Utilizing Collocated Crop Growth Model Simulations to Train Agronomic Satellite Retrieval Algorithms
Due to its worldwide coverage and high revisit time, satellite-based remote sensing provides the ability to monitor in-season crop state variables and yields globally. In this study, we presented a novel approach to training agronomic satellite retrieval algorithms by utilizing collocated crop growt...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2018-12-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/10/12/1968 |