Monitoring Key Agricultural CROPS in the Netherlands using Sentinel-1

Conference Paper (2018)
Author(s)

Susan C. Steele-Dunne (TU Delft - Water Resources)

Saeed Khabbazan (TU Delft - Water Resources)

Paul Vermunt (TU Delft - Water Resources)

A.M. Ratering Arntz (TU Delft - Water Resources)

C. Marinetti (TU Delft - Water Resources)

Lorenzo Iannini (TU Delft - Optical and Laser Remote Sensing)

K. Westerdijk (Aeres Hogeschool)

C. van der Sande (NEO BV.)

Research Group
Water Resources
Copyright
© 2018 S.C. Steele-Dunne, S. Khabbazan, P.C. Vermunt, A.M. Ratering Arntz, C. Marinetti, L. Iannini, K. Westerdijk, C. van der Sande
DOI related publication
https://doi.org/10.1109/IGARSS.2018.8518953
More Info
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Publication Year
2018
Language
English
Copyright
© 2018 S.C. Steele-Dunne, S. Khabbazan, P.C. Vermunt, A.M. Ratering Arntz, C. Marinetti, L. Iannini, K. Westerdijk, C. van der Sande
Research Group
Water Resources
Volume number
2018
Pages (from-to)
4423-4426
ISBN (print)
978-1-5386-7151-1
ISBN (electronic)
978-1-5386-7150-4
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

In this study, we performed ground validation to support the interpretation of Sentinel-1 imagery during a full growing season of five key crop types in the Netherlands. Crop height and growth stage were monitored weekly in a total of 25 parcels of maize, potato, sugar beet maize and English rye grass in the province of Flevoland. Hydrometeorological data were collected throughout the season. Here, these results are used to interpret time series of Sentinel-1 data processed for the province of Flevoland. Results demonstrate that Sentinel-1 data follow the phenological stages and can be used to identify key moments in crop development. Combined with the guaranteed availability of observations regardless of cloud cover, this makes Sentinel-l data a valuable resource for agencies and commercial entities providing advice to farmers and agro-industrial co-operatives.

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