Comparing land surface phenology of major European crops as derived from SAR and multispectral data of Sentinel-1 and -2

The frequent acquisitions of fine spatial resolution imagery (10 m) offered by recent multispectral satellite missions, including Sentinel-2, can resolve single agricultural fields and thus provide crop-specific phenology metrics, a crucial information for crop monitoring. However, effective phenology retrieval may still be hampered by significant cloud cover. Synthetic aperture radar (SAR) observations are not restricted by weather conditions, and Sentinel-1 thus ensures more frequent observations of the land surface. However, these data have not been systematically exploited for phenology retrieval so far. In this study, we first extracted crop-specific land surface phenology (LSP) from Sentinel-2 of major European crops (common and durum wheat, barley, maize, oats, rape and turnip rape, sugar beet, sunflower, and dry pulses). We used ground-truth information from the “Copernicus module” of the Land Use / Cover Area frame statistical Survey (LUCAS) of 2018 to focus on crop fields with homogenous and known crop type cover distributed over all the European Union territory. We then assessed if Sentinel-1 allows to obtain similar LSP retrievals over the same locations. We consistently used a single model-fit approach to retrieve LSP metrics on temporal profiles of CR (Cross Ratio, the ratio of the backscattering coefficient VH/VV from Sentinel-1) and NDVI (Normalized Difference Vegetation Index from Sentinel-2). Our analysis revealed that LSP retrievals from Sentinel-1 are comparable to those of Sentinel-2, particularly for winter crops. The start of season (SOS) timings, as derived from Sentinel-1 and -2, are significantly correlated (average r of 0.78 and 0.46 for winter and summer crops, respectively). The correlation is lower for end of season retrievals (EOS, r of 0.62 and 0.34). Agreement between LSP derived from Sentinel-1 and -2 varies among crop types, ranging from r = 0.89 and mean absolute error MAE = 10 days (SOS of dry pulses) to r = 0.15 and MAE = 53 days (EOS of sugar beet). Observed deviations revealed that Sentinel-1 and -2 LSP retrievals can be complementary; for example for winter crops we found that SAR detected the start of the spring growth while optical data is sensitive to the crop growth occurring before and during winter. To test if our results correspond reasonably to in-situ data, we compared average crop-specific LSP for Germany to average phenology from ground phenological observations of 2018 gathered from the German Meteorological Service (DWD). Our study demonstrated that both Sentinel-1 and -2 can provide relevant and at times complementary LSP information at field- and crop-level.

MERONI Michele;  D'ANDRIMONT Raphael;  VRIELING A.;  FASBENDER Dominique;  LEMOINE Guido;  REMBOLD Felix;  SEGUINI Lorenzo;  VERHEGGHEN Astrid; 

2020-12-18

ELSEVIER SCIENCE INC

JRC120984

0034-4257 (online),   

https://www.sciencedirect.com/science/article/pii/S0034425720306052?via%3Dihub,    https://publications.jrc.ec.europa.eu/repository/handle/JRC120984,   

10.1016/j.rse.2020.112232 (online),