Remote Sensing | |
An Automated Method for Annual Cropland Mapping along the Season for Various Globally-Distributed Agrosystems Using High Spatial and Temporal Resolution Time Series | |
Nicolas Matton4  Guadalupe Sepulcre Canto4  François Waldner4  Silvia Valero3  David Morin3  Jordi Inglada3  Marcela Arias3  Sophie Bontemps4  Benjamin Koetz1  Pierre Defourny4  Clement Atzberger2  | |
[1] European Space Agency, European Space Research Institute, Via Galileo Galilei, Casella Postale 64, 00044 Roma, Italy; E-Mail:Earth and Life Institute, Université Catholique de Louvain, Croix du Sud 2, 1348 Louvain-la-Neuve, Belgium;;Centre d’Etudes Spatiales de la BIOSphère, Unité Mixte CNES-CNRS-UPS-IRD, Toulouse 31401, France; E-Mails:;Earth and Life Institute, Université Catholique de Louvain, Croix du Sud 2, 1348 Louvain-la-Neuve, Belgium; E-Mails: | |
关键词: agriculture monitoring; cropland; timeliness; high resolution time series; Sen2Agri; Sentinel-2; SPOT 4 (Take 5); JECAM; | |
DOI : 10.3390/rs71013208 | |
来源: mdpi | |
【 摘 要 】
Cropland mapping relies heavily on field data for algorithm calibration, making it, in many cases, applicable only at the field campaign scale. While the recently launched Sentinel-2 satellite will be able to deliver time series over large regions, it will not really be compatible with the current mapping approach or the available
【 授权许可】
CC BY
© 2015 by the authors; licensee MDPI, Basel, Switzerland.
【 预 览 】
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RO202003190005289ZK.pdf | 5903KB | download |