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Güneysınır Vocational School

Home / Güneysınır Vocational School / Architecture and Urban Planning / A Protocol was signed between Güneysinir District Directorate of Agriculture and Forestry and Selcuk University Guneysinir Vocational School

Güneysınır Vocational School

A Protocol was signed between Güneysinir District Directorate of Agriculture and Forestry and Selcuk University Guneysinir Vocational School

Architecture and Urban Planning Content

A Protocol was signed between Güneysinir District Directorate of Agriculture and Forestry and Selcuk University Guneysinir Vocational School

ANNOUNCEMENT

A scientific research project protocol was signed between Güneysinir District Directorate of Agriculture and Forestry and Selcuk University Guneysinir Vocational School, which aims to determine agricultural areas and monitor agricultural resources.

Within the scope of the project, agricultural activities will be managed more effectively by combining satellite data, GNSS, GIS and artificial intelligence techniques. A project is planned in which techniques such as remote sensing, GNSS, GIS and artificial intelligence will be used to accurately detect agricultural areas and monitor agricultural resources. In the project, it is aimed to use 2020-2021-2022 data of free satellite platforms and to apply artificial intelligence and machine learning techniques.

Remote sensing plays an important role in monitoring agricultural fields by using data with radiometric and multi-spectral bands obtained from different platforms. This data will be used to assess the status of agricultural resources, perform vegetation analysis and identify potential farmland.

GNSS (global positioning system) will enable the precise determination of the geographical location of agricultural lands. In this way, monitoring, planning and management of agricultural activities at the local level will be carried out more effectively.

GIS (geographic information system) is a technology for storing, analyzing and visualizing remote sensing data. GIS can be of great help in tasks such as identifying agricultural areas, proportioning them by area, and identifying potential agricultural areas.

Artificial intelligence and machine learning techniques will be used to analyze large amounts of data and discover patterns. With these techniques, it is aimed to automatically detect and classify agricultural areas and to identify potential agricultural lands. Thus, it becomes possible to make more efficient decisions in agricultural management and planning.

We would like to thank the Selcuk University Rectorate, Guneysinir Vocational School Directorate, Guneysinir District Agriculture and Forestry Directorate and Guneysinir District Governor's Office for their support of the project.

Selcuk University

Güneybound Vocational School

Department of Architecture and Urban Planning

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