This study examines changes in the earth's surface along a specific route using aerial photographs of the earth. It aims to analyze land change using aerial photographs and according to a specific route.
In this study, route coding was first done. This route coding process is manually coded. In the past, this route coding was done on paper by sailors and pilots using the manual route determination technique. After the route coding is done, the required latitude and longitude values of the desired region are found on this route and then the data collection part is started.
The scrape technique was used as the data collection method. The latitude and longitude information of the desired region, entered via Google Maps and Yandex Maps with the Selenium library, is entered and screenshots are taken. And it is saved in the database after various preprocessing processes.
Afterwards, data analysis is performed using the data obtained. Haralick values are available. And because of these values, the data is divided into test and train and a machine learning model is created.
As a result, it is expected that it will be possible to automatically analyze land change according to the route from aerial photographs. This analysis will be an important source of information that can be used in various applications. For example, it has potential for use in areas such as land use analysis, urban planning, and natural disaster management. This study aims to assist architects, civil engineers, and experts working in this field in land use and urban planning.