# Near-Surface and High-Resolution Satellite Time Series for Detecting Crop Phenology
## 4 Discussion
The establishment of the PhenoCam and other phenology camera-relevant networks has largely facilitated the phenological characterization of individual organisms to landscapes via near-surface remote sensing. With the PhenoCams, we conducted systematic and consistent visual crop phenological interpretations across agricultural sites, as well as retrieved canopy-level phenological metrics through the corresponding GCC time series. The PhenoCam photos, with the sub-daily temporal resolution, enabled the high-quality visual assessment of crop emergence and maturity stages over space and time. For our study sites, the crops exhibited wide ranges of emergence dates (DOY 125 to 180) and maturity dates (DOY 242 to 304) with the visual assessment, due to varying weather, soil, and management conditions of those sites. This visual assessment overcame the labor-intensive issue of field phenological observations, broadened the spatial coverage, and enhanced the connections with pheno-metrics from the GCC-based seasonal trajectory. The pheno-metrics, as shown in this study, could be characterized by different transition date analysis methods. The selection of the analysis methods affected the metric retrieval accuracy (e.g., RMSE, bias, and R square), and thus the correspondence with visually targeted crop phenological stages. The high degree of concordance between CUR-based Greenup and crop emergence (RMSE = 6.43 days, bias = 0.5 days, and R square = 0.73), and between DER-based EOS and crop maturity (RMSE = 5.31 days, bias = 0.85 days, and R square = 0.7), demonstrated the capability of PhenoCams in the fine-scale crop phenological characterizations for precise agricultural management. This could be further enhanced with the continually increasing phenology monitoring network on the global scale. With the unique roles of phenological interpretations and estimations, PhenoCams drastically facilitated the reconciliation of visual- and sensor-assessed crop phenology across broad spatial extents and helped tackle the long-standing challenge of interpreting the sensor-retrieved phenology in the crop growth and physiology-relevant context. The PlanetScope image time series opened the door for satellite-based crop phenological detection at both high spatial and temporal resolutions and provided unique opportunities to be linked with visual and near-surface crop phenology. Our analysis results indicated that the PlanetScope-derived phenological metrics showed consistent comparison patterns as those from the PhenoCams, with PlanetScope-derived CUR Greenup approaching crop emergence (RMSE = 8.35 days, bias = 5.28 days, and R square = 0.64), and DER EOS for crop maturity (RMSE = 9.92 days, bias = 8.16 days, and R square = 0.58). The good performance of these metrics demonstrated the potential of leveraging the PlanetScope imagery for satellite-based fine-scale phenological retrieval in direct connection with observed crop phenological stages. This connection, in terms of scale and representation, eased the challenge of satellite-based crop phenological validation, which was typically conducted using the satellite imagery of moderate- to coarse- spatial resolutions upon comparison to crop phenological reference at aggregated levels (e.g., district-level or state-level crop progress reports) [19]. It thus facilitated the identification of critical phenological transition dates that were characteristic of crop physiological growth stages using the satellite time series. The PlanetScope time series, with its spatial and temporal resolutions, provided an effective avenue for the fine-scale agricultural seasonal dynamic monitoring and management, though its scientific quality might not be as rigorous as that of other satellites (e.g., MODIS and Landsat) employed for phenological studies [59; 69]. Further inter-sensor radiometric calibrations of the PlanetScope imagery to improve the radiometric consistency would be desired in future studies [53].