Water extraction from optical high-resolution remote sensing imagery: a multi-scale feature extraction network with contrastive learning
Accurately spatiotemporal distribution of water bodies is of great importance in the fields of ecology and environment. Recently, convolutional neural networks (CNN) have been widely used for this purpose due to their powerful features extraction ability. However, the CNN methods have two limitation...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2023-12-01
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| Series: | GIScience & Remote Sensing |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/15481603.2023.2166396 |