Preprints
https://doi.org/10.5194/essd-2020-338
https://doi.org/10.5194/essd-2020-338

  07 Jan 2021

07 Jan 2021

Review status: this preprint is currently under review for the journal ESSD.

C-band radar data and in situ measurements for the monitoring of wheat crops in a semi-arid area (center of Morocco)

Nadia Ouaadi1,2, Jamal Ezzahar3,4, Saïd Khabba1,4, Salah Er-Raki4,5, Adnane Chakir1, Bouchra Ait Hssaine4, Valérie Le Dantec3, Zoubair Rafi1,2, Antoine Beaumont6, Mohamed Kasbani3, and Lionel Jarlan3 Nadia Ouaadi et al.
  • 1LMFE, Department of Physics, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakech, Morocco
  • 2CESBIO, University of Toulouse, IRD/CNRS/UPS/CNES, Toulouse, France
  • 3MISCOM, National School of Applied Sciences, Cadi Ayyad University, Safi, Morocco
  • 4CRSA, Mohammed VI Polytechnic University UM6P, Benguerir, Morocco
  • 5ProcEDE, Department of Applied Physics, Faculty of Sciences and Technologies, Cadi Ayyad University, Marrakech, Morocco
  • 6Atmo Hauts-de-France, Lille, France

Abstract. A better understanding of the hydrological functioning of irrigated crops using remote sensing observations is of prime importance in the semi-arid areas where the water resources are limited. Radar observations, available at high resolution and revisit time since the launch of Sentinel-1 in 2014, have shown great potential for the monitoring of the water content of the upper soil and of the canopy. In this paper, a complete set of data for radar signal analysis is shared to the scientific community for the first time to our knowledge. The data set is composed of Sentinel-1 products and in situ measurements of soil and vegetation variables collected during three agricultural seasons over drip-irrigated winter wheat in the Haouz plain in Morocco. The in situ data gathers soil measurements (time series of half-hourly surface soil moisture, surface roughness and agricultural practices) and vegetation measurements collected every week/two weeks including above-ground fresh and dry biomasses, vegetation water content based on destructive measurements, cover fraction, leaf area index and plant height. Radar data are the backscattering coefficient and the interferometric coherence derived from Sentinel-1 GRDH (Ground Range Detected High resolution) and SLC (Single Look Complex) products, respectively. The normalized difference vegetation index derived from Sentinel-2 data based on Level-2A (surface reflectance and cloud mask) atmospheric effects-corrected products is also provided. This database, which is the first of its kind made available in open access, is described here comprehensively in order to help the scientific community to evaluate and to develop new or existing remote sensing algorithms for monitoring wheat canopy under semi-arid conditions. The data set is particularly relevant for the development of radar applications including surface soil moisture and vegetation parameters retrieval using either physically based or empirical approaches such as machine and deep learning algorithms. The database is archived in the DataSuds repository and is freely-accessible via the DOI: https://doi.org/10.23708/8D6WQC (Ouaadi et al., 2020a).

Nadia Ouaadi et al.

Status: open (until 04 Mar 2021)

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Nadia Ouaadi et al.

Data sets

C-band radar data and in situ measurements for the monitoring of wheat crops in a semi-arid area (center of Morocco) Nadia Ouaadi, Jamal Ezzahar, Saïd Khabba, Salah Er-Raki, Adnane Chakir, Bouchra Ait Hssaine, Valérie Le Dantec, Zoubair Rafi, Antoine Beaumont, Mohamed Kasbani, and Lionel Jarlan https://doi.org/10.23708/8D6WQC

Nadia Ouaadi et al.

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Short summary
In this paper, a radar remote sensing database composed of processed Sentinel-1 products and field measurements of soil and vegetation characteristics, weather data and irrigation water inputs is described. The data set is collected during three years (2016–2019) on three drip irrigated wheat fields in the center of Morocco. It is dedicated to radar data analysis over vegetated surface including the retrieval of soil and vegetation characteristics.