List of Articles saman javaheri

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  1 - target detection using fusion of hyperspectral and high resolution imagery
  saman javaheri Ali asghar torahi seyed mohammad tavakoli sabour
  Identification is a mission to learn about the activities, resources, abilities and position of the enemy. Military targets detection can provide commanders with a variety of information on the status of activities, deployment of forces, military arrangement of targets, More

  Identification is a mission to learn about the activities, resources, abilities and position of the enemy. Military targets detection can provide commanders with a variety of information on the status of activities, deployment of forces, military arrangement of targets, and many other information from a military area. In recent years, the advancement of remote sensing technology has made it possible to produce different images with high resolution Spectral and spatial. fusion of hyperspectral and high resolution imagery can help effectively identify, extract, and produce maps from the constituent elements of an environment. The purpose of this research is to target detection (military) using fusion of hyperspectral and high resolution imagery. For this reason the Hyperion, ALI and OrbView3 data was acquired. Firstly, Hyperion Data Preprocessing was used in terms of unused bands, bad straights, atmospheric correction and geometric correction. The image of Hyperion in a two-step process with panchromatic bands combined ALI and OrbView3 images using gram-schmidt, Pc Spectral, and IHS algorithms. The combined results showed that Gram schmidt had the best spectral and spatial performance. In the next research, the MNF conversion was used to reduce the image size and reduce the noise, and the PPI algorithm of the purest pixels was used to extract the spectral profile in a visual and precise manner compared with the reference spectra. In the following, algorithms, BANDMAX, spectral angle mapper and divergence spectral information were used to identify the targets. The results of the identification of the objectives showed that the BANDMAX method with a Overall accuracy of 89.25 and Kappa coefficient of 0.723 was better than the other two algorithms. Manuscript profile
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  2 - Ability to prepare methods land use maps using satellite images (Case study: Kamyaran city)
  saman javaheri ali asghar torahi seyed mohammad tavakoli sabour
  It is important to have new land use plans in many areas, including natural resource management and land planning. Remote sensing data has a high potential for preparing up-to-date land use maps and land cover. The purpose of this study is to evaluate the methods of pre More

  It is important to have new land use plans in many areas, including natural resource management and land planning. Remote sensing data has a high potential for preparing up-to-date land use maps and land cover. The purpose of this study is to evaluate the methods of preparing land use maps of Kamyaran city using satellite images. In this study, OLI Landsat 8 satellite sensor data for June 2018 were used. Initially, preliminary processing, including radiometric, atmospheric, and geometric corrections, was performed on raw data. ground control points were used for training, accreditation, and land use mapping. The Landuse class was identified at each point by field survey and using Google Earth images in 9 user classes of agricultural lands, forest, garden, rich pastures, medium pastures, residential areas, water area, barren lands and rocky outcrops. In the following, maximum probability, minimum distance, support vector machine and Mahanalubi distance were used for the supervised classification in ENVI 5.3 software. To evaluate the accuracy of classification methods, two criteria of general accuracy and capa coefficient were used with ground control data. The results showed that the support vector machine method was 91.4% more accurate and the Kappa coefficient was 0.88% more accurate than other methods. Manuscript profile
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  3 - Potential assessment hazard of forest fires and rangelands using AHP model (Case study: Kamyaran city)
  saman javaheri ali asghar torahi
  Fires in Zagros Rangelands and Forests Given the protective role of these forests in preventing water and soil erosion, it is a serious environmental threat to these forests and rangelands. The purpose of this study was to analyze the spatial distribution of fires in ra More

  Fires in Zagros Rangelands and Forests Given the protective role of these forests in preventing water and soil erosion, it is a serious environmental threat to these forests and rangelands. The purpose of this study was to analyze the spatial distribution of fires in rangelands and forests of Kamyaran city and identify areas prone to fire. According to reported fires, the major fires were identified as having the highest frequency and frequency, and the file was compiled using the Global Positioning System (GPS) of the entire area in the past few years and after converting it to soft format. The Arc Map was transferred and a map of the scattered areas of forests and rangelands was prepared. Then, by analyzing the studies in this area and asking the experts of natural resources, Jihad of Agriculture and Meteorology, six factors influencing the fire in rangelands and forests of this region were analyzed. Influential factors include precipitation, temperature, river distance, distance from road, elevation and slope of the area. Then, using the Analytical Hierarchy Process (AHP), the information layers in the Expert Choise software were weighted and then compared by pairwise comparison. Finally, after incorporating layers in Arc Map software, the final map of fire hazard zoning of forests and rangelands of the city was classified into five classes of areas with high potential to very low potential. The results showed that the ground truth layers were in full agreement with the final map and most of the large-scale wildfires were located in high potential and very high critical areas and from the total forest area and rangelands of the high potential areas. The fire covered an area of 45218.14 hectares, comprising 22% of the total area. Manuscript profile
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  4 - Detection of land use changes using satellite imagery during the period 1984-2019 (Case study of Kamyaran city)
  saman javaheri Ali asghar Torahi
  20.1001.1.26763508.1400.12.1.3.4
  Land use change due to human activities is one of the important issues in regional and development planning. Given the advantages and capabilities of satellite data, this technology can be of great help in identifying and detecting these changes. The purpose of this stu More

  Land use change due to human activities is one of the important issues in regional and development planning. Given the advantages and capabilities of satellite data, this technology can be of great help in identifying and detecting these changes. The purpose of this study is to detect land use changes in Kamyaran city using satellite images over a period of 35 years. In this study, data from 1984 TM sensor, 2000 ETM + sensor and 2019 Landsat OLI sensor were used.  Initially, preliminary preprocessions including radiometric, atmospheric and geometric corrections were performed on the raw data. Land control points were used for training, accreditation and to prepare land use map. Land use class was determined by field survey and using Google Earth images in 9 land use classes of agricultural lands, forests, gardens, rich and wooded pastures, medium rangelands, residential areas, water area, barren lands and rock outcrops. Next, the neural network method was used to monitor the images in ENVI 5.3 software. The evaluation results showed that the overall accuracy and kappa coefficient of OLI classified images are 94.3 and 0.92%, ETM + 92.6 and 0.91% and TM 90.3 and 0.87%, respectively. The results showed that forest lands and rich and wooded pastures decreased significantly during three time periods, which decreased by 11.64 and 19.12 percent, respectively. So that rich and wooded pastures have an increasing trend until 2000 and in the next period until 2019 has a decreasing trend. Residential lands, water areas and gardens increased by 2.27%, 0.57% and 3.98%, respectively. Due to the growing trend of population and urbanization, the results of this study provide the necessary information to make basic decisions in the development of management policies for planners and regional managers for the sustainability and evaluation of natural resources. Manuscript profile