Within-season crop monitoring at continental scale utilizing new gap-filled Landsat temporal series
18 Pags.- 13 Figs.- 6 Tabls. The JavaScript code and datasets (including training and test datasets) used in this work are available to the interested reader in the GEE repository: https://code.earthengine.google.com/?accept_repo=users/RemoteSensing_master/prompt_classification (see ‘Demo’ script)....
| Autores: | , , , , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/368021 |
| Acceso en línea: | http://hdl.handle.net/10261/368021 |
| Access Level: | acceso abierto |
| Palabra clave: | Prompt crop monitoring HISTARFM Landsat MODIS Google Earth Engine high spatial resolution crop monitoring landsat |
| Sumario: | 18 Pags.- 13 Figs.- 6 Tabls. The JavaScript code and datasets (including training and test datasets) used in this work are available to the interested reader in the GEE repository: https://code.earthengine.google.com/?accept_repo=users/RemoteSensing_master/prompt_classification (see ‘Demo’ script). © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License. |
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