Modern classification methods for monitoring of vegetation cover

The work will deal with monitoring the development of vegetation and its classification. Satellite  aerial and drone remote sensing plays a key role in vegetation monitoring. As traditional field-based assessments face challenges due to inaccessible sites and lengthy data collection, remote sensing applications exist for monitoring different vegetation ecosystems including forests, grasslands and agriculture. The research topic will be advanced techniques for land cover classification, especially in terms of vegetation cover and condition, using new classification methods including artificial intelligence. Machine learning methods have seen a great deal of growth in recent years and need to be seriously considered in terms of previously classical monitoring and classification methods. The focus will be on comparing classical methods with random forest method and available machine learning methods. In particular, the result will be an analysis of applicability for monitoring and classification of vegetation conditions for different tyoes of vegetation land covers.

Literature:

1)Prem Chandra Pandey (Editor), Mukunda Behera (Editor), Komali Kantamaneni (Editor), Navneet Kumar (Editor) Remote Sensing for Vegetation Monitoring: Technologies, Applications and Models Kindle Edition, 2026. ISBN-13 ‏ : ‎ 978-0443330773 2)Kenji Omasa, Shan Lu, Jie Wang, 2023. Crops and Vegetation Monitoring with Remote/Proximal Sensing, ISBN 978-3-0365-9446-0 (Hardback)