# Detecting Cover Crop End-Of-Season Using VEN\(\upmu\)S and Sentinel-2 Satellite Imagery
## 4 Results
### Near-Real-Time Mapping
In the last simulation (Figure 11n) ending on 31 July 2019, a termination date of 26 July 2019, was identified for field #5-9 (alfalfa). The recorded termination date was on 27 July 2019. It was the third detected termination date and the third recorded harvest date for this alfalfa field. In the simulation, all harvest events were detected correctly except for fields #5-21 and #5-45, which show some mixed termination dates from the two harvests. For field #5-21, some terminations were not detected, as illustrated in Figure 12c. For field #5-45, false detections were found for some pixels (Figure 11g-k) between two harvests (29 April 2019 and 13 July 2019). A small peak for field #5-45 was also shown in Figure 7d in early June but was not detected as a termination because the  
Figure 11: Cover crop termination maps from the 14 weekly near-real-time simulations ((**a**–**n**), ending dates below subfigures) using VENuS images. Cover crop field names (yellow text) are shown in (**a**). Newly detected termination dates from six fields are shown beside the field (white text). downward momentum and the amplitude of NDVI were not substantial at the field level. The lag time of detection ranges from 3-12 days in the weekly simulation process. To investigate the capability of the WIST approach, we ran the near-real-time simulation daily for cover crop fields at field level (same dataset used as in Sections 4.2 and 4.3) using VEN\(\upmu\)S data from both 2019 and 2020. Figure 13 shows the recorded harvest/mowing operation dates, the simulation ending dates of the first stable detection, and the detected termination dates using VEN\(\upmu\)S and Sentinel-2. All stable detections (same termination dates for at least a week) in the near-real-time simulations came from the first few detections, which means that early detected termination dates from the WIST algorithm are reliable. The thresholds for the MACD momentum (>0.01) and the NDVI amplitude (>0.15) are effective in our study area. In Figure 13, both VEN\(\upmu\)S and Sentinel-2 captured the termination dates close to the recorded harvest/termination dates shortly after the machinery operation. VEN\(\upmu\)S time-series detected all termination events while the Sentinel-2 time-series missed three in the near-real-time simulation. The average biases of remote sensing estimations were 0.4 day from VEN\(\upmu\)S and 1.5 days from Sentinel-2. The average lag times of detection were about 4 days for VEN\(\upmu\)S and 8 days for Sentinel-2. Note that in the simulation, we have not considered the lag time of satellite data acquisition and processing. The total lag time of the near-real-time detection should be the sum of lag time from the WIST algorithm and the latency from satellite data acquisition and pre-processing. Figure 12: Three examples from the near-real-time simulation from field #5-8 on 29 May (**a**), the OPE3 site on 12 June (**b**), and field #5-21 on 31 July (**c**), for explaining the weekly results in Figure 11e,g,n, respectively. Vertical red lines show the recorded harvest dates. Figure 13: The recorded harvest/termination operation dates, the detected termination dates, and the ending dates (the last day used in the simulation) from VEN\(\upmu\)S (_V) and Sentinel-2 (_S) in the daily near-real-time simulation for 29 harvests (_x_-axis) in 2019 and 2020. The _x_-axis shows the field name of each harvest. The dashed line separates harvests in 2019 and 2020.