Retrieving Soil Moisture from Sentinel-1: Limitations over Certain Crops and Sensitivity to the First Soil Thin Layer

Archive ouverte

Bazzi, Hassan | Baghdadi, Nicolas | Nino, Pasquale | Napoli, Rosario | Najem, Sami | Zribi, Mehrez | Vaudour, Emmanuelle

Edité par CCSD ; MDPI -

International audience. This paper presents a comparison between the Sentinel-1 (S1)/Sentinel-2 (S2)-derived soil moisture products at plot scale (S2MP) and in situ soil moisture measurements at a 10 cm depth for several winter and summer crops. Specifically, the paper discusses the consistency between the in situ soil moisture measurements, usually performed at a 10 cm soil depth, and the variable S1 C-band penetration depth in soil due to soil humidity conditions, vegetation development and S1 acquisition configuration. The aim is to provide end users with the strength and limitations of S1-derived soil moisture, mainly the S2MP soil moisture product, for their further applications. Both the estimated and measured soil moisture (SM) were evaluated over three testing fields in a Mediterranean climatic context, with crop cycles including wheat, tomato, cover crops and soybeans. The main results showed that the comparison between the S2MP-estimated SM based on S1 backscattering (at ~5 cm depth) with a 10 cm in situ SM is not always relevant during the crop cycle. In dry conditions, the S1 SM significantly underestimated the 10 cm SM measurements with an underestimation that could reach around 20 vol.% in some extremely dry conditions. This high underestimation was mainly due to the difference between the topsoil SM captured by the S1 sensor and the 10 cm in depth SM. Moderately wet conditions due to rainfall or irrigation showed less of a difference between the S1-estimated SM and the 10 cm in situ SM and varying between −10 and −5 vol.% due to the homogeneity of the SM at different soil depths. For extremely wet conditions, the S1 SM started to underestimate the SM values with an underestimation that can reach an order of −10 vol.%. A comparison of the S1-estimated SM as a function of the vegetation development showed that, for the studied crop types, the S1 SM estimates are only valid for low and moderate vegetation cover with a Normalized Difference Vegetation Index (NDVI) of less than 0.7. For dense vegetation cover (NDVI > 0.7), overestimations of the SM (average bias of about 4 vol.%) are mainly observed for developed tomato and soybean crops due to fruits’ emergence, whereas an extreme underestimation (average bias reaching −15.5 vol.%) is found for developed wheat cover due to the vertical structure of the wheat kernels. The results also suggest that the optimal SM estimations by S1 could be mainly obtained at low radar incidence angles (incidence angle less than 35°).

Suggestions

Du même auteur

Artificial Intelligence Algorithms for Rapeseed Fields Mapping using Sentinel-1 Time Series: Temporal Transfer Scenario and Ground Sampling Constraints

Archive ouverte | Maleki, Saeideh | CCSD

International audience. Accurate crop type information is of paramount importance for decision makers. This paper focuses on refining rapeseed field detection. This goal is achieved by creating high accuracy rapesee...

Handling soil moisture in remote sensing: perspectives from the STEROPES project

Archive ouverte | Vaudour, Emmanuelle | CCSD

International audience. Objective: to test the potential to use satellite images to predict soil organic carbon (SOC) content in agricultural soils across Europe.

Potential of Sentinel-1 Images for Estimating the Soil Roughness over Bare Agricultural Soils

Archive ouverte | Baghdadi, Nicolas | CCSD

[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-ATTOS. The purpose of this study is to analyze the potential of Sentinel-1 C-band SAR data in VV polarization for estimating the surface roughne...

Chargement des enrichissements...