# Near-Surface and High-Resolution Satellite Time Series for Detecting Crop Phenology
## 3 Results
### Concordance between Near-Surface Phenology and Visual Assessment  
The 57 PhenoCam site-year photos were visually interpreted via a consistent protocol. The crop emergence dates ranged from DOY 125 to 180 (corn: DOY 125 to 180; soybean: DOY 144 to 178). The crop maturity dates ranged from DOY 242 to 304 (corn: DOY 242 to 304; soybean: DOY 243 to 280). Among all the transition metrics, the CUR-based Greenup and Gu-based UD estimates showed higher degrees of concordance to crop emergence visual observations across sites and years, compared to TRS- and DER-based SOS metrics (Figure 6 and Table 2). Upon comparison to all the corn and soybean emergence observations, the estimated CUR-based Greenup dates were about within one week difference (RMSE = 6.518 days), with most of the comparison points (red dots in Figure 6) distributed along the one-to-one line (bias = 1.51 days). About 77% of the spatiotemporal variance of the emergence observations could be explained by the CUR-based Greenup estimates. Similarly, the Gu-based UD estimates were linearly correlated with the visually observed crop emergence dates, with corresponding R square equal to 0.766, bias being 5.999 days, and RMSE being 8.624 days. The TRS- and DER-based SOS measures, however, were about three weeks delayed from visual observations (about 20 days for both RMSE and bias). With these two metrics, most of the comparison points deviated from the one-to-one line, and the metric dates were much later than the observed ones in PhenoCam photos. The relationships between PhenoCam and visual assessments were further analyzed for corn and soybean separately. For corn, the average difference between the CUR-based Greenup estimates and visual estimates was within one week (RMSE = 5.655 days), and the corresponding bias was about 1 day. The variation in corn visual emergence across PhenoCam sites and years could be captured by the Greenup estimates with an R square value of 0.747. Similar comparison results were also found in the Gu-based UD estimates (i.e., R square = 0.751, RMSE = 8.166 days, and bias = 5.658 days). The TRS- and DER-based SOS measures had relatively large differences compared to visual observations (about 18 days for both RMSE and bias). Comparable to corn transition date estimates, the soybean CUR-based Greenup and Gu-based UD metrics were about one week different from visually observed emergence dates (RMSE = 8.557 days for Greenup and RMSE = 9.911 days for UD), and those metrics could explain more than 70% of the variation in observed soybean emergence over space and time. The TRS- and DER-based SOS estimates, on the other hand, were more than three weeks away from visual soybean phenological references, with most of the comparison points deviating from the one-to-one line. Both the collective and separate analysis of crop species indicated that the visual change in photos caused by the emergence of crops could be closely linked with CUR- and Gu-based characteristic phenology from the photo-derived GCC seasonal trajectory. Figure 6: The comparisons between the PhenoCam GCCbased transition date estimates of the greenness rising period and the visually observed emergence for (**a**) both corn and soybean, (**b**) corn, and (**c**) soybean, using the four phenophase analysis methods. We also compared the phenological transition date retrievals in the downward seasonal trajectory with visually observed crop maturity dates for all the PhenoCam observations. Among all the retrieval metrics, the TRS- and DER-based EOS measures exhibited better congruence with crop maturity visual observations across PhenoCam sites, compared to CUR-based Dormancy and Gu-based RD estimates (Figure 7). The retrieved EOS estimates of all the corn and soybean sites were aligned with visually observed mature dates, with RMSE around 5 days, almost no bias, and R square about 0.75.