AUTHOR=Chen Youkuo , Guo Yan , Qiao Longxin , Xia Haoming TITLE=Coupling optical and SAR imagery for automatic garlic mapping JOURNAL=Frontiers in Sustainable Food Systems VOLUME=6 YEAR=2022 URL=https://www.frontiersin.org/journals/sustainable-food-systems/articles/10.3389/fsufs.2022.1007568 DOI=10.3389/fsufs.2022.1007568 ISSN=2571-581X ABSTRACT=

Accurate garlic identification and mapping are vital for precise crop management and the optimization of yield models. However, previous understandings of garlic identification were limited. Here, we propose an automatic garlic mapping framework using optical and synthetic aperture radar (SAR) images on the Google Earth Engine. Specifically, we firstly mapped winter crops based on the phenology of winter crops derived from Sentinel-2 data. Then, the garlic was identified separately using Sentinel-1 and Sentinel-2 data based on the winter crops map. Additionally, multi-source validation data were used to evaluate our results. In garlic mapping, coupled optical and SAR images (OA 95.34% and kappa 0.91) outperformed the use of only optical images (OA 74.78% and kappa 0.50). The algorithm explored the potential of multi-source remote sensing data to identify target crops in mixed and fragmented planting regions. The garlic planting information from the resultant map is essential for optimizing the garlic planting structure, regulating garlic price fluctuations, and promoting a healthy and sustainable development of the garlic industry.