M Shakeri; F Mirzapour; A Darvishi Boloorani; S.K Alavi Panah
Volume 8, Issue 1 , November 2016, , Pages 55-70
Abstract
Satellite image fusion and creating data with spectral and spatial capabilities greater than those of the existing data is of special interest and position in Remote Sensing. However, the accuracy and efficiency of all processing stages of using these data depend on the precision and reliability of the ...
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Satellite image fusion and creating data with spectral and spatial capabilities greater than those of the existing data is of special interest and position in Remote Sensing. However, the accuracy and efficiency of all processing stages of using these data depend on the precision and reliability of the produced data. The optimum utilization of fused images relies, ultimately, on the precision of the employed fusion method. Evaluation of this important aspect requires selection of an optimum assessment metric which is appropriate for the objectives and application areas of fused images. Different application areas such as, natural resources, civil areas and etc. have different preferences with regard to maintaining the spectral and spatial data. Therefore, selection of the best fusion method, that is appropriate for the application area of the image, through image quality assessment metrics is one of the users’ challenges in this field. The present paper, thus, attempts to provide an analysis and assessment of 20 common image quality assessment methods so as to identify and introduce the most optimum metrics based on the area of application of fused images. It also tries to introduce the factors causing differences in the way quality is assessed by the metrics. And then present a model for identifying the capabilities of each metric for displaying the distortions that occur in the spectral and spatial aspects of data. To this end, two metrics of high-pass filter and spectral angle mapper are taken into consideration as spectral and spatial data comparison bases, and the performance of metrics with regard to their assessment of the quality of simulated data, that contain images with controlled spectral and spatial distortions, is evaluated. Spectral distortions were introduced by high-pass filter effect, band displacement and changing color tone. Low-pass filter and attrition filters with structural elements of different dimensions were also used for introducing spatial distortions. Due to offering different spectral and spatial resolutions, images from Landsat8, EO-1, and Worldview satellites were used. Pieces with different land applications were cropped from these images to serve as test images. The assessment of the metrics tested on these images resulted in the categorization of metrics into three groups as per their capability for displaying spectral and spatial distortions. The first group included methods that functioned on the basis of noise for overall assessment of images with respect to their noise; these methods included ERGAS, MSE, PSNR, WSNR, and SNR indices. The second group were those aligned with Spectral Angular Mapper method that are suitable for assessment of images with sensitive applications as they display the spectral distortions with greater precision; These methods include BIAS, RASE, Q, MSSIM, NQM, FSIM, SRSIM, and SAM indices. The third group is also compatible with high-pass filter of HPF, RFSIM and MAD that are of a greater capability for displaying spatial distortions.
Maedeh Behifar; a.a Kakroodi; Majid Kiavarz; Farshad Amiraslani
Abstract
Drought is one of the most important natural disasters in the country, with devastating environmental and economic effects. Most drought studies have focused on drought severity and other drought characteristics have not been usually investigated. In this research, for the first time, the capability ...
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Drought is one of the most important natural disasters in the country, with devastating environmental and economic effects. Most drought studies have focused on drought severity and other drought characteristics have not been usually investigated. In this research, for the first time, the capability of meteorological drought indices and satellite data are combined and applied to study drought in inland and coastal basins. For this purpose, the SPI index was calculated by using TRMM satellite precipitation products and then, the drought characteristics such as severity, duration, magnitude, and extent were spatially studied. The results showed that the correlation coefficient between the SPI calculated from the image and the station data was 0.94. The maximum intensity of drought in the study area was -4.19 which occurred in December 2010. Furthermore, the frequency of extreme droughts in 6- and 12-months timescales was higher in the inland area compared with the coastal area. Moreover, in the six-month timescales, 60 percent of drought events had a magnitude of -18.3 or less. The results showed that it is possible to obtain the extent of drought by using satellite imagery which cannot be calculated by other methods. Besides, by using satellite images, drought characteristics could be studied spatially at the basin scale, which is not possible by traditional methods. The results showed the advantage of using satellite precipitation images in the drought study
Zohreh Salehinezhad; Seyed ali Almodaresi
Abstract
Construction violations are considered one of the most important challenges of modern urbanization due to their widespread level and long-term and stable effects on the profile of cities. Construction violations are an important issue for municipalities that can threaten building structures in a city. ...
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Construction violations are considered one of the most important challenges of modern urbanization due to their widespread level and long-term and stable effects on the profile of cities. Construction violations are an important issue for municipalities that can threaten building structures in a city. The traditional methods that are used today to control constructions are very time-consuming and expensive. The main goal of this research is to provide a new framework for quick and low-cost estimation, in revealing and monitoring constructions and identifying unauthorized urban buildings using Sentinel-1 satellite images in the period from 2017 to 2022 and spatial information systems. For this purpose, in the first step, based on the analysis and processing in SNAP software, the Sigma-Notch dispersion coefficient of the images was extracted and separated into two floors of buildings and non-buildings, and a threshold limit of more than 0.01 was obtained. Then, by using pixel based algorithm, the binary image of building and non-building was prepared as zero and one, and based on the difference between the two images, the area where the construction was done was determined. After revealing the changed construction areas, they were classified into three classes (building, under construction, and other lands) using maximum likelihood classification algorithms and random forest, and were evaluated with a field survey map and unlicensed parcels. The results showed that the number of unlicensed buildings using the maximum likelihood algorithm, random forest and field sampling is 97,135 and 48, respectively; Also, the accuracy of the maximum likelihood method was 0.89% and the kappa coefficient was 0.83% compared to the random forest method with the overall accuracy of 0.86 and the kappa coefficient was 0.81%.
F Foroughnia; S Nemati; Y Maghsoudi
Volume 10, Issue 1 , June 2018, , Pages 57-72
Abstract
Tehran is subject to high-rate subsidence because of extravagant water extraction. Groundwater extraction in Tehran plain due to agricultural or industrial activities has made it always be at risk and probable incoming damages. Large spatial baselines and temporal de-correlation have always limits the ...
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Tehran is subject to high-rate subsidence because of extravagant water extraction. Groundwater extraction in Tehran plain due to agricultural or industrial activities has made it always be at risk and probable incoming damages. Large spatial baselines and temporal de-correlation have always limits the use of the conventional SAR interferometry for the purpose of subsidence monitoring in regions with high deformations velocity. Therefore, in this research, the InSAR technique based on persistent scatterer (PS) is carried out to analyze Tehran subsidence. The main objective of this paper is to determine the average annual subsidence rate of some urban regions in Tehran using a time series of Sentinel-1A (S-1A) and ENVISAT-ASAR data. PS pixels remain coherent in long spatio-temporal intervals and thus less affected by the lack of radar images correlation. However, inappropriate temporal distribution of data in this technique makes it difficult to derive the absolute value of the phase due to an integer ambiguity. Therefore, the use of S-1A dataset with short temporal baselines would help identify the phase ambiguity. Results prove considerable subsidence in southern part of the case study area for all-time series analysis which further proves the arrival of subsidence to urban parts. Results are cross-validated using the different image tracks and besides, absolute validation are employed on subsidence velocity maps based on precise leveling and GPS observations.
Volume 7, Issue 1 , December 2015, , Pages 59-79
Abstract
Optimizing of the arrangement of the land uses is one of the main goals of urban land use planning. This issue involves a variety of spatial data and analyses. Moreover, existing different arrangements for diverse land uses causes in complex and wide search space. In view of these matters, the land use ...
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Optimizing of the arrangement of the land uses is one of the main goals of urban land use planning. This issue involves a variety of spatial data and analyses. Moreover, existing different arrangements for diverse land uses causes in complex and wide search space. In view of these matters, the land use arrangement can be supposed as a spatial multi-objective optimization problem. In this research, Multi-Objective Particle Swarm Optimization algorithm along with GIS is applied in the seventh distinct of Tehran to find optimum arrangement of urban land uses. GIS is used to generate and analysis different scenarios of land use arrangements for the optimization algorithm. The proposed approach provides a variety of optimized solutions, giving the possibility of choosing the most desirable results to decision-makers. A new aspect of this research is using the land parcels as the spatial unit. In addition, making dynamic decision on the different types of land uses is one advantages of this method. The test of the method shows an acceptable level of implementation speed along with a high level of repeatability and stability of the algorithm. Keywords: Optimization, Land use planning, GIS, MOPSO, Multi-Objective, Micro Scale, Decision making.
T Managhebi; Y Maghsoudi; M.J Valadan Zoej
Volume 9, Issue 4 , May 2017, , Pages 59-72
Abstract
This paper provides an advanced method to improve results of three stage inversion algorithm using polarimetric synthetic aperture radar interferometry (PolInSAR) technique based on Random Volume over Ground model. In conventional three stage method, the ground phase, extinction coefficient and volume ...
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This paper provides an advanced method to improve results of three stage inversion algorithm using polarimetric synthetic aperture radar interferometry (PolInSAR) technique based on Random Volume over Ground model. In conventional three stage method, the ground phase, extinction coefficient and volume layer is estimated in a geometrical way without the need for a prior information or separate reference DEM. The extinction and volume height estimation is done in the third stage by searching in the two dimension area. In the proposed algorithm, defining a new geometrical index, based on signal penetration in the forest, imposes a limited range for the extinction coefficient. The new index, as an axillary data, help search in a more appropriate space. The proposed algorithm was applied on L-band ESAR single baseline single frequency polarimetric SAR interferometry data. As a result of applying this restriction in the extinction range, a 2.5 meter improvement was observed in the RMSE of proposed algorithm compared to the three stage method.
Moein Molavi; Mohammad Taleai; Gasem Javadi
Abstract
Finding the optimum location of wind turbines for the proper use of wind energy, as one of the sources of renewable energy, is very important. Determining the location of wind turbines has a great influence on the efficiency of their equipment. So far, research in the Khorasan Razavi area has limited ...
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Finding the optimum location of wind turbines for the proper use of wind energy, as one of the sources of renewable energy, is very important. Determining the location of wind turbines has a great influence on the efficiency of their equipment. So far, research in the Khorasan Razavi area has limited to the statistical analysis of wind speed and directional data while the spatial criteria affecting finding the optimum location of wind turbines was rarely considered. This research seeks to find optimum location for the wind power plant using environmental (including slope, altitude, distance from the fault, distance from the river, distance from protected areas), technical (including average wind speed, wind congestion and wind density), and economic (including distance from the city, the village, the airport, the natural resources and from the road) criteria and using ANP, ANP-DEMATEL and ANP-OWA multi-criteria decision-making methods. The aim is to evaluate the results of each method and produce a land suitability map for the construction of wind power plants in different decision scenarios. Based on this, using the analysis tools of the geospatial information system, the land suitability map is produced based on the aggregation of the mentioned criteria and the results of utilizing the mentioned decision-making methods are compared. By considering land suitability maps, it has been determined that in different scenarios of decision making, the southeastern province has the most potential for wind power plant construction. The results of this research indicate that the proposed method provides a good tool for choosing the right place to build a wind power plant.
Mahmoud Ahmadi; zahrasadat seyedmirzaei
Abstract
The study of snow cover as one of the most important sources of freshwater supply is of great importance. Due to the mountainous conditions of Iran, it is not possible to measure the area of snow cover. Accordingly, the use of satellite imagery to identify snow storage is of great importance. In this ...
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The study of snow cover as one of the most important sources of freshwater supply is of great importance. Due to the mountainous conditions of Iran, it is not possible to measure the area of snow cover. Accordingly, the use of satellite imagery to identify snow storage is of great importance. In this study, the spatio-temporal changes of Iran snow cover for the cold period of the year were evaluated using the snow cover product of MODIS Terra satellite during the period of 2003-2018. The trend and slope of the snow cover were investigated using Man-Kendall non-parametric tests and the Sen's slope estimator and change-point of snow cover using Buishand test. The results showed that in January, the highest amount of snow cover is 16.6 percent, and the lowest amount of snow cover was computed in October, which is less than 1 percent. The main center of Iran's snow cover in the cold period of the year in the highlands is above 4000 meters. The snow cover trend is negative in all studied months and the maximum decrease in snow cover was calculated in January and the change-point was calculated in 2008 January, which is statistically significant at the level of 0.05. The significant decrease in snow cover during the cold period of the year which is a major threat to Iran's water resources.
V Ahmadi; A Alimohammadi; J Karami
Volume 9, Issue 2 , December 2017, , Pages 61-78
Abstract
Management and planning of urban water supply in metropolis is very important. Development of the region urban and make cities to metropolis and increase of effective complex factor on water usage in the cities make consumption management and supply and distribution Water difficult. So rule extraction ...
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Management and planning of urban water supply in metropolis is very important. Development of the region urban and make cities to metropolis and increase of effective complex factor on water usage in the cities make consumption management and supply and distribution Water difficult. So rule extraction plays an important role in exploring patterns over data and decreasing complex. Rough Set Algorithm, which was developed in 1980s by Pawlak, is a powerful and flexible method to deal with uncertain and ambiguous data which has been used in this research to extract dominant rules over data set. The method used in this paper is combination of the rough set and genetic algorithms from data mining methods to develop rule extraction and data classification of water usage in Tehran city as the studying area. Socio-economic, environmental, time and water consumption and management zones have been used as the explanatory variables for prediction of the water use that database divided to 2 part 60% for result extraction and 40% as test set. Independent test sets have been used for evaluation of the accuracy of the extracted rules. Results have shown that, combination of the genetic algorithms and Rough Set leads to extraction of more reliable rules. Classification accuracy of the extracted rules from Rough sets was 77 percent. But optimization of rules by combination of the genetic algorithm with Rough sets, resulted in classification accuracy of 88 percent in 6th generation with average speed of convergence. By using the same speed of convergence in the accuracy increased to 92 percent in 10th generation. According to the extracted rules, important effective factors on annual water consumption are respectively the resident population, water price, population density, family size, spatial location (latitude), education levels, and per capita green spaces.
Mahdi Fahmideh Modami; Masoud Ayaz; Ahmad Alajeh Gardi; mahdi javanshiri
Abstract
The dramatic increase in construction in recent decades has been accompanied by an increase in the number of construction violations in urbanized areas and has overshadowed the urban management and planning system, so preventing unauthorized urban construction is one of the main problems of city managers. ...
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The dramatic increase in construction in recent decades has been accompanied by an increase in the number of construction violations in urbanized areas and has overshadowed the urban management and planning system, so preventing unauthorized urban construction is one of the main problems of city managers. The current method of controlling construction violations includes field inspections based on human knowledge, which in addition to the need to spend exorbitant financial, time and human resources, may lead to collusion between builders and municipal inspectors or even failure to identify construction violations in a timely manner. In this regard, providing an intelligent and accurate method for identifying construction violations and targeting the search for construction patrols is more than necessary. The aim of this study is to provide an intelligent strategic model in monitoring violations. The present research is applied in terms of purpose and descriptive and causal in terms of method and the data has been collected by library and field methods. The results of this study indicate that by using the intelligent monitoring system, it is possible to intelligently monitor illegal constructs by processing the required image and data techniques, with the least presence of human agents and in a shorter time. The overall accuracy of 94% and the kappa coefficient of 71% for image classification in this system confirm the accuracy of the above results. It shows that in this method, the speed and accuracy of image classification, identification of changing buildings and identification of illegal constructions are much higher than physical and existing methods.
Majid Hashemi Tangestani; Samira Shayghanpour
Abstract
The specific capabilities of satellite data in providing information from the Earth surface materials provide a possibility for producing the geological maps, and in this regard, the spatial and spectral resolutions of the utilized data are two fundamental characteristics in determining the precision ...
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The specific capabilities of satellite data in providing information from the Earth surface materials provide a possibility for producing the geological maps, and in this regard, the spatial and spectral resolutions of the utilized data are two fundamental characteristics in determining the precision and accuracy of the maps. In this research, the data sets of ASTER and Sentinel 2, due to their high spatial and spectral resolutions, were used to enhance the lithological units of the Sureyan complex, northeastern Fars. The metamorphosed sedimentary-volcanic complex of Sureyan is part of the Southern Sanandaj- Sirjan Belt, in Bavanat, Fars province. Investigating the spectral features of field samples, measured at the Shahid Chamran University of Ahvaz, and the spectra extracted from the imageries indicated that the main functional groups responsible for spectral features were Fe2+, Fe3+, OH, CO3, Al-OH, Mg-OH, and Fe-OH. Based on the mineralogical studies, these groups could be attributed to the occurrences of chlorite, muscovite, epidote, amphibole, calcite, and hematite, which were approved by studies of microscopic thin sections. The band ratios (6+8)/7, (7+5)/6, and (6+9)/(7+8) were conducted on 9 reflection bands of ASTER, and the principal components analysis, on 9 reflection bands of ASTER and Sentinel-2. These processing methods were successful in discriminating the chlorite-epidote schist, calk-schist, mica-schist, and the basalt and quartzite dykes as well. Comparing the results of this study to the field observations and the results obtained by laboratory investigations revealed that simultaneous use of ASTER and Sentinel-2 data and the applied processing methods could be successful in discriminating the lithological units of a metamorphic-sedimentary-volcanic complex.
Matin Shahri; Afshin Shariat Mohaymany
Abstract
Analyzing traffic conditions and suggesting traffic management methods play a critical role in evaluating the effectiveness of transportation systems. Among the methods suggested for collecting traffic data, approaches based on new technologies attracted more attention due to the ability of collecting ...
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Analyzing traffic conditions and suggesting traffic management methods play a critical role in evaluating the effectiveness of transportation systems. Among the methods suggested for collecting traffic data, approaches based on new technologies attracted more attention due to the ability of collecting large amounts of dynamic spatio-temporal data making it easy to identify trends and patterns. In this study, Tehran, the capital of Iran with socio-economic characteristics and the variety of urban trips which lead to heterogeneous traffic state will be considered. Data obtained from digital processing of Google Maps traffic images the one-month time interval (April 7th to May 7th, 2017), has been applied for the first time to evaluate the trend and overall pattern of the changes in traffic congestion in the study area. Considering the variety of trip patterns and consequently the traffic congestion, traffic congestion index (CI) has been calculated on workdays and weekends separately and was assigned to the district center and the morning and evening peak-hours were extracted using descriptive analysis. By applying Getis-Ord hot-spot and cold-spot index, the clusters of congested areas have been recognized over the study area. Also, the temporal relationship between traffic congestion indexes in different time sections was evaluated using Kruskal-Wallis statistical test and the null hypothesis of correlation between the mean values of congestion index was confirmed. Using overlay analysis of congestion maps, clusters indicating congested areas at 90% confidence intervals were extracted during morning and evening peaks on weekdays and weekends separately. The results of this study can be effective in modifying traffic congestion zones, analyzing pollution or studies relating to road pricing, and assessing the process of traffic congestion propagation during desired time intervals.
Fateme Firozi; Taghi Tavosi; Peyman Mahmoudi; Seyed Mahdi Amir Jahanshahi
Volume 10, Issue 4 , February 2019, , Pages 69-84
Abstract
The radative energy balance received and returned from Earth planet reflects the energy available in each part of the Earth-Atmosphere system. Also, net solar radiation is the most fundamental driving force for evaporation, and all actions and reactions between the Earth's surface and the atmosphere. ...
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The radative energy balance received and returned from Earth planet reflects the energy available in each part of the Earth-Atmosphere system. Also, net solar radiation is the most fundamental driving force for evaporation, and all actions and reactions between the Earth's surface and the atmosphere. These reactions significantly affect the climate and its transformations. Hence, the wide-scale cross-sectional estimation of pure net energy is important in terms of global and regional climate models. In this research, in order to study the trend of long-term monthly average changes of surface-Albedo, the Albedo products from the sensors of MODIS Satellite Terra named MCD43B3were used. The spatial resolution of the images taken was 1×1 km for a 15-year statistical period (2000-2014) for April, May, and June. After capturing images by NASA's land processes distributed active archive center, all 45 downloaded images. The next step was to convert the image format to ASCII format; each ASCII includes 30080 pixels. Finally, by using both statistical methods of Sen's slope estimator, and Classic Linear Regression the trends of long-term monthly average Albedo changes were analyzed on a pixel-based scale. The results of these two models showed that these two models did not differ in their estimation of the trends of Albedo's average changes, and acted precisely the same. Also, the results of this research showed that the center of the most slowly declining slope of Albedo changes is located in the northeast, where, due to the flow of the Hirmand River, in this part of the plain the agriculture is widespread. The incremental magnitude of the slope of the change process is also very limited, and there are small and large spots in the north, northeast, and center of the plain. This increasing trend in the values of Albedo's index in the north of the plain was exactly the same as the drying of the Hamoon triple lakes. The rest of the plain area, which has desert landscape and does not have any vegetation, as well as any human population, has not shown any particular trend. In this study, it was also clearly found that, the use of nonparametric method of Sen's slope estimator and parametric method of classic linear regression can be very effective in studying the trend of Albedo changes in the arid regions resulted from satellite products of MADIS sensors
Nastaran Nazariani; Asghar Fallah; Habibolah Ramezani Moziraji; Hamed Naghavi; Hamid Jalilvand
Abstract
Gathering accurate information for statistics requires high cost and precision. The time factor is also one of the important issues that should be seriously considered in statistics. Therefore, the use of sampling methods and satellite images will be a good alternative for this purpose. In the present ...
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Gathering accurate information for statistics requires high cost and precision. The time factor is also one of the important issues that should be seriously considered in statistics. Therefore, the use of sampling methods and satellite images will be a good alternative for this purpose. In the present study, the aim of the effect of different cluster sampling schemes in estimating the quantitative characteristics of the traditional forests of Olad Ghobad in Koohdasht township, Lorestan province using Sentinel 2 sensor images. To estimate the studied characteristics, 150 clusters in the form of six designs (triangular, square, star 1, linear, L-shaped, star 2) were implemented in the region. Then, in each subplot, the characteristics of the number and area of the tree canopy were measured. Afterimage preprocessing and appropriate image processing (principal component analysis, texture analysis, and different spectral ratios to create important plant indices), the corresponding digital values of the ground sample plots are extracted from the spectral bands and used as independent variables. Modeling was performed using nonparametric methods of random forest, support vector machine, and nearest neighbor. The results showed that the average density per hectare was 51 and the canopy area was 32.94%. The diagram of the mean squares of the error of the training and test data against the number of trees for the characteristic number per hectare and canopy showed that the optimal number of trees was obtained at approximately 75 and 350 points. The results of validation according to the percentage of squared mean squared error showed that for both density and canopy surface characteristics of random forest algorithm with linear and double star sampling designs with the squared percentage of mean squared error respectively (46.00%) and (10.44%) and Bias (-0.02%, 2.82%) along with cluster sampling designs linear and double star, respectively, had better performance in modeling. In general, the results showed that the use of different cluster sampling schemes, nonparametric modeling methods, and Sentinel2 sensor images can better performance estimate the quantitative characteristics of Zagros forests.
parviz panjehkoobi; mohammad jrayahni parvari; mehdi javardi; mohammad reza rahmannia
Abstract
In this study, meteorological radar images were used to calculate intensity - amount and distribution of precipitation. Spatial resolution of 500 m radial and temporal resolution of 15 min were calculated. Floods in three basins of Sermo, Zrinigol and Ramian were studied. Results showed that intensity, ...
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In this study, meteorological radar images were used to calculate intensity - amount and distribution of precipitation. Spatial resolution of 500 m radial and temporal resolution of 15 min were calculated. Floods in three basins of Sermo, Zrinigol and Ramian were studied. Results showed that intensity, duration and location of precipitation determined the amount of runoff in the basin. Flood time differed with the concentration and maximum runoff time of the basin. Investigating the radar images revealed that the maximum runoff in addition to the sum of precipitation on the basin was also dependent on the distribution of precipitation. If the sum and distribution of precipitation were consistent, intensity of flooding was significantly increased, if intensity and sum of precipitation were inconsistent, flood intensity was lower. Maximum runoff time was different in each basin depending on location of rainfall intensity and the distribution of rainfall. The results showed that use of radar data was more accurate than experimental methods to predict flood and maximum runoff.
Volume 6, Issue 1 , April 2014
Abstract
Nowadays, urban land use and land cover information at the micro and macro levels of planning have a particular importance. So many researches have not been done in land use information extraction. Remote sensing as an inexpensive and fast method, and particular with appearance of object-based analysis, ...
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Nowadays, urban land use and land cover information at the micro and macro levels of planning have a particular importance. So many researches have not been done in land use information extraction. Remote sensing as an inexpensive and fast method, and particular with appearance of object-based analysis, has an appropriate potential for this. In this paper, the aim is land use information extraction on a dense and complicated urban area. For this purpose, a hierarchical system inclusive land cover and land use levels has been used. After the implementation of a step by step land cover classification approach, land use unites extraction are done. In the next stage, feature space inclusive more than 50 conceptual features based on land cover information is designed and extracted. After this stage, optimized features among these features with high separability using SFFS are extracted. Finally a fuzzy nearest neighbor classification for land use classification based on optimized is implemented. Land use classification is performed on two combined and uncombined class system that combined class is recognized as most appropriate class system. In the present approach without considering area criteria of land use object, 82% overall accuracy and with this criteria 85% overall accuracy is achieved.
Volume 6, Issue 2 , August 2014
Abstract
Evaluation of snow storage is of high importance in water balance studies and optimum operation of water resources in arid and semi-arid regions like Iran. Particularly in the river basins nearby Zagrous Mountains where surface water flows mainly consist of spring runoffs, stochastic forecasting of the ...
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Evaluation of snow storage is of high importance in water balance studies and optimum operation of water resources in arid and semi-arid regions like Iran. Particularly in the river basins nearby Zagrous Mountains where surface water flows mainly consist of spring runoffs, stochastic forecasting of the snow storage at the end of the year is necessary. In this study stochastic forecasting of snow in river basins of the Karkheh, Dez, Karun and some parts of the Marun was investigated using the first order Markov Chain model. Snow cover data retrieved from NOAA-AVHRR satellite images between 1989 and 2004 were applied as inputs to the model. Two possible states were defined for each snow cover map including existence (1) and non-existence (0) of snow. Through applying the Markov Chain process, snow cover maps of the study area were predicted for March 2000 to 2004. Results show that stochastic forecasts of snow cover properly consist with satellite derived maximum snow cover maps.So that, not only the area of snow covered lands was successfully estimated, but also the exact location of the snow or dry covers was appropriately predicted in more than 80% of the pixels. The performance of the model was assessed using contingency tables and three measures including: Probability of Detection, False Alarm Ratio and Critical Success Index. Results reveal the promising capability of the first order Markov Chain model to forecast snow covered area. Keywords: Snow Probability, First-Order Markov Chain, State Transition Matrix.
Volume 6, Issue 4 , October 2014
Abstract
A primary uses from Iran rangelands is livestock grazing and the major livestock is sheep. Sheep grazing on the slopes above 60%, because of using a lot of energy for grazing operation, caused to not only reduces livestock performance but also increases the risk of erosion. Sheep grazing in an area where ...
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A primary uses from Iran rangelands is livestock grazing and the major livestock is sheep. Sheep grazing on the slopes above 60%, because of using a lot of energy for grazing operation, caused to not only reduces livestock performance but also increases the risk of erosion. Sheep grazing in an area where more than five kilometers away from water sources, due to the prolongation of the march route will reduce performance. Water point dispersion is one of the important factors in rangeland suitability determination. According to the above is required in each rangeland to determine suitability of water for livestock. The study area is located in 50˚ 36´ to 50˚ 53´ east longitude and 36˚ 05´ to 36˚ 19´ north latitude, in Taleghan (Alborz Province), with the area 37977 hectares. Data analysis was performed on the raster model using ILWIS software. Water sources model organize from Quantity of water, quality of water and accessibility to water points sub-models. Results of water sources suitability model showed that 19989 hectares of the area contained good suitability (S1), 1229 hectare classified as moderate suitability (S2), and 4338 hectare located in not usable (N) order, were not part of the Rangeland included low suitability (S3). The steep slope of the study area is the main limiting factor of sheep grazing suitability in the mountainous areas. Recommended in offering the solutions to reclamation and improvement of rangeland noted to decreasing and limiting factor of water sources suitability, and betterment actions to resoling the decreasing factor of rangeland suitability will be done. Keywords: Rangeland, Water source, Sheep, GIS.
Volume 6, Issue 3 , October 2014
Abstract
There exist a number of factors that affect the quality laser scanner. In other words, the accuracy of a terrestrial scanner is limited extensively by systematic errors and thus must be calibrated. Indeed, calibration is a prerequisite for obtaining 3D precise and reliable data from point clouds. Until ...
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There exist a number of factors that affect the quality laser scanner. In other words, the accuracy of a terrestrial scanner is limited extensively by systematic errors and thus must be calibrated. Indeed, calibration is a prerequisite for obtaining 3D precise and reliable data from point clouds. Until now, several models have been proposed to improve the accuracy of laser scanner data, most of which include both physical empirical parameters which are produced by observing point residuals, As a result, these models are just usable solely for those observations. The authors of have previously developed a new general parametric model based on the internal structure of laser scanner which can be used for a variety of TLS instruments. Due to of the importance of stability of parameters in a model, stability of them and the correlation between them needs to be investigated precisely, a task which is addressed thoroughly in this paper through a number of practical experiments. The results show that this model with a relative stability can improve the accuracy of TLS data. Keywords:Terrestrial Laser scanner, Calibration, Point cloud, Parametric model.
Amir Aghabalaei; Hamid Ebadi; Yasser Maghsoudi
Abstract
Monitoring the earth and its biosphere is an essential task in any scale to achieve a sustainable development. Therefore, forests, as an invaluable natural resource, have an important role to control the climate changes and the carbon cycle. For this reason, biomass and consequently forest height have ...
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Monitoring the earth and its biosphere is an essential task in any scale to achieve a sustainable development. Therefore, forests, as an invaluable natural resource, have an important role to control the climate changes and the carbon cycle. For this reason, biomass and consequently forest height have been known as the key information for monitoring the forest and its underlying surface. Several studies, it has been shown that Synthetic Aperture RADAR (SAR) imaging systems can greatly help to this purpose. In this framework, a novel technique called Polarimetric SAR Interferometry (PolInSAR) is an appropriate and an available tool for forest height estimation, due to its sensitivity to location and vertical distribution of the forest structural components. Based on this, from a view point, the methods employed in this field can be divided into two categories: a) based on Random Volume over Ground (RVoG) inversion model, and b) based on model-based decomposition techniques of PolInSAR data. In this study, in order to improve the forest height estimation, a novel method based on the combination of two mentioned categories has been proposed. The performance and the efficiency of the proposed method were demonstrated by four datasets related to the Pine and the deciduous forests which simulated from the PolSARProSim software in L and P bands.
A Sedaghat; H Ebadi
Volume 7, Issue 4 , November 2015, , Pages 61-84
Abstract
A descriptor is computed on a local region around a feature point and is used to characterize and compare the features. Various descriptors have been proposed in the literature which have different properties and performance in different image data. Evaluation of the local feature descriptor is important ...
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A descriptor is computed on a local region around a feature point and is used to characterize and compare the features. Various descriptors have been proposed in the literature which have different properties and performance in different image data. Evaluation of the local feature descriptor is important to identify the strengths and weaknesses of each algorithm in different applications. In this paper a performance evaluation of the state of the art in local descriptors is performed on a set of satellite images under varying imaging conditions. Ten descriptors are included, which are spin image (SI), shape context (SC), SIFT, PIIFD, SURF, DAISY, LSS, LBP, LIOP and BRISK. 80 satellite image pairs in three groups including simulated images, multi-temporal, and multi sensor images are used as data set and descriptors are evaluated using four evaluation criteria including Recall, Precision, positional accuracy and speed. The evaluation results indicate that there does not exist one descriptor which outperforms the other descriptor for all scene types and all types of transformations, but in average DAISY and SIFT show the best performance
H Emami; M Jafary; A Nazari Samani; A Malekian
Volume 10, Issue 2 , September 2018, , Pages 61-74
Abstract
Spatial modeling of the groundwater springs occurrences allowed the identification of new springs fordrinking, agriculture and industry. The objective of this study was spatial modeling of thegroundwater springs occurrences using the geomorphometry indexes affecting the groundwatersprings occurrences ...
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Spatial modeling of the groundwater springs occurrences allowed the identification of new springs fordrinking, agriculture and industry. The objective of this study was spatial modeling of thegroundwater springs occurrences using the geomorphometry indexes affecting the groundwatersprings occurrences and Weights-of-evidence control model and evaluating this model in CentralAlborz. Generally, 584 springs were identified in the study area that 409 (70%) of them were utilizedfor training and 175 (30%) springs for validation of Weights-of-evidence control model. 14 importantgeomorphometry indexes includin elevation, degree of slope, aspect, plan curvature, profilecurvature, topographic wetnes index, stream power index, slope length, topography position index,lithology, distance of faults, fault density, distance from rivers and drainage density were chosen inthe form of Weights-of-evidence control model for spatial modeling of the groundwater springsoccurrences. According to Weights-of-evidence control model, aspect and topographic wetness indexhad the lowest and the highest impact on the ground water springs occurrences respectively. The mapresulted from spatial modeling of groundwater springs occurrences were classified into 4 classesincluding the low, middle, high, and very high potential occurrences. The model was validated usingROC method, which the area under the curve was 0.866. This means the weights-of-evidence controlmodel was accurate enough for estimating the spatial modeling of groundwater springs occurrences inCentral Alborz.
Abolfazl Ranjbar; Abbasali Valia; Marzieh Mokarramb; Farideh Taripanahc
Abstract
Vegetation is one of the essential factors in structure and function of terrestrial ecosystem and it is one of the principal loops in water-soil-plant-atmosphere continuum. Several studies have demonstrated that vegetation covers are sensitive to alteration of climatic, edaphic, topographic and human ...
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Vegetation is one of the essential factors in structure and function of terrestrial ecosystem and it is one of the principal loops in water-soil-plant-atmosphere continuum. Several studies have demonstrated that vegetation covers are sensitive to alteration of climatic, edaphic, topographic and human activities. Thus, alteration in vegetation and its relation with the mentioned factors are important of high importance. In order to investigation of vegetation changes and its effective factors, the current study was conducted in Kharestan region placed in Fars province, Iran. In this regard, the images obtained from ETM Landsat 7 (2000-2017) and meteorological data gained from local and 17 regional meteorological stations were used. Using these images, temporal and spatial changes NDVI and NDVI anomaly were studied. A supervised classification method was used to extract land use map. Finally, the relationship of NDVI with climatic, topographic and anthropogenic factors was investigated. Relationship between NDVI and climatic and topographic factors was estimated using GWR and OLS methods, respectively. Generally, temporal variations showed a slow increasing trend in NDVI value. NDVI anomaly was mostly negative before 2008 but it turned to positive after 2009. NDVI spatial distribution showed an increasing tendency from north toward center and continued to south-west of the study area. The study shows that the vegetation cover change was caused by both natural factors and human activities. NDVI increased in agricultural and pasture lands. Also, natural vegetation has been affected by climatic factors more than irrigated vegetation (agricultural and gardens). Furthermore, vegetation variation influenced by topographic factors likes height, slope and aspect. Also, with an altitude over than 2500 m, NDVI showed a decreasing trend, on slopes lower than 5° it increased. NDVI values in north and east directions were higher than in southern aspects. The overall trend indicates an increase in temperature and a decrease in precipitation during the study period. The maximum positive and negative correlation between mean annual precipitation and NDVI using ordinary least squares method were 0.93 and 0.83, respectively. Also the maximum negative and positive correlation between NDVI and temperature were 0.65 and 0.5, respectively. The highest local R2 values between NDVI with precipitation and temperature were 0.45 and 0.44, respectively, which was observed in the central parts of the region. According to the obtained results through the present study, it can be stated that environmental factors like precipitation, altitude, slope and aspect are the Influential factors controlling vegetation in Kharestan (Fars province, Iran).
alijafar mousivand; meysam shir mohammad pour; ali shamsoddini
Abstract
Vegetation is a key component of the earth planet, which controls the energy and water exchanges between atmosphere and the Earth surface and plays an important role in the global energy cycles, such as oxygen, carbon dioxide, and water. Monitoring and management of vegetation are done using its biophysical ...
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Vegetation is a key component of the earth planet, which controls the energy and water exchanges between atmosphere and the Earth surface and plays an important role in the global energy cycles, such as oxygen, carbon dioxide, and water. Monitoring and management of vegetation are done using its biophysical and biochemical parameters such as LAI. Leaf area index (LAI) is one of the most important vegetation parameters that used in most of the applications such as water and carbon cycles modeling.Remote sensing in terms of their continuous and extensive cover is a unique tool for generating vegetation variables. Different retrieval approaches have been developed to extract biophysical parameters information from remote sensing data, which is divided into two broad classes, the statistical/experimental approaches and the physical approach. In the present study, the PROSAIL RT model (Radiation Transfer Model) based on the LUT table have been used to retrieve the LAI variable. Ground reference data collected during the SPARC 2003 campaign were also used to evaluate the accuracy of the retrieved variable. To drawback, the ill-posed problem, four categories of cost functions have been used: Information Measurement (IM), Minimum contrast (MC), Angle Measurement (SAM) and Least Square Error (LSE) and used the multiple Best solution instead of Single best solution. The results showed improvement in the LAI estimation of up to 12% for the multi-species canopy.
Maryam Haghighi Khomami; Mohammad Panahandeh; Mohammad javad tajaddod; Fariborz Jamalzad Fallah; Mahsa Abdoli
Abstract
Wetlands as an integral part of the global ecosystem in flood prevention or mitigation, feeding aquifers and providing unique habitat for plants and animals and other services and benefits are key elements of a regional conservation strategy. Anzali International Wetland in Guilan Province is one of ...
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Wetlands as an integral part of the global ecosystem in flood prevention or mitigation, feeding aquifers and providing unique habitat for plants and animals and other services and benefits are key elements of a regional conservation strategy. Anzali International Wetland in Guilan Province is one of the 10 most valuable wetlands in the world, which has undergone many changes in land use and vegetation due to structural changes resulting from man-made processes, and its nature and ecological functions have been endangered. The purpose of this study is to investigate the application of remote sensing data in mapping changes in the spatial pattern of the landscape with the help of field work training areas at the bed of the wetland and to analyze the changes of territorial cohesion based on the metrics of the landscape. First, satellite data were analyzed and Sentinel -2 images from 2016 to 2020 were classified by training areas. Then, a map of land cover in 7 classes of agriculture, barren, reed, forest, rangeland, water and urban area was created for mapping and analysis of land use metrics. After extracting class-level and landscape-level metrics in Fragstats software and determining appropriate metrics using PCA method with R and Canoco software, LPI, LSI, ENN_MN, CA, TE, NP, SHAPE_MN, PARA_MN, IJN, ARE_ Applications were selected for better analysis of the area. Analysis of metrics indicates that, in general, the landscape is fragmented, more complex and irregular in form, and more discontinuous in terms of the degree of integration of structural elements.
