# Analysis of Maize Sowing Periods and Cycle Phases Using Sentinel 1&2 Data Synergy
## 4 Conclusions  
The sowing period has been proven to have an important impact on the yield of many of the most common crops, especially cereals. Moreover, the shifting of agricultural sowing periods is increasingly used as an adaptation strategy to climate change. In this work, the reliability of Earth Observation to retrieve maize sowing periods was tested, analyzing a pattern of 1154 fields within a 30 km \(\times\) 30 km area in Piedmont (North-West Italy) for year 2019. Radar and optical acquisitions from Sentinel-1 and Sentinel-2, respectively, were used to classify maize fields and to detect crop emergence through the soil, building up the spatial distribution of sowing periods at the field scale. For this reason, a SAR-based normalized index (named Polarimetric Ratio Index, IPR) was proposed in this study, in order to detect the geometric changes on ground surface induced by maize emergence. Results show that in 2019 maize was sown within April and May: about 52% of maize hectares were sown between April 25 th and 30 th, and 31% from May 13 th to the end of May. The late sowings are more frequent at higher elevations: a moderate correlation was found between emergence delay and elevation above the sea level (Pearson correlation coefficient, R = 0.41). The maize sowed in May at lower elevations is likely cultivated on those fields where winter crops are harvested in late spring, according to a widespread agricultural practice in this area. The comparison with actual data of local sowing practices highlights a good alignment with sowing periods occurring in the Po Valley in previous years (period 2005-2007). Results fit well with the sowing periods declared by local farmers within a survey conducted by the authors, in which the second half of April and May were indicated as the two main sowing periods. Results from this study are also well aligned to the most widely used comprehensive crop calendars, such as the global dataset of sowing periods proposed by FAO. Although the combined use of SAR polarizations has been previously used for agricultural applications, the novelty of this approach relies on the use of a normalized SAR-based index, which allows filtering out the effect of bare soil and clearer detection of the signals induced by crop growth. Further analyses combining more satellite constellations and ground information for validation, could exploit the EO-based methodology proposed in this study to assess more precise sowing periods for various crops. For the future, even temperate areas are expected to suffer lack of water and yield losses, because of changes in the precipitation regimes and withdrawable water for irrigation. Remote sensing is a very useful tool to support effective adaptation strategies to climate change, especially in those regions where new agricultural mindsets are increasingly required. The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/rs14153712/s1](https://www.mdpi.com/article/10.3390/rs14153712/s1)]([https://www.mdpi.com/article/10.3390/rs14153712/s1](https://www.mdpi.com/article/10.3390/rs14153712/s1)). Conceptualization, M.Z. and M.R. ; methodology, M.Z. and M.R. ; software and resources, M.R., M.Z. and E.A. ; data curation, N.B. and M.R. ; writing--original draft preparation, M.R. ; writing--review and editing, M.Z., S.T. and P.C. ; supervision, M.Z., S.T. and P.C. All authors have read and agreed to the published version of the manuscript. This research was funded through the 4000126684/19/I-NB CCN3 ESA project. The research funds covered the visiting period spent by the first author at CESBIO (Centre d'Etudes Spatiales de la Biosphere, Toulouse, FR). The data that support the findings of this study are openly available. The source of each dataset is detailed in Section 2, including links and references. No lab/field measurements were performed to achieve the aims of this study.