Monitoring and Analysis of Land Use Changes Using Satellite Images and Remote Sensing (Case Study: Sabzevar City)
محورهای موضوعی : فصلنامه علمی پژوهشی سنجش از دور راداری و نوری و سیستم اطلاعات جغرافیایی
Amin Mohammadi Dehcheshmeh
1
(Senior expert of Jahad Nasr company of Yazd, Yazd, Iran)
Razieh Mirfazlullah
2
(Employee of document registration office of Mashhad, Mashhad, Iran)
کلید واژه: land use, Landsat, remote sensing, Maximum Probability,
چکیده مقاله :
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.
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.
