Detecting irrigation events using Sentinel-1 data

Hassan Bazzi (1) , Nicolas Baghdadi (1) , Ibrahim Fayad (1) , Mehrez Zribi (2) , Valérie Demarez (2) , Yann Pageot (2) , Hatem Belhouchette (3, 4)

1 UMR TETIS - Territoires, Environnement, Télédétection et Information Spatiale
2 CESBIO - Centre d'études spatiales de la biosphère
3 CIHEAM-IAMM - Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier
4 UMR ABSys - Agrosystèmes Biodiversifiés

Better management of water consumption in irrigated agriculture is essential in order to save water resources. The objective of this study is to propose a new model capable of detecting the irrigation events using the Sentinel-1 (S1) Cband SAR (synthetic-aperture radar) in a near real-time approach. The proposed irrigation detection model relies on the change detection in the S1 backscattering coefficients at plot scale. A tree-based approach has been constructed to detect irrigation events by studying the behavior of the S1 backscattering coefficients following irrigation events at plot scale over three study sites located in Montpellier (southeast France), Tarbes (southwest France) and Catalonia (northeast Spain). Auxiliary data such as the NDVI (Normalized Difference Vegetation Index) and the soil moisture estimations were integrated as additional filters to reduce ambiguities related to vegetation growth and surface roughness. The results shows that the proposed model was capable of detecting 84% of the irrigation events over Montpellier. Over Catalonia site, 90.2% of the non-irrigated plots had no detected irrigation events whereas 72.4% of the irrigated plots had one and more detected irrigation events. In Tarbes, the analysis shows that irrigation events could still be detected even in the presence of abundant rainfall events during the summer season.

Mots clés: Irrigation Events; Sentinel-1; Change Detection; Near real-time

Domaines: Sciences de l'environnement

Hassan Bazzi, Nicolas Baghdadi, Ibrahim Fayad, Mehrez Zribi, Valérie Demarez, et al.. Detecting irrigation events using Sentinel-1 data. IGARSS 2021, Jul 2021, Bruxelles, Belgium. pp.6355-6358, ⟨10.1109/IGARSS47720.2021.9553587⟩. ⟨hal-03342931⟩