Comparative Study of Random Forest and Support Vector Machine for Land Cover Classification and Post-Wildfire Change Detection
The land use land cover (LULC) map is extensively employed for different purposes. Machine learning (ML) algorithms applied in remote sensing (RS) data have been proven effective in image classification, object detection, and semantic segmentation. Previous studies have shown that random forest (RF)...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-11-01
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| Series: | Land |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-445X/13/11/1878 |
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