Assessing Land Cover Changes Using the LUCAS Database and Sentinel Imagery: A Comparative Analysis of Accuracy Metrics
Classification of remote sensing images using machine learning models requires a large amount of training data. Collecting this data is both labor-intensive and time-consuming. In this study, the effectiveness of using pre-existing reference data on land cover gathered as part of the Land Use–Land C...
Saved in:
Main Authors: | Beata Hejmanowska, Piotr Kramarczyk |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-12-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/15/1/240 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Detecting and Mapping Peatlands in the Tibetan Plateau Region Using the Random Forest Algorithm and Sentinel Imagery
by: Zihao Pan, et al.
Published: (2025-01-01) -
Application of the ESTARFM algorithm for fusing Sentinel-2 and MODIS NDSI series in the eastern Qilian Mountains
by: Hui Guo, et al.
Published: (2025-02-01) -
Coupling ICESat-2 and Sentinel-2 data for inversion of mangrove tidal flat to predict future distribution pattern of mangroves
by: Xiaoyong Ming, et al.
Published: (2025-02-01) -
Assessing swidden land use in Myanmar by decision tree-based detection method using landsat imagery
by: Nyein Chan, et al.
Published: (2022-10-01) -
Lucas numbers of the form PX2, where P is prime
by: Neville Robbins
Published: (1991-01-01)