Synergizing BRDF correction and deep learning for enhanced crop classification in GF-1 WFV imagery
Accurate crop classification is essential for agricultural management, resource allocation, and food security monitoring. GF-1 Wide Field View (WFV) imagery suffers from Bidirectional Reflectance Distribution Function (BRDF) effects due to large viewing angles (0°–48°), reducing crop classification...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-07-01
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| Series: | Frontiers in Remote Sensing |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/frsen.2025.1620109/full |
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