Volume 7, Issue 1 , December 2015, , Pages 1-20
Abstract
Location of some facilities such as shopping centers has a crucial role in their success. Finding the location of a new shopping centers where there are existing ones belonging to competitors, asks to consider and evaluate confusing factors and objectives. In this research based on multiple objective ...
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Location of some facilities such as shopping centers has a crucial role in their success. Finding the location of a new shopping centers where there are existing ones belonging to competitors, asks to consider and evaluate confusing factors and objectives. In this research based on multiple objective decision making (MODM) approach, two objectives are considered to maximize the profit: maximizing demand response and maximizing accessibility to shopping centers. Demand objective is evaluate based on two criteria: population and competitive conditions. Accessibility is related to access to major roads, public transit stations, parking, parks and entertainment centers. There are many methods for solving multi-objective problems that have been generally divided into classic and evolutionary methods. Classical methods are faced with several shortcoming and recent researches are focused on utilizing the heuristicmethods. In the proposed model, first unsuitable locations are removed based on their land use and then Tabu Search, as a multi-objective evolutionary algorithm, is used as a competitive location model for finding the location of new shopping centers based on the trade-off between objectives. The proposed model is tested in a case study area in Karaj city and the result is compared with traditional overly analysis. Keywords: Shopping center, Competitive location models, Multi objective optimizing, Tabu Search.
A Baghani; M.J Valadan Zoej; M Mokhtarzade
Volume 7, Issue 2 , November 2015, , Pages 1-18
Abstract
Due to the absence of either satellite ephemeris information or camera model for various high resolution satellite images, rational functions models (RFMs) are widely used by photogrammetric and remote sensing communities. This method has various disadvantages such as: The dependency of this method on ...
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Due to the absence of either satellite ephemeris information or camera model for various high resolution satellite images, rational functions models (RFMs) are widely used by photogrammetric and remote sensing communities. This method has various disadvantages such as: The dependency of this method on many ground control points (GCPs), numerical complexity and particularly terms selection. As there is no physical meaning for the terms of RFM, in traditional solution all of them are involved in the computational process which causes over-parameterization. In this letter, a modified Ant Colony Optimization is applied to identify the optimal terms for RFMs. For this purpose this method is tested on three images with different geometric correction levels, different coordinate systems (UTM, CT & Geodetic) and different combination of Ground Control Points (GCPs) and Independent Check Points (ICPs), without normalization of the image and ground coordinates. Experimental results demonstrate how well the proposed algorithm can determine an RFM, which is optimal in both the total number of terms and the positional accuracy. The results have showed that the CT coordinate system has the better capability in accuracy and convergence’s speed. As a conclusion, ACO when using for RFM optimization, can achieve subpixel accuracy even with just four GCPs.
Jadidi Milad Niroumand; Mehdi Mokhtarzade; Mahmood Reza Sahebi
Volume 7, Issue 3 , November 2015, , Pages 1-16
Abstract
The mixed pixels are considered as a major challenge in land cover mapping procedure from satellite imagery. Developments of the spectral unmixing and soft classification methods have provided the possibility for estimation of class proportions within the pixels. However, sub-pixel land cover mapping ...
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The mixed pixels are considered as a major challenge in land cover mapping procedure from satellite imagery. Developments of the spectral unmixing and soft classification methods have provided the possibility for estimation of class proportions within the pixels. However, sub-pixel land cover mapping requires the spatial allocation of the sub-pixels. Recently, the Super Resolution Mapping (SRM) techniques have been developed for optimization of the sub-pixels spatial arrangement using the outputs of soft classifiers and based on the concepts of spatial dependency. In this research, the overall capability of the simulated annealing algorithm was evaluated through sub-pixel land cover mapping of the study area. To do so, a novel method was proposed for generating new solutions in each step of the algorithm and then the results were compared to the traditional method. On the other hand, the effective parameters on the performance of the algorithm (e.g. zoom factor, cooling function type, static and dynamic iterations) were investigated. According to the obtained results, higher values of zoom factor yields more promising overall accuracy . Also, the geometric function was found as the optimal cooling function with respect to the overall accuracy and processing speed. Meanwhile, dynamic iterations demonstrated more accuracy than the static case. As another key result of the paper, the proposed method for generating the new solutions in simulated annealing algorithm is led to increasing of the overall accuracy and also reducing the processing time of algorithm up to 50 percent. The most accurate result of the proposed algorithm, which was obtained for the that case of being independent from soft classifier, is determined 94.97 percent
Ali akbar Matkan; Babak Mirbagheri; Abbas Beigi; Mostafa Ghiyasvand
Volume 7, Issue 4 , November 2015, , Pages 1-12
Abstract
Researchers have always been looking for better ways to develop the design, operation and implementationofwater distribution networks in GIS.Despite,extensivegeographical potentials of GIS,however, it cannot be independently considered as a spatial decision support system (SDSS) for management of this ...
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Researchers have always been looking for better ways to develop the design, operation and implementationofwater distribution networks in GIS.Despite,extensivegeographical potentials of GIS,however, it cannot be independently considered as a spatial decision support system (SDSS) for management of this kind of networks. This research aimed to develop a spatial decision support systemin the form of standalone application for management of the water distribution network of FereidoonShahr City. This study attempts to combine advanced analytical hydraulic functions with the spatial analysis potentials of GIS software.In this regard, the identification and assessment stage was intended to develop the components of SDSS including Database Management component, Model Management component and Dialog Management component. By implementing conceptual, logical and physicalmodels in Database Management component, our geodatabase was developed. By using user friendly interfaces in order to communicate easily with users the Dialog Management component was developed. After that,in the Model Management component, some hydraulic models of water distribution networks such as velocity analysis model of pipes, and pressure on junctions were developed using ArcObjects components. Ultimately, alternative evaluating models were designed in order to solve semi-structured issues of urban water distribution networks. With the implementation of the above system for the first time in Iran which is based on a scientific approach, network administrators and analysts can use this software as a comprehensive SDSS in the analysis of urban water distribution networks.
E Khodabandehloo; A Alimohamdadi; A Sadeghi-Niaraki; A Darvishi Boloorani; A.A Alesheikh
Volume 8, Issue 1 , November 2016, , Pages 1-18
Abstract
Dust storm has been one of the most important challenges of western Asia. This phenomenon has been intensified due to the drought and has many negative effects on people's lives. Since this region located in a dust belt in the world, it is necessary to explore different aspects of this phenomenon ...
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Dust storm has been one of the most important challenges of western Asia. This phenomenon has been intensified due to the drought and has many negative effects on people's lives. Since this region located in a dust belt in the world, it is necessary to explore different aspects of this phenomenon is well. Predictive and modeling of this phenomenon can be prevented of jeopardizing the lives of millions of people. So present a Regional Model to assess different aspects of this phenomenon is necessary. Since climate and weather elements are constantly changing, the spatiotemporal model should be used for modeling and visualization. Hence, a model for estimating dust emission has been designed and developed and Geographic Information System (GIS) spatial modeling capabilities and remote sensing (RS) data (wind speed, soil moisture, soil texture and digital elevation model) are used. The model which is called DustEM calculates horizontal dust emission. In this study, modeling is done for 2001 to 2007 and model’s output is evaluated by MODIS AOD and for dictating hot spot area output is clustered in 3 categories contain high, medium and low with threshold 0.3 and 0.6 for AOD. Accuracy index mean for the study period was 73.6% and show high precision of model in detecting hot spot area.
F Shafiei; A Darvishi Boloorani; S Pourmanafi; A Shahsavani
Volume 8, Issue 2 , November 2016, , Pages 1-16
Abstract
Dust storms are atmospheric phenomena with negative environmental effects and especially for human health. Sampling and analysis of physical and chemical composition of recent dusts show that they are not merely composed of dust, gravel, sand and salt particles, rather they are of complex combination ...
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Dust storms are atmospheric phenomena with negative environmental effects and especially for human health. Sampling and analysis of physical and chemical composition of recent dusts show that they are not merely composed of dust, gravel, sand and salt particles, rather they are of complex combination of chemical elements. Metals such as soil alkaline metals, carbon, silica, aluminum, potassium, calcium and other organic components are observed that all these elements can have harmful effects on public health. In this study, Ahwaz where during last decades has seen several storms was studied. Using collected samples in the ground station and laboratory analyses dust contents were determined for seven dust events. For use of remote sensing technology using satellite images in order to identify the elements of dust, MODIS satellite images were used. Using MODIS images, the least squares method and cross-validation modeling, the relationship between MODIS bands and the results and measured chemical contents of dusts were created. Results show that silica, can be estimated from the ratio of 21 band to 26 with RMS 1.28. For aluminum, the ratio bands 25 to 26 with RMSE 2.08, for calcium the ratio of bands 24 to 25 with RMSE 2.3, for sodium of the ratio of bands 23 to 27 with RMSE 0.48 and finally for Magnesium the ratio of bands 15 to 24 with 0.78 RMSE are useful indexes to identify these elements using MODIS satellite images. According to the results MODIS images are useful for dust storms chemical elements estimation. Also using CALIPSO data, the rate of concentration and intensity of dust particles at the height of 6 km/asl are
, Y Rezaei; , M.J. Valadan Zouj; , M.R Sahebi
Volume 9, Issue 1 , October 2017, , Pages 1-16
Abstract
Mountain Glaciers are pertinent indicators of climate change and their surface velocity changes, are an essential climate variable. In order to retrieve the climatic signature from surface velocity, large scale study of glacier changes is required. Satellite remote sensing is an effective way to derive ...
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Mountain Glaciers are pertinent indicators of climate change and their surface velocity changes, are an essential climate variable. In order to retrieve the climatic signature from surface velocity, large scale study of glacier changes is required. Satellite remote sensing is an effective way to derive mountain glacier surface velocities. In this research, we have conducted a comprehensive assessment of Alam-Chal glacier surface changes (include displacement and velocity), all based on remotely-sensed data. All datasets include aerial photos and satellite images were ortho rectified, normalized and co-registered. By using an aerial photograph collected in 1955 as a baseline and comparing it against a 2003 image collected by the SPOT satellite, the glacier retreat, in direct response to changes in local climate conditions were extracted. Furthermore, we have assessed short-term changes over two-time scales (1988-2003, 2003-2005),using an aerial photo acquired in 1988, a 2003 SPOT image, and a high-resolution Quick Bird image collected over the study area in 2005. We have derived accurate glacier surface velocity vectors (RMSE~2m), based on an FFT-based image cross-correlation technique. Our results point to the capability of the proposed method in accurately retrieving glacier surface changes at a high level of spatial detail, which is important for studies of regional climate change.
M Akhondi; M Mesgari; M. R Malek; O Askari Sichani
Volume 9, Issue 2 , December 2017, , Pages 1-20
Abstract
Nowadays, heavy traffic is one of the major problems of living in big cities. In recent years, to overcome this problem, various solutions are proposed, many of which have been on the basis of general and comprehensive models. However, because of the essential complexity of urban environment and because ...
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Nowadays, heavy traffic is one of the major problems of living in big cities. In recent years, to overcome this problem, various solutions are proposed, many of which have been on the basis of general and comprehensive models. However, because of the essential complexity of urban environment and because of the diversity of parameters affecting urban traffic, those models cannot represent the dynamic space of urban traffic, properly. In contrast to them, agent based approach is a promising approach for modeling of urban traffic. This is mainly because of its ability in modeling the interactions of traffic components, and in the modeling of the dynamic nature of urban environment. Much research has been made in the field of application of agent technology to the modeling of urban traffic. The majority of these researches are focused on a particular area of traffic phenomenon. Some of them are on providing traffic lights with some levels of intelligence. Others try to simulate the behavior and decision making of the drivers. In other cases, agent based modeling is used for simulation of dynamic vehicle routing systems using real-time traffic information. Nonetheless, less attention is paid to the more comprehensive modeling of traffic using intelligent agents. Therefore, in this research, an agent based model is proposed for improving the navigation of vehicles, on the basis of communicating traffic information amongst traffic components. The urban environment is modeled as a vector space. The model components include the two-way streets, intersections, traffic lights, origin and destination of cars. Environment comprises of intersections, streets between intersections, and streets between intersections and the origin/destination points. Active agents are the cars, traffic lights and traffic control center. In this agent based model, the green-red changing of traffic lights is controlled and programmed based on the traffic jam condition (number of cars) of the streets connected to the light. It is assumed that all vehicles are equipped with GPS and necessary communication media. The system is implemented using JADE platform and its class libraries. The data of a simulated traffic network is entered to the model. The main result of this study is a simple model of the basic part of the urban traffic, in which mobile vehicles and traffic lights have access to online traffic information. In this model, all three types of agents, i.e. cars, traffic lights and traffic control center, can communicate with each other. By defining some criteria, the impact of such communications and access to online information can are assessed. In other words, the results of different scenarios are evaluated using criteria such as traffic jam and average of traveling time. An important aspect of the model is that, although communicating with each other, all agents including drivers and traffic lights act and decide independently, i.e. without any centralized decision-making system. In this study, no GIS software is directly used. However, the behavior of vehicles and traffic lights are modeled on the basis of metric spatial relationships (distance calculations) and topological relations (connections of the street edges with each other and with traffic lights). In other words, in this study, a simple spatial environment and simple spatial behaviors are modeled. Spatial environment of two-way street and moving in them is represented by movements in a set of simple lines in the direction of X and Y axes. This model is the first step towards a more complete modeling of urban traffic. In this model, the spatial movements of vehicles are modeled as vectors. The lengths of these vectors are calculated using the assumed vehicle speeds, the distance between points, and simple estimations of traffic jams.
F Mahmoudi; M Mokhtarzadeh; M.J Valadan Zouj
Volume 9, Issue 3 , February 2018, , Pages 1-14
Abstract
This research studies the suitable process of change detection at at an Agricultural areas by focusing on object based method and color fusion. In order to obtain this goal, it is benefit from Landsat7 images. The main idea of offering object based method is a modern algorithm i.e. Double-layer image ...
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This research studies the suitable process of change detection at at an Agricultural areas by focusing on object based method and color fusion. In order to obtain this goal, it is benefit from Landsat7 images. The main idea of offering object based method is a modern algorithm i.e. Double-layer image are combined and An image of the entire layer is formed. Then by selecting suitable parameters a single image is separated in to several parts and by color fusion and object based classification method the changed and unchanged parts are classified. In fact, color fusion is determined by creating different color areas with elementary images that determines changed parts on visual basics and then by using object based classification method and selecting some parts by the user, the total parts of image is determined. Finally, by selecting training samples only one part of image is labeled and its classification is determined and the ultimate map of changes is obtained. Results show that this method is suitable for reducing training samples, increasing exactness (3%-2.5%), speed and increasing information for classification of spatial information and structure and in addition to spectral information it is better than ordinary methods of change detection from comparing 2 multi-temporal images.
F Mohseni; M Mokhtarzadeh
Volume 9, Issue 4 , May 2017, , Pages 1-22
Abstract
Soil moisture plays an important role in interactive processes between earth and atmosphere and global climate changes. In recent decades, there has been a great research interest to determine soil moisture from remote sensing methods. Triangular or trapezoidal methods are the most common remote sensing ...
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Soil moisture plays an important role in interactive processes between earth and atmosphere and global climate changes. In recent decades, there has been a great research interest to determine soil moisture from remote sensing methods. Triangular or trapezoidal methods are the most common remote sensing methods that apply the combination of thermal and optical satellite images to estimate soil moisture content. The accuracy of methods governed by the accuracy of saturated and dry edges that define from vegetation/ temperature scatter plot. A main limitation of these methods arose in some days or in some vegetation condition that dry and wet edges cannot be defined correctly. This concern is addressed in this paper by using the temperature and vegetation information during one year interval to form the temperature-vegetation scatter plot, saturated edge and dry edge exactly. The main contribution of the paper is, however, the introduction of co-moisture lines in the one-year scatter plot. These lines are later applied to define the wet and dry edges of each individual day which are taken as the two closest co-moisture lines that contain all corresponding pixels of that day. The soil moisture index as a parameter dependent to evaporation efficiency is finally estimated from the slope and intercept of these two co-moisture lines. The proposed soil moisture index calculated from co-moisture was implemented and validated in Manitoba, Canada area while MODIS satellite images, taken in 28 cloudless days of year 2014, were used as the input data. The correlation between ground soil moisture data and proposed soil moisture index was estimated. Correlation of 0.92 was achieved for low vegetation days and lower in days with higher vegetation densities.
P Zeaiean Firozabadi; P Safarbeyranvand; A Hosseinhgholizade; R Hasanitabar; M Safarbeyranvand
Volume 10, Issue 1 , June 2018, , Pages 1-16
Abstract
The issue of the mapping of rock units in an ever-expanding area has now reached a point where the detection and classification of rock units is carried out through the aid of hyperspectral image. In this research, Hyperion images are used in the light of the work of previous researchers and the application ...
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The issue of the mapping of rock units in an ever-expanding area has now reached a point where the detection and classification of rock units is carried out through the aid of hyperspectral image. In this research, Hyperion images are used in the light of the work of previous researchers and the application of the SAM supervised classification algorithm for the detection and separation of rock units in Khorramabad region, Lorestan province. After performing the necessary preprocesses including atmospheric correction performed by the FLAASH method, linear MNF transformation was used to determine the dimension of main image, to separate the noise from other information and reduce the processing level in the next stages, and the PPI algorithm to find the pixels that More purity is used in multispectral images. From the overlapping of pure pixels with rock units and based on ground data from the study area, the average range was extracted for each member. Then, these pure members were used as inputs for the above-mentioned algorithms and image categorization was used. Finally, the mapped classification of this method was compared with existing maps and land data and their accuracy was checked. The accuracy of the SAM method was verified by verifying the accuracy of the algorithm by calculating the error matrix with the highest of 68.83% and kappa coefficient of 0.49%, which indicates the importance of hyperspectral images and the SAM method in separating the rock units.
Seyed Yousef Sajjadi; Saeid Parsian
Volume 10, Issue 2 , September 2018, , Pages 1-14
Abstract
In this study, the fusion of hyperspectral and LiDAR data was used to propose a new method to detectbuildings using the machine learning algorithm. The data sets provided by the National ScienceFoundation (NSF) - funded by Centre for Airborne Laser Mapping (NCALM)- over the University ofHouston campus ...
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In this study, the fusion of hyperspectral and LiDAR data was used to propose a new method to detectbuildings using the machine learning algorithm. The data sets provided by the National ScienceFoundation (NSF) - funded by Centre for Airborne Laser Mapping (NCALM)- over the University ofHouston campus and the neighboring urban area, were used. The objectives of this study were: 1)automatic buildings extracting using the hyperspectral and LiDAR fused data (automation), 2)detecting of the maximum number of listed buildings on the study area (completeness), and 3)achieving the high accuracy in building detection throughout the classification procedure (accuracyand precision). After classification of the buildings, a comparison was made between the resultsobtained by the proposed method and the reference method in this field. Our proposed methodshowed a better accuracy for buildings detection in a much shorter time compared to the referencemethod. The accuracy of the classification was assessed by four parameters of Precision,Completeness, Overall Accuracy and Kappa Coefficient, and the values of 96%, 100%, 99% and 0.94were obtained, respectively.
Ali shamsoddini; hasan mehrzad; babraz karimi
Volume 10, Issue 3 , January 2019, , Pages 1-16
Abstract
Agriculture is one of the most important economic parts in each country, which each product requires specific climatic and environmental conditions. So climatologists pay special attention to landuse planning and managing ecological resources with appropriate methods. The purpose of this study is to ...
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Agriculture is one of the most important economic parts in each country, which each product requires specific climatic and environmental conditions. So climatologists pay special attention to landuse planning and managing ecological resources with appropriate methods. The purpose of this study is to identify the effective climatic factors and elements in fig planting in Fars province and zoning the areas susceptible to planting this product climatically and environmentally, using the ability of GIS to combine different layers and in the form of different models. In this study, six climatic elements (average temperature, maximum and minimum absolute temperature, average and maximum humidity and amounts of precipitation) from 21 stations of synoptic, climatology and Rain gauge stations in Fars province and 5 environmental parameters (elevation, slope, soil type, erosion and landuse) has been used. First, the climatic elements have been reconstructed using Differences and Ratios methods due to their incompleteness. Then maps of these parameters and elements are plotted in GIS and these maps are standardized and weighted using Fuzzy logic and the criteria for fig tree planting, and combined with Fuzzy logic, and zoning map of susceptible land obtained in Fars province. The results showed that 32 percent of the lands are very suitable for planting Figs, 40 percent has a moderate ability, and 22 percent are also inappropriate for fig tree planting. In addition, 6% of the lands is not worthy of Fig tree planting (lake lands, salty lands, etc.), which is excluded from the analysis.
Sholeh Malekshahi; Iraj Rassa; Nematollah Rashid Nezhad Omran; Mohammad Lotfi
Volume 10, Issue 4 , February 2019, , Pages 1-26
Abstract
Separation and mapping of alteration zones in the exploration of porphyry copper types is of particular importance. Aster sensor of Terra satellite image is used to show these alteration zones. There are different alteration in the Sarkuh area, include potassic, propylitic, phyllic, argillic, siliceous ...
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Separation and mapping of alteration zones in the exploration of porphyry copper types is of particular importance. Aster sensor of Terra satellite image is used to show these alteration zones. There are different alteration in the Sarkuh area, include potassic, propylitic, phyllic, argillic, siliceous veins, and secondary effects to iron oxide-hydroxides that are reflected in the development of Aster images. Using methods such as color composition, band ratio, false color composition from band bonding and spectral analysis methods(Matched Filtering ، Ls-fit), was used. In argillic alteration, iron oxides and propylitic processes, Matched Filtering, Ls-fit And the bandwidth ratio method is used among these methods, the MF algorithm and bandy's ratio is well answered. Potassic alteration has a close connection with mineralization. propylititic alteration includes calcite + chlorite + epidote + actinolite + sericite + pyrite in the surroundings of Stock and also volcanic rocks around it.. Phyllic alteration contains sericite and quartz. The results obtained in this section are also consistent with the results of the XRD analysis. In survey field, the set of alteration zones shows a relatively regular zoning with the north-east-southwest process with the center of the porphyry-type Sarkuh porphyry mass.
Behrooz Moradi; mohammad javad valadan zoej; mojtaba jannati; somayeh yavari
Abstract
In the absence of satellite ephemeris data and inner geometry of satellite’s sensor, utilization of Rational Function Models (RFMs) is one of the best approaches to georeferencing satellite images and extracting spatial information from them. However, since RFMs have high number of coefficients, ...
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In the absence of satellite ephemeris data and inner geometry of satellite’s sensor, utilization of Rational Function Models (RFMs) is one of the best approaches to georeferencing satellite images and extracting spatial information from them. However, since RFMs have high number of coefficients, then usually high number of control points is needed for their estimation. In the other hand, RFM terms are uninterpretable and all of them causes over-parametrization error which count as the most important weakness of the terrain-dependent RFMs. Utilization of optimization algorithms is one of the best approaches to eliminate these weaknesses. Therefore, various optimization algorithms have been used to discover the optimal composition of RFM’s terms. Since the mechanism of these algorithms is different, the performance and feature characteristics of these algorithms differ in the discovery of the optimal composition train-dependent RFM’s terms. But the existing differences not comprehensively analyzed. In this paper, in order to comprehensive assessment the abilities of Genetic Optimization Algorithm (GA), Genetic modified Algorithm (GM), and a modified Particle Swarm Optimization (PSO) in terms of accuracy, quickness, number of control points required, and reliability of results, are evaluated. These methods are evaluated using for different datasets including a GeoEye-1, an IKONOS-2, a SPOT-3-1A, and a SPOT-3-1B satellite images. In terms of accuracy achieved, difference between these methods was less than 0.4 pixel. In terms of speed of evaluation of parameters, GM was 10 to 12 time more quickly in comparison with two other algorithms. In terms of control points required, degree of freedom of modified PSO was 45.25 percent and 27 percent more than GM and GA respectively, and finally in terms of reliability, the dispersion of RMSE obtained in 10 runs of three algorithms are relatively same. These results indicated that accuracy and reliability of all three methods are almost the same, speed of GM is higher and modified PSO needs less control points to optimize terrain-dependent RFM
Naser Shafiei Sabet; Maliheh Ayoubi; Abolfazl Fadaei Bashi
Abstract
Metropolises are horizontally drawn to the periphery due to the extreme concentration of power, capital and population and this physical development often occurs unevenly, which causes many problems including land use change, natural and socioeconomic transformation, and consequently environmental problems. ...
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Metropolises are horizontally drawn to the periphery due to the extreme concentration of power, capital and population and this physical development often occurs unevenly, which causes many problems including land use change, natural and socioeconomic transformation, and consequently environmental problems. Factors such as urban growth, land value and development density are among the most important factors in the formation of urban sprawl, which transforms the inner structure of cities and causes the heterogeneous development of urban indicators in periphery, and it transforms the areas into unplanned spaces. In this research, urban sprawl patterns and analysis of changes were carried out during three periods, using GIS and remote sensing, as well as Landsat TM satellite data and images of 1986 and ETM+ 2000 and ETM+ 2014. The findings of this research show that in the past three years, residential construction has increased dramatically in the region. The area of such construction rose from 4.89% in 1986 to 10.3% in 2014. In contrast, the area of agricultural land decreased from 61.33% in 1986 to 44.7% in 2014. Moreover, scattered structures and urban sprawl in the studied area were according to discrete sprawl pattern, which has led to inconsistencies in the agricultural sector and rural economy of the area. Furthermore, the expansion of the network of roads, highways, electricity networks and non-residential construction have exacerbated the discontinuous urban sprawl in the study area. On this basis, attention to the integrated land use planning alongside urban and rural integrated planning might be a remedy to reduce agricultural instability and to change the use of valuable agricultural lands and rangeland
Fatemeh Hadian; Reza Jafari; Hossein Bashari; Mostafa Tarkesh
Abstract
Plants are one of the most important components of the ecosystem which are affected by natural and human factors. Therefore, the study of net primary production (NPP) is one of the main subjects in ecology. The main purpose of this research was to model spatial and temporal distributions of NPP ...
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Plants are one of the most important components of the ecosystem which are affected by natural and human factors. Therefore, the study of net primary production (NPP) is one of the main subjects in ecology. The main purpose of this research was to model spatial and temporal distributions of NPP and also to determine the degradation of vegetation types using Carnegie Ames Stanford Approach (CASA), Rain Use Efficiency (RUE) and Light Use Efficiency (LUE) models in semi-steppe rangelands of Isfahan Province. For this purpose, the 16- day MODIS NDVI images, metrological data, land cover maps and field study were applied in the study area. The results showed that the NPP rate increased from March (11.44gC/m2/mo) to May (41.07gC/m2/mo) while demonstrating a decreasing trend from the onset of June (2.2 g C/m2/mo) due to soil dryness. Climate , vegetation type and rangeland conditions had important roles in annual plant NPP and therefore the highest and lowest NPP were observed in Astragalus- Daphnae (38.85 gC/m2 y-1) and Artemisia sieberi - Scariola (4 g C/m2 y-1) vegetation types with maximum (0.13 g C (MJ)-1) and minimum (0.005 g C (MJ)-1) LUE, respectively. The amount of RUE decreased in degraded rangelands. Moreover, the correlation between field measurements and the CASA model decreased in semiarid warm climate and degraded rangelands. Therefore, rangeland conditions, vegetation type and climate condition must be taken into consideration in NPP monitoring and rangelands management.
Monireh Mosabeaigi; Imam Baharloo; Alireza Vafaeinezhad
Abstract
Identify factors contributing to the spread of soil erosion, and zoning is an important tool to manage and control this phenomenon and to determine appropriate ways are to deal with spreading this phenomenon. In this research, using analysis network process model and GIS has been estimated zoning map ...
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Identify factors contributing to the spread of soil erosion, and zoning is an important tool to manage and control this phenomenon and to determine appropriate ways are to deal with spreading this phenomenon. In this research, using analysis network process model and GIS has been estimated zoning map of soil erosion in the catchment tea castle in West, East Azerbaijan Province. For this purpose, by examine the sources and expert opinion, effective factors such as slope, aspect, lithology, land use, normalized difference vegetation index (NDVI), annual precipitation and soil is provided of the geographic information system environment. Then, using Arc GIS software and extracted coefficient, the analysis network process prepared to zone map soil erosion and in five classes: very high, high, medium, low and very low. The results showed that 37.12 percent of the area that includes 118.56 square kilometers, is located in risk classes the high and very high. Furthermore, necessary to explain that in the southern and central parts of the basin is the amount of soil erosion high. These areas showed critical situations and acute erosion. And due to dam construction, Ghale Chai should be placed the priority programs and plans of soil conservation and watershed management.
َAmirhossein Vahdat; Abas Alimohammadi
Abstract
The models of the association between land use and air pollution have wide applications in urban studies, but the land-use role and its different parameters effective on the variability of air pollution concentration in various hours can be used for more accurate Spatio-temporal prediction of pollution. ...
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The models of the association between land use and air pollution have wide applications in urban studies, but the land-use role and its different parameters effective on the variability of air pollution concentration in various hours can be used for more accurate Spatio-temporal prediction of pollution. In this study, to make Spatio-temporal prediction of CO pollutants using hourly land-use regression (LUR), the effective parameters on Spatio-temporal variation of this pollutant are investigated during the day and night. The hourly data are collected from 21 air pollution monitoring stations for the summer in Tehran and the predictive parameters including density and distance from different variables such as road network, vegetation, elevation, and different land-use are generated in the geographic information system (GIS). A general model and 8 hourly models are created at 3 am, 6 am, 9 am, 12 noon, 3 pm, 6 pm and 12 midnight. The coefficient of determination (R2) of the created model is equal to 0.7898, and it shows that the model has an outstanding performance. By analyzing the generated hourly models, because of the differences in the parameters used in these models, it is denoted that both temporal variability and spatial variability play effective roles in forming the models during the day and night. The coefficient of determination (R2) of the hourly models ranges from 0.51 to 0.92 in which the lowest one and the highest one are related to the noon hours’ models and the nocturnal hours’ models, respectively. The parameters including local access roads and official/commercial areas have the most effect on increasing CO pollutants during the day and night, and the parameters including green space, sports, and medical centers lead to the locations with lower CO pollutants concentration.
Hamid Jannati; Mohammad Javad Valadan Zoej
Abstract
Speckle in Synthetic aperture radar images makes grainy effects, because of the coherent imaging system which cause some difficulties in object-oriented processes, like segmentation or classification. Therefore, a lot of methods have been developed for speckle reduction purpose. These methods can be ...
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Speckle in Synthetic aperture radar images makes grainy effects, because of the coherent imaging system which cause some difficulties in object-oriented processes, like segmentation or classification. Therefore, a lot of methods have been developed for speckle reduction purpose. These methods can be classified but not limited in some approaches, like spatial based, transform based and optimization, which mostly suffer from limitations like edge and texture destruction and also regulating parameter dependence. In this paper a new structure has been presented based on adaptive filtering of the amplitude response of the discrete fourier transform of the image in the frequency space, which not only reduces the speckle but also preserves edges and delicate textures. In addition, it has low level of computation and complexity compared to the kernel dependent spatial approaches. The main contribution of the paper is to fit a predefined analytical function to amplitude response of the discrete fourier transform of the image, in order to recover underlying speckle reduced SAR image. Proposed method, improves equivalent number of looks index 50 percent and edge preservation index 50 and 30 percent for real and simulated synthetic aperture radar images, respectively.
Hadi Zare khormizie; Hamid Reza Ghafarian Malamiri
Abstract
Phenology is the study of the occurrence of repeatable plant life events in relation to living and non-living factors. The phenology reflects the response and adaptability of ecosystems to climate change. Phonological study can be used to regulate livestock grazing management programs at rangeland, various ...
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Phenology is the study of the occurrence of repeatable plant life events in relation to living and non-living factors. The phenology reflects the response and adaptability of ecosystems to climate change. Phonological study can be used to regulate livestock grazing management programs at rangeland, various agricultural activities, and etc. In order to study the effect of height and temperature on plant phenological processes, harmonic analysis of time series satellite observations was used. In this study, the 8-day products of the NDVI indices of MODIS sensor (namely MOD09Q1) with a spatial resolution of 250 m was used. First, the HANTS algorithm was used to decompose the one-year NDVI MODIS products time series to thier Fourier Series components (the amplitude and phase images). Then, the correlation of each of these components with respect to height and temperature were investigated in Shirkoh area of Yazd province. According to the results, with 1 centigrade decrease in the average spring temperature, which occurs with elevation, there were a delay of 6.6 days in annual cycles and 3.9 days in the 6-month cycles of the NDVI time series, respectively. These results indicate that a delay of 6.3 days was observed in phenological processes and plant starting growth time in plant with annual growth periods and a delay of 3.9 days in plants with seasonal and six-month growth stages. Accordingly, the results of the HANTS algorithm and the Fourier series analysis can be very effective in understanding the effects of climatic factors on phenological processes and the onset of plant growth.
Behrooz Moradi; AbasAli Mehraban; Morteza Mohammadi
Abstract
Autonomous landing is a key challenging in the domain of UAV navigation systems. Developing an autonomous landing system requires a precise estimation of the UAV pose relative to landing marker, particularly in vision systems this involves precise Helipad recognition. It seems that traditional approaches ...
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Autonomous landing is a key challenging in the domain of UAV navigation systems. Developing an autonomous landing system requires a precise estimation of the UAV pose relative to landing marker, particularly in vision systems this involves precise Helipad recognition. It seems that traditional approaches including cascade classifiers, image matching and segmentation techniques to have major challenges in different weather conditions and scales. On the other hand, convolutional neural networks (CNNs) have been introduced as a powerful tool in the visual recognition systems in the recent years but the high computational cost of this techniques, limited their performance in the low cost and light weight UAVs. The aim of this paper is to compare the convolutional neural networks and cascade classifier for helipad detection. The results show that CNNs are invariant under translation, rotation, scaling and occlusion. The detection accuracy of this method is 99.1 % which is 3 % more than cascade classifier while its running time is suitable for real time UAV applications.
Mohammadreza Negahdarsaber; Shohreh Didari; Mojtaba Pakparvar; Alireza Abbasi
Abstract
Iranian oak has been affected by oak canopy level dieback in recent years. This phenomenon has led to damage a vast part of the oak forests in the Zagros arena. As to the suitable temporal and spacial resolution of the recent satellite images, it seems promising to detect the forest dieback by remote ...
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Iranian oak has been affected by oak canopy level dieback in recent years. This phenomenon has led to damage a vast part of the oak forests in the Zagros arena. As to the suitable temporal and spacial resolution of the recent satellite images, it seems promising to detect the forest dieback by remote sensing. The spatial capabilities of Spot6 images with pan and spectral resolution of 1.5 and 6 m, respectively in detecting the drying of oak trees was investigated. The forest area was located on Kuhmareh district of Shiraz in Fars province. The values of different indices such NDVI, EVI, TDVI, SAVI, RNDVI, OSAVI, DVI, MSR of each tree stocks was obtained and the corresponding quantity of dryness was determined at the filed. The best correlation was obtained between TDVI and the observed data. A non-linear function was built based on TDVI standard deviation to predict the dryness of more than 30% as y=17.92(x-0.06)-0.32 with an R2 = 82%. Monitoring forest areas to understand the decline or recovery of trees will be of great help to the forest management community. Therefore, using the results of this study can be a proof to compare the current situation with future periods.
Maryam Teimouri; Mehdi Mokhtarzade; Mohammad Javad Valadan Zoej
Abstract
In this study, the SAR data is used as a supplementary data to overcome the limitations of the multispectral (MS) image in building detection. Therefore, the proposed method utilizes a multisensor data fusion to take the advantages of both MS and SAR data together. In addition, two different filter-based ...
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In this study, the SAR data is used as a supplementary data to overcome the limitations of the multispectral (MS) image in building detection. Therefore, the proposed method utilizes a multisensor data fusion to take the advantages of both MS and SAR data together. In addition, two different filter-based feature selection methods, MNF and PCA, are investigated as an alternative scenario when the training data is not accessible. In this respect, the optimum feature vector is selected using MNF, PCA and Genetic methods from MS and SAR data, separately. Thereafter, each selected feature vector is used to classify the images by implementing the support vector machine (SVM) and the artificial neural network classification methods. The experimental result shows that the PCA is able to select the feature vector without the need of training data as well as genetic algorithm. However, the MS classification result is poor where both roofs and streets are covered with asphalt. In this framework, the fusion of SAR and MS images in feature level was utilized to improve the classification results. Finally, to assign a label at the sample, a majority voting is calculated between the used classification methods results. However, according to the noisy result, using the neighborhood information in the form of a moving spatial window in different sizes is examined to determine the label of the central pixel more accurately. According to the experimental results, the overall accuracy and building detection accuracy are obtained 92.82% and 80.14%, respectively, which represent the satisfying performance of the proposed method.
Mahmoud Bayat; Khosro Mirakhorloo; Hosein Sadeghzadeh; Sahar Heidari Masteali
Abstract
Lack of up-to-date, documented and scientific information on the current situation (area and distribution) of Zanjan poplar plantation is one of the main problems of wood production managers for planning and management of wood supply in the province and the country. In this study, Sentinel-2 satellite ...
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Lack of up-to-date, documented and scientific information on the current situation (area and distribution) of Zanjan poplar plantation is one of the main problems of wood production managers for planning and management of wood supply in the province and the country. In this study, Sentinel-2 satellite data with spatial resolution of 10 m in spectral bands were used and the ground truth map of existing poplar fields with 600 points was plotted in all cities and villages from field surveys. From the beginning to the end of the poplar growing season (first half of March to December 2018), at least 6 time periods of 30 to 40 days were used in the SVM classifier. Post-test and calibration of SVM model based on the phenology of poplar genus and field samples were extracted, populated area distribution map of province was extracted. The results showed that the total area of poplar areas is 2744 hectares which covers 0.12% of total area of Zanjan province. One percent of the total polygons were randomly selected for field control and after field control, the overall mapping error was obtained and calculated. In this study, the exact location and area of poplar mills were estimated with acceptable accuracy (96%). So that using extracted information (distribution map of poplars of the province) can provide studies on comprehensive planning of poplars and sustainable management of wood production from the poplars of the province.
