Vegetation classification in a subtropical region with Sentinel-2 time series data and deep learning
Preparing regular time series optical remote sensing data is a difficult task due to the influences of frequently cloudy and rainy days. The irregular data and their forms severely limit the data’s ability to be analyzed and modeled for vegetation classification. However, how irregular time series d...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-01-01
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| Series: | Geo-spatial Information Science |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10095020.2024.2336604 |
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