Skip to Main content Skip to Navigation
Conference papers

Detecting Irrigation Events Using Sentinel-1 Data

Abstract : 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.
Document type :
Conference papers
Complete list of metadata

https://hal.inrae.fr/hal-03342931
Contributor : Isabelle Nault <>
Submitted on : Monday, September 13, 2021 - 4:38:22 PM
Last modification on : Tuesday, September 14, 2021 - 3:42:34 AM

File

IGARSS2021_bazzi.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-03342931, version 1

Citation

Hassan Bazzi, Nicolas Baghdadi, Ibrahim Fayad, Mehrez Zribi, Valerie Demarez, et al.. Detecting Irrigation Events Using Sentinel-1 Data. IGARSS 2021, Jul 2021, Brussels, France. ⟨hal-03342931⟩

Share

Metrics

Record views

36

Files downloads

6