Within-season crop monitoring at continental scale utilizing new gap-filled Landsat temporal series

18 Pags.- 12 Figs.- 5 Tabls. Data availability: 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 (se...

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Bibliographic Details
Authors: Rajadel-Lambistos, C., Moreno-Martínez, A., Maneta, M. P., Beguería, Santiago, Kimball, J. S., Clinton, N., Atzberger, C., Camps-Valls, G. S.W., Running, S. W.
Format: article
Status:Published version
Publication Date:2024
Country:España
Institution:Consejo Superior de Investigaciones Científicas (CSIC)
Repository:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/366687
Online Access:http://hdl.handle.net/10261/366687
Access Level:Open access
Keyword:Prompt crop monitoring
HISTARFM
Landsat
MODIS
Google Earth Engine
highspatial resolution
crop monitoring
landsat
Description
Summary:18 Pags.- 12 Figs.- 5 Tabls. Data availability: 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). This is an Open Access article distributed under the terms of the Creative Commons Attribution License.

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