Sentinel-1 Data for Winter Wheat Phenology Monitoring and Mapping

Abstract

The ability of Synthetic Aperture Radar (SAR) Sentinel-1 data to detect the main wheat phenological phases was investigated in the Bekaa plain of Lebanon. Accordingly, the temporal variation of Sentinel-1 (S1) signal was analyzed as a function of the phenological phases’ dates observed in situ (germination; heading and soft dough), and harvesting. Results showed that S1 data, unlike the Normalized Difference Vegetation Index (NDVI) data, were able to estimate the dates of theses phenological phases due to significant variations in S1 temporal series at the dates of germination, heading, soft dough, and harvesting. Particularly, the ratio VV/VH at low incidence angle (32–34°) was able to detect the germination and harvesting dates. VV polarization at low incidence angle (32–34°) was able to detect the heading phase, while VH polarization at high incidence angle (43–45°) was better than that at low incidence angle (32–34°), in detecting the soft dough phase. An automated approach for main wheat phenological phases’ determination was then developed on the western part of the Bekaa plain. This approach modelled the S1 SAR temporal series by smoothing and fitting the temporal series with Gaussian functions (up to three Gaussians) allowing thus to automatically detect the main wheat phenological phases from the sum of these Gaussians. To test its robustness, the automated method was applied on the northern part of the Bekaa plain, in which winter wheat is harvested usually earlier because of the different weather conditions. The Root Mean Square Error (RMSE) of the estimation of the phenological phases’ dates was 2.9 days for germination, 5.5 days for heading, 5.1 days soft dough, 3.0 days for West Bekaa’s harvesting, and 4.5 days for North Bekaa’s harvesting. In addition, a slight underestimation was observed for germination and heading of West Bekaa (−0.2 and −1.1 days, respectively) while an overestimation was observed for soft dough of West Bekaa and harvesting for both West and North Bekaa (3.1, 0.6, and 3.6 days, respectively). These results are encouraging, and thus prove that S1 data are powerful as a tool for crop monitoring, to serve enhanced crop management and production handling.

Comparing land surface phenology of major European crops as derived from SAR and multispectral data of Sentinel-1 and -2

“…Despite this noise, a distinct seasonality is observed for CR. This finding is in agreement with the observed crop temporal profiles of Mercier et al (2020) (wheat and rapeseed), Nasrallah et al (2019) (wheat) and with Frison et al (2018) and Proisy et al (2000) who studied the CR temporal behaviour over mixed temperate forests. In addition, CR temporal evolution coincides with that of NDVI derived from S2, depicting a VI increase in the early and late spring for winter and summer crops, and a sharp decrease in summer.…”

“…SOS50, PS90 and EOS50 timings derived from both NDVI and CR were correctly associated with early, intermediate and late stages of observed phenological development ( Table 4 ). Deviations of S1-derived SOS50 and EOS50 timings for wheat from BBCH 31 (early stem elongation, SOS50 delayed of 4.7 days) and BBCH 87 (late ripening, EOS50 delayed of 5.7 days) are comparable to those observed by Schlund and Erasmi (2020) for the same phenological stages using S1 CR and a different retrieval methods and to those of Nasrallah et al (2019) for the germination and harvesting stages using CR and a multiple-Gaussian model-fit approach. Using RADARSAT-2 and TerraSAR-X SAR data with a dynamic filtering framework to estimate BBCH stages of canola, McNairn et al (2018) obtained a similar error magnitude during vegetative stages but reported higher accuracies for inflorescence emergence and flowering.…”

“… Vreugdenhil et al, 2018 suggested the use of CR for crop monitoring as it minimises the effect of soil moisture and soil-vegetation interaction effects. Nasrallah et al (2019) detected wheat germination and harvesting dates in selected fields in Lebanon with CR (VV/VH in their work), while the use of VV and VH backscatter coefficients was preferred for the heading and soft dough dates, respectively. Likewise, Schlund and Erasmi (2020) showed the potential of CR for detecting the date of shooting and harvesting of selected wheat fields in Germany.…”

Assessment of Agricultural Practices From Sentinel 1 and 2 Images Applied on Rice Fields to Develop a Farm Typology in the Camargue Region

“…For 2017, as there were not sufficient Sentinel 2 data for the sowing period due to clouds and rain in spring, Sentinel 1 data have been used. The microwave signal presents a high sensitivity for the soil water content and roughness but is also influenced by vegetation density [30]. The temporal profiles of the ratio VH/VV has been chosen since [8,30] have shown their interesting potentialities for the phenology monitoring of various crops.…”

“…The microwave signal presents a high sensitivity for the soil water content and roughness but is also influenced by vegetation density [30]. The temporal profiles of the ratio VH/VV has been chosen since [8,30] have shown their interesting potentialities for the phenology monitoring of various crops. We noticed that the plots had higher values of VH/VV few days before the sowing date.…”