in Piranshahrwere classified based on 5general classes, sub-variables and a 23×23 matrix. So only by putting the indices in the distribution chart, a very favorable situation of the distribution of boundary related variables can be presented. In the context of the above mentioned results and according to the scenario formulation table, it can be concluded that the results of the present study are to a large extent applicable. Moreover, they can be applied for scenario-building and guide management toward the development of border towns within the framework of structural planning.
Mahdi Sedaghat; Hamid Nazaripour
Abstract
Extended Abstract Introduction Soil moisture is considered to be a key parameter in meteorology, hydrology, and agriculture, and the estimation of its temporal-spatial distribution contributes to understanding the relations between precipitation, evaporation, water cycle, and etc. Soil moisture reduction ...
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Extended Abstract Introduction Soil moisture is considered to be a key parameter in meteorology, hydrology, and agriculture, and the estimation of its temporal-spatial distribution contributes to understanding the relations between precipitation, evaporation, water cycle, and etc. Soil moisture reduction results in the creation of centers susceptible to dust storms. With socio-economic impacts ranging from urban to intercontinental and from a few minutes to several decades, this can challenge regional development. The first estimate of potential dust sources is derived from the soil properties. With the reduction of surface soil moisture and the wind speedcrossing a certain threshold level, wind erosion process can cause the formation of dust storms. Field studies have proved that increasing the moisture content in soil from zero to about 3%, reduces the dust concentrationsignificantly. To understand the climatology of dust and develop related numerical predictive methods, continuous recording of dust storms is essential, which requires effective and continuous monitoring of the variations in surface soil moisture. Remote sensing technology is an effective method for calculating soil moisture. This technology was first used for the estimation of energy flux and surface soil moisture in the 1970s. To extract the surface soil moisture content, some remote sensing methods use surface radiation temperature and some others apply water transfer (soil/vegetation/air) (SVAT) model. Various indices have been developed for soil moisture monitoring, such as soil moisture (SM), soil water index (SWI), Temperature-Vegetation-Dryness Index (TVDI), Soil Moisture Index (SMI) and Perpendicular Soil Moisture Index (PSMI), all of which combine vegetation and surface temperature variables. Materials and Methods Soil moisture is considered to be a significant parameter in the exchange of mass and energy between the Earth surface and the atmosphere. Lack of soil moisture or decreased moisture in soil is considered to be a factoraccelerating the process of dust storm formation. During the previous decades, water stresses on the ecosystem of Hour-al-Azim have transformed this wetland into one of the main dust centers in the southwest Iran. Hour-al-Azim is one of the largest wetlands in southwestern Iran. This wetland is shared between in Iran and Iraq. It is located between N 30° 58´- N31° 50´ and E 47° 20´- 47° 55´. The Iranian part of this wetland encompassed an area of 64,100 ha in the 1970s, while in the 2000s, the area has decreased to only 29,000 ha. The present study aims to monitor the spatial-temporal variability of soil moisture in Hour-al-Azim wetland and to investigate the relation between these changes and dust storms in the southwest Iran. To reach this end, we used 8-day images obtained from the Aqua satellite in the period of 2003 to 2017 and also annual frequency of dust storms with a visibility of less than 1000 m in the period of1987–2017. A database consisting of 189 images of the red band, near-infrared band, and ground surface temperature (LST) was created, which contained 4 images per year (one image per season). The resolution of the red / near-infrared band data and daily LST values were 231.65 and 926.62 meters, respectively. Then, soil adjusted vegetation indices (SAVI) and perpendicular soil moisture index (PSMI) were extracted. SAVI index is used to reduce the effect of background soil on vegetation cover in semi-arid and arid environments with less than 30% vegetation cover.Compared to NDVI, SAVIwith L = 0.5reduces the effect of soil changes on green plants. In the next step, a trapezoidal method was used to calculate the PSMI index. In order to investigate changes in the soil moisture content of the Hour-al-Azim wetland, three time series obtained from regional mean of SAVI, LST and PSMI remote sensing indices and a time series consisting of the number of days with dust storms observed in the 9 stations were evaluated using simple linear regression test. Results and discussion Extracting Soil Adjusted Vegetation Index indicated that in the study period, the highest values of this index was observed with a regional mean of 0.15 on 4/7/2014 and the lowest values was observed with a regional mean of 0.08 on 1/1/2005. Land Surface Temperature survey showed that during the study period, the highest values of this index was observed with a regional mean of 54.42 ° C on 7/4/2010 and the lowest values was observed with a regional mean of 17.28 ° C on 1/1/2007. The regional mean of Perpendicular Soil Moisture Index indicates that despite winter is considered to bethe wettest season of the region, PSMI index with a regional mean of 0.2 has experienced the driest soil moisture conditionsat the beginning of winter (1/1/2016),while it had experienced the wettest soil moisture conditionsin the same season on 1/1/2009 with a regionalaverage of 0.13. Conclusion Finding of the present study indicate an increasing trend in the range of remote sensing indicators. The range of SAVI index is increasing, which means that the density of vegetation in the Wetland is decreasing. Perpendicular Soil Moisture Index values also show an increasing trend, indicating a decrease in soil moisture content. As a result of the decrease in soil moisture, the vegetation density also has decreased and the land surface temperature has increased. Results of statistical tests indicate the role of changes in environmental conditions of Hour-al-Azim wetland in the frequency of dust storms. Using findings of the present study, or studies such as Kim et al. (2017), it is possible to take advantage of soil moisture variations for the prediction of dust generation, its emission, and spread level.
Ahmad Rashidinejad; Morad Kaviani Rad; Afshin Mottaghi
Abstract
Introduction According to the United Nations, two out of every three people in the world will face “water stress” by 2025. This estimate is based on the premise that the world’s annual population growth (80 million) requires 64 billion cubic meters of more water. Presently, 700 million ...
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Introduction According to the United Nations, two out of every three people in the world will face “water stress” by 2025. This estimate is based on the premise that the world’s annual population growth (80 million) requires 64 billion cubic meters of more water. Presently, 700 million people in 43 countries of the world are not far from the water stress threshold (1,700 cubic meters per year). As an important economic resource, transboundary water resources are considered to be an influential factor in territorial disputes. Uneven distribution of rainfall and the distance between water resources and catchments and human settlements have also increased concerns in this regard. Territorial disputes over water resources have a long history, and the first war in which water resources have played a significant role is estimated to have occurred 4,500 years ago. Nowadays, 263 transboundary river basins play a vital role in the relations among 151 riparian states. Transboundary water conflicts often occur due to overexploitation of water in the upstream and a decrease in the amount of water flowing to the downstream countries and sometimes a decrease in the water quality due to water pollution in the upstream. Conflicts over the quality of water resources can usually be resolved through the cooperation of the riparian states. Nonetheless, water scarcity and conflicts over the volume of water in these resources are difficult to resolve and many of them are considered to be a threat to the riparian states. This may be in part due to the problems in international laws. Currently the international law lacks decisiveness in the issue of water distribution and one-third of the world’s rivers are subject to local and regional agreements. However, asymmetry of power between riparian states is often the main problem hindering the process of resolving disputes through mutual cooperation. It is often assumed that if the upstream country is stronger than the downstream countries, reaching an agreement will be more difficult. In such a situation, the upstream country sees water as a tool to achieve its goals. However, the avarice of countries like Israel in the downstream of the Jordan River or Egypt in the downstream of the Nile River shows that what is hindering an agreement is not only an “upstream” position, but also a “hydro-hegemonic” position. In other words, a country may be geographically located in the upstream of a river, but this does not necessarily result in its hegemonic dominance over downstream countries since it may be geopolitically weaker or international agreements may not grant dominance to this country. In other words, hydro-hegemonic structure of a region only form when a country can exercise its leadership not only through “compulsion” but also through other material and immaterial sources of political power. According to “Zeytoon” and “Warner”, hydro-hegemony is superiority along a river basin created through the strategy of controlling water resources. This strategy is executed through threatening and pressurizing, signing agreements, and building infrastructure, which due to the weakness of international institutions enable the stronger country to have a larger share in water resources. This implies that infrastructure facilities such as dams not only have physical and economic benefits, but also are considered to be hydro political tools with the potential of changing the structure of hydro-hegemony and hydro-political relations. Method The present study uses the above mentioned definition of hydro-hegemony to examine “construction of infrastructure facilities” in Ethiopia (Renaissance Dam), and scrutinize the role of this hydro-political tool in changing the hydro-hegemonic structure of the region. To reach this aim, a descriptive-analytical methodology is used and data collection is performed using library research method. Results Findings indicate that with the increase of material power (economic and military power), anti-hegemonic mechanisms applied by Ethiopia in the Nile catchment have also increased. Along with the stability and political-economic development of Ethiopia over the past decade, the Egyptian revolution in January 2011 and subsequent internal instability have served as an opportunity for the implementation of the Ethiopian hydropower projects. It should be noted that having the highest military capacity, economic dominance, and political power in comparison with other low-income countries such as Ethiopia, Sudan, Rwanda, and Tanzania, Egypt has been able to supply its needs from the Nile and deny upstream countries of their rights to build projects which may affect its share of this river for decades. This situation can be described as Egyptian hydro-hegemony. Actually, Ethiopia was unable to take advantage of its geographical position in the upstream of the Nile River and the Horn of Africa due to ongoing conflicts, poverty, and distrust. However, recent changes in foreign policy, increased attention to domestic issues and economic growth have made it possible for this country to solve its domestic issues and use its geographical position. Conclusion Findings of the present study indicates that Grid Construction Project can be considered as the beginning of the end of Egyptian hydro-hegemony and power asymmetry in the Nile basin. Some scholars even consider this project as a step towards more equitable shares of the Nile Basin and regional integration. Inspired by a hydro-hegemonic framework in which asymmetric power relations along transboundary rivers are closely examines, these scholars see the Renaissance Dam as a successful case of anti-hegemony resulting in the development of a fair regime in the Nile Basin.
Leyla Karami; Seyed Mohammad Tavakkoli Sabour; Ali Asghar Torahi
Abstract
Extended Abstract
Introduction
Vegetation is considered to be one of the most important elements in all major ecosystems on the Earth. Thus, a proper understanding of vegetation and its growth trends and other environmental factors has always been of particular importance for environmental research. ...
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Extended Abstract
Introduction
Vegetation is considered to be one of the most important elements in all major ecosystems on the Earth. Thus, a proper understanding of vegetation and its growth trends and other environmental factors has always been of particular importance for environmental research. Estimating vegetation phenology parameters (VPPs) requires continuous NDVI data collection over a specific period of time. However, soil moisture, cloud cover, and particulate matter may affect the energy reflected from the vegetation cover and result in noisy images or erroneous data. Vegetation phenology parameters cannot be extracted from raw data due to the presence of random errors. These errors do not follow the phenological process and thus, overestimate or underestimate NDVI and fail to produce accurate results. Smoothing functions and especially the TIMESAT model are used to resolve this issue and eliminate errors in the NDVI time series. There is still no general consensus on which function acts more efficient and accurate in the TIMESAT model especially regarding the highlands. Naturally, each method yields different results in different regions, and thus it is necessary to compare and evaluate different functions used in the TIMESAT model and determine their accuracy in producing a continuous time series. The present study aimed to evaluate the performance of various functions such as asymmetric Gaussian (AG), double-logistic (DL), and Savitzky–Golay (SG) used to extract VPPs especially in mountainous regions.
Materials and Methods
TIMESAT model is a time-series analysis model based on remote sensing (RS) vegetation indices. It includes three functions: Savitzky–Golay, asymmetric Gaussian, and double-logistic, which are used to smooth collected data and identify outliers. Savitzky–Golay is an adaptive-degree polynomial filter (ADPF). The other two functions fit the information using nonlinear functions. These functions use unmodified NDVI data as input to produce modified and smoothed NDVI output. Four wheat farms in cold and warm regions of Khorramabad were used in the present study to investigate plant phenological behaviors and extract VPPs. The northern and eastern parts of Khorramabad have a cold climate, while the southern and western parts have a warm climate. One-year time series (2020) data of MODIS sensor was used in the present study. Using the infrared and near-infrared spectral reflectance values, NDVI was calculated in the Google Earth Engine environment. Errors of the NDVI time series were first corrected and a phenology curve was produced for wheat in both warm and cold farms. Asymmetric Gaussian, double-logistic, and Savitzky–Golay filter functions were also used to adapt the NDVI data. Following the reconstruction of growth curves in the time series of vegetation indices and smoothing the curve, various VPPs such as start of the season (SOS), end of the season (EOS), middle of the season (MOS), length of the growing season (LOS), base limit and value, maximum NDVI, vegetation growth season range, large seasonal integral, and small seasonal integral were extracted.
Results and Discussion
The model indicated that on average, beginning of the wheat growing season (SOS) in the warm regions of Khoramabad coincided with the 31.5th day of the year in the Gregorian calendar, whereas it happened on the 90th day of the year in the cold regions, thus indicating a 1.5-2 month difference between the beginning of the wheat growing season in cold and warm regions. The wheat growing season ended (EOS) on the 163rd day of year in the warm regions and on the 193rd day in the cold regions. In addition, in order to analyze the effect of climate on VPPs such as SOS and EOS, a comparison was made between the parameters obtained from farms in warm and cold regions. On average, the peak of vegetation growth has occurred in late March (Mar. 28, 2020) in farms of warm regions while cold regions experienced the peak of growth on May 20, 2020. In other words, warm regions have experienced peak growth approximately two months earlier than cold regions. Finally, the models were assessed and obtained values were compared with ground-based data collected in field surveys. Validation results showed that with an average RMSE of 2, Savitzky–Golay smoothing model reconstruct data more accurately as compared to asymmetric Gaussian, and double logistic function with an RMSE of 4 and 11, respectively. In other words, Savitzky–Golay estimates SOS and EOS with a higher accuracy and lower errors.
Conclusion
Findings indicate that Savitzky–Golay filter outperformed asymmetric Gaussian and double logistic functions in extracting VPPs in mountainous areas. Accordingly, it is suggested to use Savitzky–Golay in future studies aiming to investigate the phenological behavior of different vegetation covers in other Iranian highlands. The study has also showed that different climatic conditions within the study area affect plant phenological behaviors, which can lead to differences in SOS, peak of growing season, and EOS in different cold and warm regions of the province. Growing season of plants in cold regions of the province has occurred with an approximately two-month delay compared to the warm regions of the province.
Nemat Hosseinzadeh; Ali Reza Estelaji; Tahmineh Daniali
Abstract
Extended Abstract Introduction The growth and expansion of urbanization in the contemporary era and the emergence of metropolitan areas as places in which large number of people live together and capital and assets are accumulated have recently attracted the attention of many planners, governments and ...
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Extended Abstract Introduction The growth and expansion of urbanization in the contemporary era and the emergence of metropolitan areas as places in which large number of people live together and capital and assets are accumulated have recently attracted the attention of many planners, governments and nations topotential natural hazards and the importance of crisis management in these areas.In this regard, land use planning is considered to be critical due to its importance for sustainable development, optimal configuration, and crisis management. Materials & Methods The present study primarily seeks to design a spatial model for spatial evaluation of urban land use in district 19 of Tehran Municipalityusing a crisis management approach. In this descriptive-analytical study,necessary information were collected through library research methods and the analysis of quantitative and qualitative indicators.In quantitative index analysis, per capita land use of the district was compared to the country’s standard level, and in qualitative index analysis, three criteria of compatibility, capacity and desirability have been evaluated. One of the goals of urban land use planning is proper site selection for different land uses and separation of incompatible land uses from each other which is achieved through collection of necessary information about the current situation and evaluation of the collected information. For example, attempts are made to find a proper site forland uses producing pollutants such as smoke, odors, and noise away from residential, cultural, and social areas.In contrast, activities that complement each other are located in vicinity of each other. ArcGIS was used to evaluate and model the compatibility level of neighboring land uses. The proposed model inthe present study aims to evaluate the proximity of activities in order to determine their level of compatibility from the perspective of crisis management. Results of this model can be used for land use planning. This model is based on two principles: the logic behindland uses’ compatibility, and spatial neighborhood relationship and models of this relationship in GIS environment. Model Builder, a visual programming language at the Arc Info \ Editor Level which is undoubtedly one of the most important features offered in this program has been used to achieve the desired goal in this study. This modeler is actually an interface which forms the input-output parameters and processing functions in the processor. In this interface, the user can call several functions in a sequence and the processes will be performed one after the other. The input parameters includeeverysupported format in ArcGIS. Processing functions include all functionsused in the spatial analysis network. Outputs can be stored and used in later steps. Results & Discussion Qualitative analysis of land uses in District 19 of Tehran Municipality Evaluating the compatibility of land uses in District 19 In order to analyze the compatibility levelofneighboring land uses, the number of neighbors in each parcel is determined.Then,a binary compatibility relationship is stipulated for each pair and finally a fixed number is reached in the process of comparing land uses. As required by the land use compatibility matrix, urban uses are hypothetically classified into 5 groupsbased on their current situation: fully compatible, relatively compatible, indifferent, completely incompatible, and relatively incompatible. Following the production of compatibility matrix, details oflandusescollected during the field study have been analyzed and presented as maps. Then, the model is run in Arc GIS and the level of each land use’s compatibility is presented with anespecialcolor. Results indicate that except for Velayat park which is not compatible with the surrounding land uses, most of the incompatible land uses are located in the western and southwestern parts of the district. These incompatible land uses are presented with 5 different color ranges. Investigating the capacity of different land uses in district 19 of Tehran Municipality Qualitative analysis of accessibility zone in the capacity matrix In this matrix, the performance of each major land use in service provision and performance coverage is determined based on the urban population and its area of influence, and the results are presented in the relevant tables and on a map produced using Euclidean analysis in Arc GIS. The basic level of performance for each land use at the regional level and its area of direct influenceis identified based on the population required for standard performance of that specific land use in this area. This identified level of performance was used as the basis for further calculations. According to the proposed model and considering the accessibility zone, a special buffer zone is identified for each land use and its census blocks are determined. Finally,population within the blocks is determined separately for each land use (in this section, a few maps of buffer zones are provided for some land usesas an example). This model determines whether the rules of accessibility have been complied in different land uses. Based on the accessibility zone and censusblocks, decision making about the necessity of different land uses is made possible. Investigating the desirability of land uses in district 19 To reach the desired goal, a land use layerto which a new field of desirability has been added will be consideredaccording to the model (Figures 5 and 7) and the existing rules for specific land uses. Results are exhibited in two different classes (desirable, undesirable). According to the existing rules and maps, the desired parts of the area are marked in green and the undesirable parts of the area are marked in red. Conclusion As one of the most important tools and a major goal of urban planning,land use planning has a vital role in risk mitigation duringurban development. Thus, improving methods and processes of realizing this goal is of great importance and priority. Physical and functional characteristicsof land use have a significant effect on the number of casualties in different urban crisis. Therefore, land use planning is considered to be an important principle of urban planning and an urban planner is primarily expected to make the right decisions and to properly monitor land uses.On the other hand, crisis management and resilience approach have become a pervasive topic of debate in the present decade. Many researchers consider resilience to be the internal ability of a system, community or element to withstand the effects of a natural or social event. In order to determine the level of resilience, land uses in this area are investigated based on different aspects of crisis management. A major difference is observed between the findings of the present study and that of other researchers: most of dimensions, criteria or the main indicator in the present study are related to each other.The dimensions proposed in this model cover all physical and non-physical aspects and the proposed criteria or indicators also show important factors in each dimension. Moreover, the vulnerability of each dimension affects other dimensionsdirectly or indirectly. In fact, a district of Tehran municipality may be more resilient than other districts in some dimensions, but this does not suffice by its own and vulnerability in one dimension reduces the resilience of the whole district.Therefore, a resilient city or district needs to reduce its vulnerability in all dimensions and achieve resilience and crisis management in their real sense. One of the main concerns in the study of urban issues and urban planning is the issue of quantitative and qualitative analysis of the city and urban land uses. In the present study, an attempt has been made to perform quantitative index analysis of urban land uses under the topic of fair distribution of land uses per capita.And for the analysis of quality index, urban land uses were separately investigated based on their compatibility, capacity, and desirability level.This is another innovation of the present study which makes it different from other researches.In the discussion of compatibility,a model has been developed in ArcGIS environmentbased on the rules of urban planning to determine the compatibility of neighboring land uses. The highest level of incompatibility between neighboring land uses was observed in the western and southwestern part of the district. In terms of capacity, a model has been designed for existing uses in the area based on the standard accessibility zone. Regarding desirability, appropriateness of spatial conditions (slope, pollution, odor, location ...) and the land uses in a particular place have been considered as important criterion used to distinguish desirable and undesirable areas.The present studyinvestigates appropriateness of land uses based on standard slope. As previously mentioned, a model has been developed for each case in the GIS environment and the results are provided as a map at the end of each section. Following qualitative analysis, the most incompatible land uses were identified. Finally, the following solutions and suggestions are provided to improve and manage land use and for the managementof possible future crisis: Using empty spaces in the district and worthless lands in the southern and southwestern areas of the district to prevent the physical expansion and encroachment of the district on Tehran and Islamshahr. Considering a special zone around high-risk land uses such as gas stations and applying additional rules and regulations to prohibit increased density in these zones. Collecting physical and environmental data as much as possible, combining these data with each other, and using them statistically. Assessing earthquake risk and including the results in land use planning to mitigate risk and manage possiblecrisis. Distributingthe population in this districtbased on identified hazards in the area. Properly distributing parks and green spaces in the district, maintaining them for the times of possible crisis, ensuring easier access and equitable distribution among citizens. Increasing the quality of buildings in accordance with construction and urban planning standards, planning for the reconstruction and repairing of worn out buildings.
Aerial photography
Zahra Azizi; Mojdeh Miraki
Abstract
Extended Abstract
Introduction
Advances in computer vision and the development of remote sensing instruments have made indirect measurement of tree features possible. Individual tree crown delineation is an important step towards information collection and mapping trees in an urban area. This information ...
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Extended Abstract
Introduction
Advances in computer vision and the development of remote sensing instruments have made indirect measurement of tree features possible. Individual tree crown delineation is an important step towards information collection and mapping trees in an urban area. This information is then used to help planners design strategies for optimization of urban ecosystem services and adapt to climate changes. Common methods of Individual tree crown delineation (ITCD) were based on very high-resolution satellite or Light Detection and Ranging (LiDAR) data. However, satellite data are usually covered by clouds and thus, cannot be appropriate for the measurement of individual trees. Aerial Laser scanning is also relatively expensive. Remote sensing with unmanned aerial vehicle (UAV) captures low altitude imagery and thus, is potentially capable of mapping complex urban vegetation. Automatic delineation of trees with UAV data makes collection of detailed information from trees in large geographic and urban regions possible. Therefore, a multirotor UAV equipped with a high-resolution RGB camera was used in the present study to obtain aerial images and delineate individual trees.
Materials & Methods
The present study has compared the performance of Inverse watershed segmentation (IWS) and region growing (RG) algorithms using point clouds derived from Structure from Motion (SfM) algorithm and UAV imagery captured with the aim of tree delineation in Fateh urban forest located in Karaj. Region growing (RG) is used to separate regions and distinguish objects in an image. It starts at the initial seed points and determines whether the neighboring pixels should be added to the growing region. If the neighboring pixels are sufficiently similar to the seed pixel, they are labeled as belonging to the seed pixel. To implement the algorithm, the window size and the growing threshold were set for all resolutions. In order to obtain the most appropriate size for the search window, we examined different window sizes with a growing threshold of 0.5 for each resolution. Individual trees delineation was performed for each CHM resolution in the three different sites using "itcSegment" package of R software. Watershed segmentation algorithm is also similar to RG algorithm. The only difference is that it sets the growing seeds at the local minima. In other words, the local maxima in this algorithm change into local minima and vice versa. Inverse Watershed Segmentation (IWS) method was implemented in ArcGIS 10.3 because of its capability in delineation of distinct tree entities. In the summer of 2018, three sites with different structures including a mixed uneven-aged dense stand (site 1), a mixed uneven-aged sparse stand (site 2), and a homogeneous even-aged dense stand (site 3) were surveyed and photographed, and a 3D point cloud was extracted from the images. Then, the performance of algorithms was tested using a series of different canopy height models (CHM) with spatial resolutions of 25, 50, 75, 100, and 120 cm. To generate these models, digital surface model (DSM) was subtracted from digital terrain model (DTM). Results of individual tree delineation were validated using data collected in field observation of the aforementioned sites.
Results & Discussion
Results indicated that both RG and IWS algorithms yielded their best performance in the dense homogeneous structure. Moreover, the number of segments resulting from CHMs with low resolution was often much more than the actual number of trees. This was due to the occurrence of several peaks within an individual tree crown especially in low resolution images. With an F-score of 0.88, homogeneous even-aged dense stand (site 3) showed the highest overall accuracy in RG algorithm with a pixel size of 75 cm. Generally, results indicated that RG is an appropriate approach for individual tree delineation due to its flexibility in delineation of varying crown sizes. Furthermore, this method does not assume a circular shape for tree crowns and thus, is capable of detecting and segmenting irregular crowns. Generally, delineation of trees in urban forests using CHMs obtained from UAV-captured aerial imagery was highly accurate in homogeneous sites, while such models lacked efficiency in heterogeneous sites.
Seyyed Reza Ghaffari-Razin; Navid Hooshangi
Abstract
Extended AbstractIntroductionThe Earth's atmosphere (atmosphere) is divided into concentric layers with different chemical and physical properties. To study wave propagation, two layers called the troposphere and ionosphere are considered. The troposphere is the lowest part of the Earth's atmosphere ...
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Extended AbstractIntroductionThe Earth's atmosphere (atmosphere) is divided into concentric layers with different chemical and physical properties. To study wave propagation, two layers called the troposphere and ionosphere are considered. The troposphere is the lowest part of the Earth's atmosphere and extends from the Earth's surface to about 40 kilometers above it. In this layer, wave propagation is mainly dependent on water vapor and temperature. Unlike the ionosphere, the troposphere is not a dispersive medium for GPS signals (seeber, 2003). As a result, the propagation of waves in this layer of the atmosphere does not depend on the frequency of the signals. The delay caused by the troposphere can be divided into two parts of hydrostatic delay and wet delay. The hydrostatic component of the tropospheric delay is due to the dry gases in this layer. In contrast, the wet component of tropospheric refraction is caused by water vapor (WV) in the troposphere. The study of atmospheric water vapor is important in two ways: First, short-term climate change is highly dependent on the amount of atmospheric water vapor. Water vapor has temporal and spatial variations that affect the climate of different regions. Second, long-term climate variation is reflected in the amount of water vapor. Obtaining water vapor using direct measurements and water vapor measuring devices is a difficult task. Radiosonde and radiometers are used to directly measure atmospheric water vapor, but the use of these devices will have problems and limitations, for example, the maintenance cost of these devices is expensive and also these devices do not have a suitable station cover. The best way to get information about water vapor changes indirectly is to use GPS measurements. GPS meteorological technology can provide continuous and almost instantaneous observations of the amount of water vapor around a GPS station.Estimation of precipitable water vapor (PWV) and water vapor density using voxel-based tomography method has disadvantages. The coefficient matrix of tomography method has a rank deficiency. Initial value of water vapor must be available to eliminate it. Also, the amount of WV inside each voxel is considered constant, if this parameter has many spatial and temporal variations. In this method, the number of unknowns is very high and it is computationally difficult to estimate (Haji Aghajany et al., 2020). To overcome these limitations, this paper presents the idea of using learning-based models. To do this, in this paper, 3 models of artificial neural networks (ANNs), adaptive neuro-fuzzy inference system (ANFIS) and support vector regression model (SVR) have been used. Materials and MethodsDue to the availability of a complete set of observations of GPS stations, radiosonde and meteorological stations in the north-west of Iran, the study and evaluation of the proposed models of the paper is done in this area. Observations of 23 GPS stations were prepared in 2011 for days of year 300 to 305 by the national cartographic center (NCC) of Iran. Out of 23 stations, observations of 21 stations are used to training of models and observations of the KLBR and GGSH stations are used to test the results of the models. In the first step, the observations of 21 GPS stations that are for training are processed in Bernese GPS software (Dach et al., 2007) and the total delay of the troposphere in the zenith direction (ZTD) is calculated. It should be noted that for every 15 minutes, a value for ZTD is calculated using the observations of each station. In the second step, the zenith hydrostatic delay (ZHD) is calculated. By subtracting ZHD from ZTD, zenith wet delay (ZWD) are obtained. ZWD values are converted to PWV values. The obtained PWV values are considered as the optimal output of all three models ANN, ANFIS and SVR. Also, the input observations of all three models will be the latitude and longitude values of each GPS station, day of the year and time. Results and DiscussionAfter the training and achievement of the minimum cost function value for all three models, the PWV value is estimated by the trained models and compared at the location of the radiosonde station as well as the test stations. The mean correlation coefficient for the three models ANN, ANFIS and SVR in 6 days was 0.85, 0.88 and 0.89, respectively. Also, the average RMSE of the three models in these 6 days was to 2.17, 1.90 and 1.77 mm, respectively. The results of comparing the statistical indices of correlation coefficient and RMSE of the three models at the location of the radiosonde station show that the SVR model has a higher accuracy than the other two models. The average relative error of ANN, ANFIS and SVR models in KLBR test station was 14.52%, 11.67% and 10.24%, respectively. Also, the average relative error of all three models in the GGSH test station was calculated to be 13.91%, 12.48% and 10.96%, respectively. The results obtained from the two test stations show that the relative error of the SVR model is less than the other two models in both test stations. ConclusionThe results of this paper showed that learning-based models have a very high capability and accuracy in estimating temporal and spatial variations in the amount of precipitable water vapor. Also, the analyzes showed that the SVR model is more accurate than the two models ANN and ANFIS. By estimating the exact amount of PWV, the amount of surface precipitation can be predicted. The results of this paper can be used to generate an instantaneous surface precipitation warning system if the GPS station data is available online.
