Full cycle rice growth monitoring with dual-pol SAR data and interpretable deep learning
Addressing challenges in crop growth monitoring, such as limited assessment dimensions, incomplete coverage of growth cycles, and limited deep learning (DL) interpretability, a novel dual-pol SAR rice growth monitoring method using a new crop growth index (CGI) and an interpretable DL architecture i...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
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| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2024.2445639 |
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