In-Season Automated Mapping of Xinjiang Cotton Based on Cumulative Spectral and Phenological Characteristics
Obtaining timely, accurate, and automated data on the spatial distribution and planting area of cotton is crucial for production management and informed trade decision-making. In this regard, remote sensing technologies are important and effective means. Methods based on machine learning, and deep l...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10827816/ |
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