Journal of Radar and Optical Remote Sensing and GIS	: 5 (4)

Open Access Article

1 - Introduction

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Open Access Article

2 - The Analysis and Ranking of Spatial Distribution of Waste Landfill Potential, Using AHP Model and TOPSIS Technique (Case Study: Rasht)
Ameneh Rezaei Farajabad Mahdi Zarrini

One of the effects of a gradual population increase in the urban areas is waste in crescent and its disposal. Among the common methods of waste management, land filling is technically, ecologically and economically important. The purpose of this study is to determine th More

One of the effects of a gradual population increase in the urban areas is waste in crescent and its disposal. Among the common methods of waste management, land filling is technically, ecologically and economically important. The purpose of this study is to determine the appropriate spatial potential for sanitary landfill of waste in Rasht, based on location criteria and using GIS and remote sensing. Zoning of suitable burial sites was done based on the 4 main criteria of land use, hydrological characteristics, geological characteristics and accessibility. In a current study, SRTM sensor data, which is paired with a short time interval (to reduce changes occurring at ground level) was used to prepare a digital model of land. The maps derived from the digital model of land, included elevation and slope maps that were used to prepare the criteria of the "geological profile." After standardization and preparation of maps, in order to achieve the weight and importance of each layer to find suitable landfills, the weight of the layers used was calculated by hierarchical analysis method. Considering the effective factors in locating the municipal waste landfill and weighing each of the criteria and sub-criteria, five values of very suitable, suitable, relatively suitable, inappropriate and very inappropriate were specified. To determine the priority of the very suitable areas, the TOPSIS method was used. Among the 9 sites introduced to the TOPSIS algorithm, site four, with an area of 89.36 hectare, which is located in the southern parts of Rasht, was determined as the most suitable place for waste disposal. Manuscript profile

Open Access Article

3 - License Plate Detection and Recognition based on Neural Networks in Complex Environments
.N. . Ameena Bibi Purru Supriya

Now a days due to the rapid advancement of economy around the world the count of vehicles increases day by day. Increase in the number of vehicles causes violation detection, road congestion, accidents at different traffic situations, uneven illumination, lighting and w More

Now a days due to the rapid advancement of economy around the world the count of vehicles increases day by day. Increase in the number of vehicles causes violation detection, road congestion, accidents at different traffic situations, uneven illumination, lighting and weather conditions. To overcome this issue license plate number is recognized but due to variations in license plate layout, font size of characters, tilted number plates, weather conditions, dirt plate and motion blur license plate recognition becomes difficult. License plate recognition has two main tasks, one is to detect the license plate and the other is to identify the license plate characters. By using region of interest license plate is detected. For recognition first tilted images are corrected using affine transformation and to improve the quality of a low-resolution image super resolution CNN is employed and connected component analysis, horizontal and vertical projection profile area used for separating each individuals characters. Each individual character image is fed to the Convolutional Neural Network (CNN) for character extraction and for classification and the license plate is recognized using convolutional neural networks. The main aim of this paper is to recognize different plate layout with different conditions with minimum data set and less processing time with maximum efficiency. Manuscript profile

Open Access Article

4 - Evaluation of Local Climate Zone Model in Monitoring Land Use Changes with Emphasis on Physical Growth (Study Area: Tehran)
Seyed aghil Ebrahimi Seyed Ali Almodaresi Farhad Hamzeh

Land use change and land cover are considered as one of the important and effective factors on global environmental change, so understanding and predicting the causes, processes and consequences of land use change has become a major challenge on the planet. Today, remot More

Land use change and land cover are considered as one of the important and effective factors on global environmental change, so understanding and predicting the causes, processes and consequences of land use change has become a major challenge on the planet. Today, remote sensing technology and GIS are used effectively to identify and quantify land use change and its effects on the environment. The physical development of cities and the expansion of its dimensions is one of the important factors in urban land change that has many environmental, economic and social consequences. In the past few decades, the city of Tehran has faced numerous urban growth and development and surrounding towns, which has caused extensive changes in the urban lands of Tehran and surrounding areas. In this study, the trend of land use changes in Tehran in the past few decades has been studied. In the present study, using Landsat 8 satellite images, the change and transformation of lands in Tehran from 2013 to 2020 was monitored. Images were pre-processed and classified according to the LCZ model in 17 classes. Then, they were classified in SEGA GIS software and analyzed by image difference and post-classification methods. The results of image processing and classification show that urban lands are constantly growing and barren lands are increasing on a very small and slow scale. Also, land with dense vegetation has decreased from 2013 to 2020, which in itself can cause serious damage to urban planning for city managers. Manuscript profile

Open Access Article

5 - Monitoring and Analysis of Land Use Changes Using Satellite Images and Remote Sensing (Case Study: Sabzevar City)
Amin Mohammadi Dehcheshmeh Razieh Mirfazlullah

Remote sensing is one of the effective tools to study the process of land use change on a large scale and in a short time. In this research, the aim is to monitor and analyze land use changes using satellite images and remote sensing from 2010 to 2020 in Sabzevar city w More

Remote sensing is one of the effective tools to study the process of land use change on a large scale and in a short time. In this research, the aim is to monitor and analyze land use changes using satellite images and remote sensing from 2010 to 2020 in Sabzevar city with Landsat images. For research, preprocessing included atmospheric correction and radiometric and geometric correction. A total of 200 ground control points were collected to classify and evaluate the accuracy of the classification with the maximum probability classification algorithm in the ground visit. The classification results showed that the forest area in 2010 was equal to 68980.21 hectares, which with the change of use and its conversion to residential use, barren and rainfed agriculture in 2020 reached 66044.99 hectares, ie 2935.22 hectares, its area has decreased. Residential use with its growth in 2010 to 2020 has increased from 2855.89 to 4563.98, ie 1708.09 hectares. Land use changes in semi-dense rangeland have also decreased from 167164.89 to 153287.68 hectares, i.e. 13877.21. Kappa coefficient and overall accuracy in 2020 were 98.42 and 97.84, respectively, which was the highest value compared to previous years. In this study, it can be recommended that the government increase the vegetation of the land to protect pasture and forest uses against further changes, and to compensate for these changes, to plant fast-growing forests. Manuscript profile

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