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Назва: Using Multispectral Images to Establish Land Categories
Автори: Perovych, L.
Perovych, I.
Lazarieva, O.
Mas, A.
Ключові слова: Land categories
Space images
Multi-criteria analysis
Дата публікації: 2024
Видавництво: Montreal Quebec: Grassroots Institute
Короткий огляд (реферат): At the present stage, the dominant means of obtaining information is space shooting, which is carried out from space carriers with the help of special shooting equipment, and makes it possible to obtain high-quality images covering a significant area of the earth's surface. Methods combining multi-criteria analysis and GIS technologies can be used to make appropriate environmental decisions. At the same time, an important component for all interested parties is obtaining the original information at the lowest cost. In this regard, this publication provides a methodology for constructing maps of land categories, which is based exclusively on a free basis. This methodology includes free and open FOSS software, space images of the Landsat 8 satellite, and multi-criteria analysis of space image processing. The procedure of the methodology includes the creation of a database based on available land management documents, cadastral plans and maps, satellite images, etc.; processing of the database using multi-criteria analysis; analysis of the results and decision-making. The database is created using QGIS software, and PostgreSQL with the PostGIS extension is used for modeling and data storage. MultiSpec software was used to create multispectral images, perform satellite image classification and evaluation. Using a set of the above software products and Landsat 8 satellite images, a pilot project on an area of 615 km2 was carried out to determine the capabilities of this methodology for establishing land categories. It was established that the multispectral image of the combination of 6-5-2 channels best represents land categories. The accuracy of the classification is 96.2%, and the User Accuracy for arable land is almost 100%, for orchards 55%, and for hayfields and pastures 61.3%.
Опис: Perovych, L., Perovych, I., Lazarieva, O., & Mas, A. (2024). Using Multispectral Images to Establish Land Categories. Grassroots Journal of Natural Resources, 6 (1), 166-176. DOI: 10.33002/nr2581.6853.060108
URI (Уніфікований ідентифікатор ресурсу): https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195399857&doi=10.33002%2fnr2581.6853.060108&partnerID=40&md
https://grassrootsjournals.org/gjnr/0601m00331.html#status
https://dspace.chmnu.edu.ua/jspui/handle/123456789/2335
ISSN: 2581-6853
Розташовується у зібраннях:Публікації науково-педагогічних працівників ЧНУ імені Петра Могили у БД Scopus



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