The influence of Sentinel-1 SAR sub-swath on the recorded backscatter time-series over managed hemiboreal forests

The Sentinel-1 SAR is a C-band radar on sun-synchronous polar orbit (Fletcher, 2012). Sentinel-1A has been on the orbit since 3 April 2014 and Sentinel-1B since 25 April 2016, while the 1B is not functional since December 2021 due to technical problems (ESA, 2022). The radar measures microwave backscatter using the Terrain Observation with Progressive Scans SAR (TOPSAR) method by electronically steering the radar antenna over target area while the satellite is moving in azimuth direction. Measurements are done using one of four configurations. The Interferometric Wide swath (IW) mode is commonly used for land surface targets. The full ground range swath of Sentinel-1 SAR in the IW-mode is divided into three sub-swaths (Fletcher, 2012; Hajduch et al., 2022).

The long Sentinel-1 SAR time series are used for prediction of soil moisture dynamics, for mapping of forests and other vegetation phenology (Van doninck et al., 2012; Dostálová et al., 2018; Rüetschi et al., 2018). One crucial step before using SAR backscatter (σ⁰) data for studies of vegetation properties is the correction or normalization of the signal for the local incidence angle (θ) that is a combination of the view angle, terrain slope and azimuth of the slope (Gauthier et al., 1998).

A frequently used method for normalizing SAR backscatter is to assume a linear relationship and convert the σ⁰ measured at angle θ to a value at some reference angle θ_ref

(1) σ0(θref)=σ0(θ)−β(θ−θref), $$\sigma ^0 \left( {\theta _{ref} } \right) = \sigma ^0 \left( \theta \right) - \beta \left( {\theta - \theta _{ref} } \right),$$

where β is the slope of the linear model fitted to σ⁰ data using the difference (θ − θ_ref) as a predictor variable (Gauthier et al., 1998; Van doninck et al., 2012; Dostálová et al., 2018; Schaufler et al., 2018). The σ⁰ (θ_ref) could be then used as a predictor variable forming dense time series for a particular target object from pixel values extracted from all overlapping image swaths viewed from different orbits.

The orbits of Sentinel-1 converge towards Earth poles and at higher latitudes it is possible to observe target objects from different orbits. In Estonia the image swaths from four to six orbits intersect on the ground. With the Sentinel-1A/1B pair on the orbit it is therefore possible during 72 hours to get three nighttime measurements and three daytime measurements for a forest stand so that an almost fullview angle range of Sentinel-1 SAR is covered in the triplets. We selected a 15 by 15 km test site near Laeva village, Estonia, in managed hemiboreal forests to study the applicability of the linear normalization (1) for the compilation of dense SAR time series.

By comparing the values of β estimated for orbit pairs we found that almost in all forest stands the mean value of σvv0$$\sigma _{vv}^0 $$ decreases more per unit angle in pairs with greater incidence angles (Figure 2). This was found in daytime as well as in nighttime measurements. If we assume that backscatter of microwave pulse follows a linear monotonous decrease through the usual SAR incidence angle range, then the application of the normalization model (1) would be justified. Based on this assumption, Van doninck et al. (2012) used the model (1) to normalize Advanced Synthetic Aperture Radar (ASAR) data from 80 descending passes and noted that all the observations for each image pixel were used for the model fitting. Dostálová et al. (2018) and Schaufler et al. (2018) used the model (1) for Sentinel-1 SAR data that covered large areas. In the case of Laeva Sentinel-1 SAR data set, however, (1) there is a systematic difference of backscatter from ascending and descending passes and (2) the angular correction coefficient β depends on the incident angle.

Figure 2.

The reason for the dependence of the angular correction coefficient β on the incident angle is not clear. It is possible that forward scattering increases with θ and relatively less energy is reflected back in the case of larger local incidence angles. However, it cannot be excluded that the empirical finding is related to the Sentinel-1 SAR construction and the usage of TOPSAR measurement method. In Laeva test site the stands were located on different subswaths in the image triplets (Appendix 2). Sentinel-1 SAR calibration and signal restoration for the image construction is done by the sub-swaths (Hajduch et al., 2022).

Our empirical finding may have importance for the construction of the normalized incidence angle of Sentinel-1 SAR backscatter time series for vegetation mapping and phenology studies. Fitting just a linear model on all Sentinel-1 SAR backscatter measurements over target to correct for incidence angle is not sufficient to remove the signal dependence on the influence of scanner subswath. In mapping and change detection applications the processing and decision-making accuracy may be increased if the effect of Sentinel-1 SAR subswath characteristics and the nighttime and daytime backscatter difference on the registered microwave pulse backscatter will be taken into account. Also, the 1B is not functional since December 2021 and this can create artefacts in long time series as the combination of sub-swaths over the targets is now different compared to the operational pair of Sentinel-1A and Sentinel-1B.