Optimizing time windows of Sentinel-2 images for deep learning-based cropland segmentation through iterative multi-criteria decision analysis
Precision agriculture depends on accurate cropland segmentation from satellite imagery. However, unoptimized satellite time series can lead to the inclusion of redundant information, increasing data volume and reducing the efficiency of deep learning (DL) model training. This study proposes a method...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Geocarto International |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10106049.2025.2509294 |
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