## 3 Results
### Relationships between Time-Series SAR Signatures and the Timing of Field Activities  
The focus of this study was to estimate crop seeding and harvest dates through change detection based on the analysis of time-series InSAR data. This is built on an assumption that surface roughness or structural conditions of crop fields can be altered by seeding or harvest operations and captured by time-series SAR backscattering and InSAR coherence. However, SAR signals are also affected by other factors, such as soil moisture, precipitation, canopy structural changes associated with plant growth, as well as radar acquisition geometry, although not an issue for Sentinel-1 since by design the interferometric acquisition geometry is kept constant. When interpreting time-series SAR data for crop seeding and harvest date estimation, we took the following aspects into consideration:  
(1) VV is mainly related to surface roughness (either soil or upper canopy of the plant), thus can be inspected to infer information on tillage types during the seeding or harvest period when contribution from living plant tissues is relatively small. (2) For C band, VH is mainly responsive to volumetric scattering and is positively related to the amount of plant tissues; therefore, its signal level is low during seeding to early season and during harvest period. VH tends to reach the highest at full vegetative development stage. This is because the VH polarization mainly reflects the interaction of microwave with the interior parts of the canopy (e.g., volume scattering; [PERSON], et al. (2014)), although a double bounce component has been observed by [PERSON] and [PERSON] (2016) for flooded vegetation. (3) InSAR coherence reflects the local phase spatial similarity of two SAR images, which was evaluated within a spatial window of \(3\times 3\) pixels from an interferogram in this study. A high coherence obtained from a pair of SAR images indicates no change during the period between the two acquisition dates, whereas a low coherence indicates a change has occurred. The coherence levels of two consecutive InSAR pairs can be inspected to infer a change due to field operations. If two interferograms are created from three consecutive SAR scenes, the following scenarios could happen:  
* high-high: no change;
* high-low: change in second InSAR period;
* low-high: change in first InSAR period;
* low-low: continuous change. It is noted that low coherence in general is not necessarily indicative of a change at all time since geometric decorrelation can happen for vegetated surface even when there is no temporal change. As examples, Figure 6a-d depicts time-series InSAR data and the observed seeding and harvest dates for barley, canola, soybean and oats fields, and Figure 7 shows the corresponding post-harvest field photos taken on October 9, 25, 10, and 8, respectively. Pre-harvest photos were taken in the barley and oats field only, on September 16 and August 26, respectively. These four crops are selected for illustrations here because they have quite distinct structures during their life cycles. Average VV and VH and InSAR coherence of the three fields exhibit temporal patterns similar to that outlined in Figures 3-5. For the four crops, the VH showed a greater difference between the mid-season and the start/end of the season. This variation pattern followed the variation of amount of fresh biomass present in the field during the growing season, i.e., increase at the growing phase and decrease at the senescent phase. The VV showed a greater dynamic range at the early (May-June) and late (October) growth periods than the VH, possibly because it responded more to vertical structures (such as stems that start developing in the spring and drying up in the fall). Figure 6: Time-series SAR data and seeding/harvest dates for example fields of (**a**) barley, (**b**) canola, (**c**) soybean and (**d**) oats. Vertical blue lines mark the observed seeding date (dashed) and harvest date (solid).