Monir Darestani Farahani; Mahdi Akhondzadeh Hanzaei; Farhang Ahmadi Qivi
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Abstract
Water salinity is one of the important environmental factors of the sea and plays a significant role in the study and prediction of the oceanic surface currents, location analysis of the fish aggregation, density determination and studying its changes, and also in ecological properties. This ...
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Abstract
Water salinity is one of the important environmental factors of the sea and plays a significant role in the study and prediction of the oceanic surface currents, location analysis of the fish aggregation, density determination and studying its changes, and also in ecological properties. This parameter changes greatly with time and location, and proper recognition of it requires measurements at short time intervals (monthly) of multiple points in the study area.
In traditional ways, the assessment and evaluation of one or several specific factors of water quality is often costly and time-consuming, and cannot be a good indication for the entire area of a vast region. But in recent years, satellite and remote sensing technology have been considered as an appropriate tool for evaluating some water quality parameters because, given the digitality of these data, their wide availability, regular measurements, their repetition in short periods of time, Less cost and time, a wide range of projects can be achieved. The purpose of this study is mapping sea surface salinity of the Persian Gulf in Iran and the Gulf of St. Lawrence in Canada using MODIS satellite imagery. In this regard, a software has been produced in Iran for the first time that can prepare salinity, temperature and density maps of the sea surface in three different models with proper accuracy by entering the MODIS satellite imagery and CTD field data. High capability and flexibility of the Artificial Neural Network in approximation of nonlinear and linear continuous functions in hybrid space, led this study to provide a new method based on using this network in which salinity map is determined by a multilayer perceptron network.
Zeinab Obeidavi; Kazem Rangzan; Mostafa Kabolizadeh; Rouhollah Mirzaei
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Abstract
Sustainable management of wildlife and natural habitats is an outcome of a series of spatial, quantitative and qualitative surveys and studies related to wildlife populations and habitat populations, a matter which necessitates to pay attention to the proper maintenance of existing data ...
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Abstract
Sustainable management of wildlife and natural habitats is an outcome of a series of spatial, quantitative and qualitative surveys and studies related to wildlife populations and habitat populations, a matter which necessitates to pay attention to the proper maintenance of existing data and to organize them to increase the useful life of such data in order to avoid repeating the operations of data acquisition and collection, and consequently to avoid the loss of funds for conservation and management of wildlife. Therefore. In the present study, considering the advantages of using database management system for maintenance, use and management of data, the design and implementation of a wildlife spatial database sample in Khuzestan province is carried out. In the design and implementation of the target database, the PostgreSQL / PostGIS object-relational database was used. According to the findings of the study, the PostgreSQL / PostGIS open source database management system was identified as an appropriate option for the development of the spatial data management capabilities of wildlife. It was also found that the designed system was able to support all possible questions related to wildlife spatial data, providing a solution to some issues and problems related to the management of a huge amount of wildlife scattered data. Also, due to the success of the present research, the necessity of focusing on the organization and management of wildlife information in the country and its inclusion in the context of the policy of the Environmental Protection Agency of the nation has been emphasized, and the need for the creation and development of a comprehensive spatial database of the wildlife of is pointed out.
Mohammadzaman Ahmadi; Saeed Behzadi
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Abstract
Wells are one of the main sources of drinking water, agriculture and industry. Water quality in terms of drinking is the most important parameter among qualitative parameters. Therefore, the investigation and anticipation of pollution are the goals of managers and planners. In this research, ...
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Wells are one of the main sources of drinking water, agriculture and industry. Water quality in terms of drinking is the most important parameter among qualitative parameters. Therefore, the investigation and anticipation of pollution are the goals of managers and planners. In this research, artificial neural network and geospatial information system have been used to determine the contamination of magnesium parameter in the water of Gonbad villages in Golestan province during the 4 consecutive of 2008, 2009, 2010 and 2011. In this model, the artificial neural network has been evaluated in Perceptron structure with a number of hidden layers and various neurons. At present, pollution of underground is increasing due to the chemical and industrial activities. Therefore, it is necessary to identify vulnerable areas to prevent the pollution of groundwater. Also, in this research, to determine the groundwater contamination, maps such as topography, geology, location of wells, slopes and …, were used in spatial environment. After determining the amount of contamination using the neural network models and the output of the model in spatial environment, the pollution maps were obtained. Also, by observing contamination maps and data available in the aforementioned years, it can be concluded that the level of pollution was low and this pollution cannot be dangerous.
Ali Kalantari Oskouei; Mahdi Modiri; Ali Asghar Alesheikh; Reza Hosnavi
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The main objective of this research was to determine Iran’s National Spatial Data Infrastructures (NSDI) readiness index, with the aim of identifying the basic restrictions that impede NSDI development. The framework of the research is constructed on the basis of survey and SDI readiness ...
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The main objective of this research was to determine Iran’s National Spatial Data Infrastructures (NSDI) readiness index, with the aim of identifying the basic restrictions that impede NSDI development. The framework of the research is constructed on the basis of survey and SDI readiness model. In this research, Iran’s NSDI based on this fuzzy-based model has been assessed using 16 decision-making criteria in the form of five organisational, human resources, data and information, technological and financial factors.The required data for the research were collected through the questionnaire and interview with the experienced experts from the government agencies, Universities, and private sector of the country who were familiar with the spatial data infrastructure. The results of the implementation of the model demonstrated that Iran’s NSDI readiness composite index was 0.44. In addition, the assessment of the factors of Iran’s NSDI readiness showed that all of them, with the exception of the technology factor, were less developed. Moreover, the status of 75% of decision-making criteria was not satisfactory. In this research, the state of investment of the government and the private sector, communication infrastructure, organizational and individual leadership, legal issues, politicians' perspective, metadata, culture and education regarding the spatial data infrastructure were recognized as the most important limiting measures in the establishment of the NSDI. In spite of numerous factors inhibiting the development of NSDI, the status of criteria for connecting to the Web, access to data and digital spatial data, human capital, and access to geospatial software were evaluated at an appropriate level of development. Also, according to the results of this research, it seems that in the development of the NSDI, non-technical issues (organizational, human resources, and financial factors) can play a role as a limiting factor than technical issues (technological factor). At the end of the paper, recommendations have been presented to resolve the country’s NSDI development constraints.
Farzad Foroozani; Mohammad Reza Malek; Ali Esmaeily
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Abstract
The Distribution networks are the most important part of the utilities that distribute electrical energy to the consumers. Problems with location-referenced information such as inaccuracy, inability to control information, and lack of rapid access to information are considered as technical ...
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Abstract
The Distribution networks are the most important part of the utilities that distribute electrical energy to the consumers. Problems with location-referenced information such as inaccuracy, inability to control information, and lack of rapid access to information are considered as technical problems. The complexity of updating information, the complexities related to information storage and wearing out are no exception to this rule. Existing technical problems and the failure to use the new systems in the relief issue will prolong the duration of the blackout. The purpose of this research is to design and implement a context aware spatial information system for providing a series of services such as routing, map displaying, and the provision of distribution network information in the field of urban electricity distribution incidents. Urban electricity distribution networks consist of various parts and equipment. The rescuer determines the type of failure due to available and accessible network information. The failure type is considered as the user's environmental context, and the location of the rescue vehicle is considered as the location context. Therefore, the context in this study are classified into two general categories of position and network context. Finally, the implementation and testing of a designed to help managing the urban electrical distribution networks was studied which resulted in 80% satisfaction.
Seyyed Yaser Hakimdoost; Shahbakhty Rostami; Mahmood Moradi; Abdolhamid Nazari
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The present study is seeking to identify the spatial pattern of habitability of rural settlements in Hirmand’s border regions in order to identify the hazardous areas. The research method in this study is of applied type, and the governing approach to the research is descriptive and analytical. ...
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The present study is seeking to identify the spatial pattern of habitability of rural settlements in Hirmand’s border regions in order to identify the hazardous areas. The research method in this study is of applied type, and the governing approach to the research is descriptive and analytical. In order to analyze the distribution pattern of the habitable villages at three optimal, moderate and undesirable levels spatially, spatial statistics tests will be used in the GEO DATM and GIS software environment to identify the spatial pattern of the habitability of the villages and ultimately the hazardous and vulnerable zones to be identified. The results of the research show that 16 villages are in the optimal, 16 in the moderate and 12 in the undesirable range. Also, the results of using the Moran Anselin’s Algorithm in the region indicate that 7 cold clusters (low habitability) and 11 hot clusters (high habitability) were identified in the region. The largest hot spot is located in the south of the city and the villages located on this spot are highly habitable and adjacent to each other, and the largest cold spot is located in the south-east and center of the city. The results of the study indicate that the villages near the borderline have a weaker habitability and cold clusters are concentrated in these areas, and the rural regions of the northern part of the city are less habitable due to their dependence on the agricultural economy and the shortages of resources of the Hamoon’s Abūroud in the north of the city. Hazardous spots from the unstable situation of rural settlements perspective can endanger the region from the security aspect, and consequently, habitats with more appropriate habitability located in the vicinity of the spots with low habitability will also be endangered in terms of security and will eventually overwhelm their habitability.
Seyyed Eskandar Seydaei Seyyed Eskandar Seydaei; Seyyedeh Somayeh Hosseini
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Abstract
In the sustainable tourism development approach, not only market needs are considered, but also the needs of society and the natural environment are emphasized. In this regard, GIS can be used for many tourist, planning and modeling activities. The present study aimed to provide a model for ...
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In the sustainable tourism development approach, not only market needs are considered, but also the needs of society and the natural environment are emphasized. In this regard, GIS can be used for many tourist, planning and modeling activities. The present study aimed to provide a model for access to tourist attractions for the sustainability in tourist hubs of Isfahan province. Regarding the studied components, this research is an applied one in terms of type and a descriptive-survey in terms of method. This research was conducted based on the closest access considering the speed of access (road quality) in terms of minutes, and in order to provide a model for the stability of areas with the highest attraction and concentration of tourist in a zone rather than a point. The cities of Isfahan and Kashan (historical-cultural) and the cities of Semirom and Fereydoon Shahr (natural tourism) have the highest tourist capacity in the province, respectively. The results of the study show that according to the "Closest Access" model, five classes have been taken into consideration for the sustainability of the four tourist hubs in the province. The first class covers the potential rural and urban locations to a 60 minute radius (according to experts, the 60 minute distance is the distance that the tourists tend to travel by car on the way to the desired attraction) from the natural tourist hubs, the West (Fereydoon Shahr), the Southwest (Semirom) and the historical-cultural tourist hubs of Isfahan and Kashan which should be addressed by the authorities and tourism planners of the province to instruct tourists.
Reza Aghataher; Mahdi Samadi; Ilia Laliniat; Iman Najafi
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Digital Elevation Models (DEM) enable researchers to perform geographical researches on a global and regional scale such as global changes, natural disasters, environmental hazards, environmental monitoring, etc. Therefore, DEM data plays a key role in scientific researches. SRTM and ASTER ...
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Abstract
Digital Elevation Models (DEM) enable researchers to perform geographical researches on a global and regional scale such as global changes, natural disasters, environmental hazards, environmental monitoring, etc. Therefore, DEM data plays a key role in scientific researches. SRTM and ASTER GDEM are two elevation datasets that cover nearly the entire land surface of the earth and are globally available (for almost 80% of the earth). Thus, it is necessary to evaluate the vertical accuracy of such data prior to their use and to select the appropriate data considering the research target. ASTER-based digital elevation model has spatial resolution of 30 meters, which seems to provide more precise elevation data than SRTM with 90 meters spatial resolution. Several studies have been performed for evaluating the accuracy of each of these two datasets in various countries of the world. The results of such studies indicate their advantages and limitations over each other. In this study, the vertical accuracy of these two DEMs are evaluated by ground control point in three zones of Iran with different topographic characteristics which are East Azerbaijan, Sistan and Baluchestan and Bushehr. Results show that the RMSE of SRTM as the index of error for the study area in East Azerbaijan, Sistan and Baluchestan and Bushehr are 6.1, 7.4 and 2.9 meters and in ASTER GDEM are 8.7, 8.3 and 7.2 meters respectively. Therefore, the vertical accuracy of STRM is higher than that of ASTER GDEM in all three zones. In this research, the relation between vertical error and land characteristics including slope and direction of slope has been studied and the results have been presented. The final findings of the research indicate higher vertical accuracy for SRTM compared to ASTER GDEM in Iran and it is concluded that SRTM is a more appropriate choice for various applications.
Ali Akbar Damavandi; Mohammad Rahimi; Mohammad Reza Yazdani; Ali Akbar Noroozi
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Abstract
Drought is a natural phenomenon that occurs in almost all climates of the world. The effects of this creeping and gentle phenomenon are higher in arid and semi-arid regions due to their less annual rainfall. In the present research, in order to monitor the location of drought, time series NDVI ...
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Drought is a natural phenomenon that occurs in almost all climates of the world. The effects of this creeping and gentle phenomenon are higher in arid and semi-arid regions due to their less annual rainfall. In the present research, in order to monitor the location of drought, time series NDVI ((Normalized Difference Vegetation Index)) and LST (land surface temperature) of the Terra satellite’s MODIS (Moderate Resolution Imaging Spectroradiometer) sensor were used during the growing seasons (March, 21 to September, 21) of the years 2000 to 2014 in Markazi province. For this purpose, the VCI (Vegetation Condition Index) and TCI (Temperature Condition Index) indices were created on a monthly basis based on the NDVI and LST 15-year time series, and the VHI (Vegetation Health Index) index was extracted based on the combination of the two indices. As a result, drought severity maps based on the VHI index were extracted in five categories: 1- Very severe 2- Severe 3- Moderate 4- Mild 5- no drought, and variations of these classes were investigated in VHI time series. A review of time series resulted from VCI and TCI showed that there was a meaningful relationship between NDVI and LST variations. According to the results of drought severity classification maps, VHI index had the highest drought intensity in the years of 2000 and 2001 and the years of 2004 and 2007 had the lowest drought severity. Also, the highest and the lowest drought severity were observed in May and September, respectively. The highest percentage of the areas of drought classes belonged to drought-free (56%), mild (19%), moderate (15%), severe (8%) and very severe (2%). Comparing the results of this research and the report of the Meteorological Organization shows the high precision of the method of using the VHI remote sensing index in agricultural drought monitoring. The result is that, remote sensing indicators of drought monitoring (such as VCI, TCI and VHI) can greatly help decision-makers and planners in monitoring agricultural drought by eliminating the weaknesses of point-based approaches.
Mohammad Zeinali; Ali Asghar Jaafarzadeh; Farzin Shahbazi; Shahin Oustan; Khalil Valizadeh Kamran
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Abstract
Soil salinity and salinization of lands as one of the problems facing agriculture, has paramount importance and should be avoided with proper knowledge of its progress. The first step in this way is to identify saline areas and prepare the salinity maps for these soils. With the development ...
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Abstract
Soil salinity and salinization of lands as one of the problems facing agriculture, has paramount importance and should be avoided with proper knowledge of its progress. The first step in this way is to identify saline areas and prepare the salinity maps for these soils. With the development of remote sensing technology and efficient use of satellite imaging, this research aimed to compare the prepared salinity maps with various types of image classification algorithms (Maximum probability, Minimum distance from the mean and Parallelepiped) by Landsat-5 satellite data with TM sensor in a part of the eastern lands of Khoy city. Therefore, 269 soil samples were analyzed with specific geographic coordinates and the results were plotted on TM image. For initial identification, topographic maps and ENVI 4.8 software were used to process satellite images and geometric corrections were made with specific points using GPS. Educational and experimental samples were located on the desired image with an appropriate distribution and salinity classes were determined from 1 to 9. Samples of each class of salinity due to having coordinates were placed accurately and with single pixel size in each image on the corresponding pixel and were stored with ROI format. The results indicate the existence of correlation between bands 1, 4, and 5 of TM image with salinity data, and the highest accuracy of the map among the classification algorithms in the Pixel-based method, is related to the maximum probability. In order to evaluate the accuracy, indices such as error matrix, Producer’s veracity, User’s authenticity, overall accuracy, and kappa Coefficient were extracted. Also, the correspondence of various salinity classes of this map with field observations and measured salinity level indicate the high accuracy of this algorithm in preparing a surface soil salinity map. The aim of the present study is to compare the prepared salinity maps with the results of other researchers by these methods in the area of interest.
Hossein Mohammadi Hossein Mohammadi; Ghasem Azizi; Faramarz Khoshakhlagh; Mahdi Khazaei
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Abstract
Accurate and timely estimation of evapotranspiration has a significant and critical impact on the planning of water resources and agriculture. In this research, the estimation of evapotranspiration of sugarcane in Khuzestan province has been studied, and the data used, have been air temperature, ...
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Accurate and timely estimation of evapotranspiration has a significant and critical impact on the planning of water resources and agriculture. In this research, the estimation of evapotranspiration of sugarcane in Khuzestan province has been studied, and the data used, have been air temperature, relative humidity, wind speed and sunny hours since the establishment of synoptic station until 2014. For this purpose, the evapotranspiration values of the reference plant were first calculated using the FAO Penman-Monteith standard method and then, using available plant coefficients, the amount of sugarcane evapotranspiration was estimated at different stages of growth. The results of this study show that the average sugarcane evapotranspiration in Khuzestan province has been 3.35 mm / day in June and in the early stages of growth, 10.46 mm/day in the middle stages of growth, and 6.26 mm / day in the final stages of growth. The value of this parameter in July was estimated 3.59 mm/day in the early stages, 11.23 mm/day in the middle stages and 6.74 mm/day in the final stages of growth. Finally, the amount of evapotranspiration of sugarcane in August was estimated 3.56 mm per day in the early stages of growth, 11.12 mm/day in the middle stages and 6.67mm per day in the final stages of the growth. The maximum daily and monthly evapotranspiration has occurred in July and the minimum in June. Also, the highest daily and monthly fluctuations of sugarcane evapotranspiration have occurred in the middle stages of growth and the lowest in the early stages of growth.
Parham Pahlavani; Mahdi Hasanlou
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Nowadays, the combination of data and images obtained from different remote sensing sources is considered as an optimal solution for extracting more information, since these data, with their own wide vision, digital format, their periodically preparation, and high temporal resolution provide ...
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Nowadays, the combination of data and images obtained from different remote sensing sources is considered as an optimal solution for extracting more information, since these data, with their own wide vision, digital format, their periodically preparation, and high temporal resolution provide researchers with a variety of information about the land surface. In this regard, the passive optical sensors are widely used in mapping horizontal structures. Given that, radar data can often be collected 24-hours a day and Independent of atmospheric conditions, and also some ground structures and artificial targets have a specific response in the radar frequency, they complete the capabilities of optical images. LiDAR airborne data can also provide sample measurements from vertical structures with very high accuracy. As a result, the simultaneous use of optical, radar and LiDAR data can provide more information in a variety of applications. In this research, by simultaneously applying these three categories of data, we tried to identify the urban specific features in an optimal way. In this regard, by utilizing and producing various descriptors (57 descriptors), and using the feature extraction methods (including PCA and ICA) and estimating the intrinsic dimensions of the data (including SML and NWHFC), an optimal space for the supervised classification was created. After classifying (K-NN method) using the obtained results, descriptors (information layers) produced to identify specific urban features including buildings, roads and vegetation were obtained and grouped according to the classification accuracy. The numerical results indicate the high efficiency of the proposed procedure as well as the applied methods of estimating intrinsic dimension and extracting the features.
