Journal of Radar and Optical Remote Sensing and GIS	: 2 (2)

Open Access Article

1 - Detection and Diagnosis of Fire Areas in Golestan Forests Using Landsat Satellite Images
Ali Emadizadeh Zahra Azizi

Fire is a major factor in the development of some plant communities, especially those exposed to lightning. Lightning is almost the main cause of natural fires in most plant communities. Fire is effective in the evolution of various species of forests, pastures, and shr More

Fire is a major factor in the development of some plant communities, especially those exposed to lightning. Lightning is almost the main cause of natural fires in most plant communities. Fire is effective in the evolution of various species of forests, pastures, and shrubs in arid regions of the world's Mediterranean regions. Remote sensing and geographic information systems are appropriate in assessing the severity of burns. In this study, the intensity of the fire in Gorgan forests is evaluated and examined. The period of the study area was from 2013 to 2017 and Landsat 8 satellite imagery was used. First, the fire points were identified within an area of 500 meters by the IDW method. Then, by using NDVI, NBR, and dNBR indicators, fire points were evaluated and fire points were marked with red pixels which is clear in the two pictures before and after the fire. Finally, it was concluded that the NBR and dNBR index are the most accurate indicators with an accuracy of more than 74%. Manuscript profile

Open Access Article

2 - Predicting Land Changes in River Margin and Urban Areas by Remote Sensing and GIS
ehsan izadi Ali Akbar Jamali

Today, the rapid growth of the world's urban population, especially in developing countries, has created many problems in various fields. Among these, land-use change is of great importance. Modeling and predicting future land-use changes has become increasingly importa More

Today, the rapid growth of the world's urban population, especially in developing countries, has created many problems in various fields. Among these, land-use change is of great importance. Modeling and predicting future land-use changes has become increasingly important for urban and environmental management and other relevant authorities and researchers. The main purpose of this study is to apply cellular automata (CA) Markov models based on spatial information system to simulate and predict land-use change. Landsat satellite imagery was prepared during the three periods of late June 1986, 2001, and 2016. Then land use maps of the study area were obtained by classifying the maps. The Manuscript profile

Open Access Article

3 - Fusion of Synthetic Aperture Radar Images and Optical Images Using Curvelet Transform and Retina model
Mina Solhi Mehran Yazdi Mahmoud Sharzehei

In recent years, various image integration techniques have been developed to improve their quality. In this paper, some image integration techniques such as Intensity-Hue-Saturation (HIS), Brovey transform, feedback, non-feedback retina model, wavelet transform, and cur More

In recent years, various image integration techniques have been developed to improve their quality. In this paper, some image integration techniques such as Intensity-Hue-Saturation (HIS), Brovey transform, feedback, non-feedback retina model, wavelet transform, and curvelet transform are investigated to improve the spectral and spatial information of satellite images. Also, a new algorithm has been proposed to improve the image quality resulting from the combination of SAR and visible-like images. In the proposed method, the curvelet transform is first applied to the three input levels of Synthetic Aperture Radar (SAR) and visible-like images, then using horizontal cells in the feedback retina model, spectral and spatial information below a specified and adjustable frequency is determined by a Gaussian low-pass filter and replaced with the curvelet coefficients of the integrated image approximation sub-band. Moreover, fine1 and detail1 sub-bands are selected from the visible-like image, and the coefficients of fine2, detail2 sub-bands are weighted and aggregated from both SAR and visible-like images in a specific way. Spectral and spatial quality evaluation criteria including Quality Index (Q_I), Measure the Quality of edges (Q^(AB/f)) Relative Dimensionless Global Error in System (ERGAS), Mutual Information (MI), Euclidian Distance (ED) and Standard Deviation (STD) were used to compare and analyze the results of the methods. The results of this evaluation indicated the remarkable performance of the proposed method in preserving the spectral and spatial information content of the integrated image compared to other methods. Manuscript profile

Open Access Article

4 - Detection, Recognition and Tracking Cars from UAV Based implementation of MobileNet- Single Shot Detection deep neural network on the embedded system By Using Remote Sensing Techniques
Mohammadjavad Nateghi

Tracking targets from the ground is difficult due to natural and artificial barriers, and in some cases, such as car detection, is dangerous, therefore, identifying targets using remote sensing is obvious. To achieve the purpose, the desired camera is installed on the u More

Tracking targets from the ground is difficult due to natural and artificial barriers, and in some cases, such as car detection, is dangerous, therefore, identifying targets using remote sensing is obvious. To achieve the purpose, the desired camera is installed on the unmanned aerial vehicle (UAV). with images processing on captured images from the camera, the system has used can identify the vehicle using aerial images and follow it if it is necessary. An important issue to this matt Manuscript profile

Open Access Article

5 - Investigation of land Subsidence in Orzuiyeh Plain of Kerman Using Radar Differential Interference Method (DINSAR)
Mahdi Emambakhsh Karim Naghdi

The Phenomenon of subsidence of the earth occures causing wide–raging problems and dangers. The occurrence of this phenomenon causes problems for farmers, the destruction of communication lines and infrastructures and some other issues. In this research from diffe More

The Phenomenon of subsidence of the earth occures causing wide–raging problems and dangers. The occurrence of this phenomenon causes problems for farmers, the destruction of communication lines and infrastructures and some other issues. In this research from differential interference (DINSAR) and using ASAR sensor data from 2009 to 2010 and sensors sentinel 1 in 2014 – 2015 in relation to the Kerman's Orzuiyeh plain, it is tried to depict the phenomenon of desertification in the picture of the Kerman valley. temporal and spatial Changes have been made in this plain. seascape software is used to process image The results of the series analysis the time has come to show that the region is continuously subsiding; the amount of subsidence per year 2008 to 2009 is 15 centimeters, the most abandoned in the northwest and central plain and 2009 year by 9, 100 cm by 2010, which is still the high et amount of subsidence in the northwest and central plain and for the year 2014 to 2015 is 8.2 cm and the largest amount of this phenomenon is in the southeast part of the Orzuiyeh plain. looking at the pictures of the subsidence of these years can be concluded that Orzuiyeh's desertification is dynamic and has a trend from the north the west was southeast of the plain. Manuscript profile

Open Access Article

6 - FFT-PCA Image Fusion Based Flora and Vegetation Mapping Of Eshkevarat No Hunting Zone
Zeinab Hoseinnejad Hasan Hasani Moghaddam Zahra Parvar Kourosh Kavousi Hamid Gashtasb Meigooni

fusion of remote sensing data is essential in order to obtain more information from different images. Mapping the vegetation of an area is very important due to its environmental importance. In this research, used Landsat ETM+ images and field surveying to identify vege More

fusion of remote sensing data is essential in order to obtain more information from different images. Mapping the vegetation of an area is very important due to its environmental importance. In this research, used Landsat ETM+ images and field surveying to identify vegetation states of the Eshkevarat No hunting zone. After applying necessary preprocessing like gap filling and atmospheric correction, the panchromatic and multi-spectral images were fused based on the FFT-PCA algorithm. In the next section, the fused image was classified based on the Support Vector Machine (SVM), algorithm into five classes. The results showed that the overall accuracy and kappa coefficient of classified images is 0.943% and 0.910 respectively. In order to field surveying of study area, 1-meter plots in 500-meter distance choose and 14 Flora and vegetation species were identified and mapped. The results showed that satellite images have good accuracy in this field but based on its spatial resolution limitations a large number of species present in the area have not been identified. In this research, it is suggested to use a combination of both satellite image sources and field surveys. Manuscript profile

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