High spatial resolution crop type and land use land cover classification without labels: A framework using multi-temporal PlanetScope images and variational Bayesian Gaussian mixture model
Previous studies often combined high spatial resolution data (e.g., PlanetScope) with wider spectral range data (e.g., Sentinel-2) and relied on supervised classification methods to produce land use and land cover (LULC) maps. This study proposed a new unsupervised framework to generate crop type an...
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| Main Authors: | Minh Tri Le, Khuong H. Tran, Phuong D. Dao, Hesham El-Askary, Tuyen V. Ha, Taejin Park |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-12-01
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| Series: | Science of Remote Sensing |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666017225000707 |
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