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Although a vast literature exists on satellite-based mapping of rice paddy fields in Asia, where most of the global production takes place, little has been produced so far that focuses on the European context. Detection and mapping methods that work well in the Asian context will not offer the same performance in Europe, where different seasonal cycles, environmental contexts, and rice varieties make distinctive features dissimilar to the Asian case. In this context, water management is a key clue; watering practices are distinctive for rice with respect to other crops, and within rice there exist diverse cultivation practices including organic and non-organic approaches. In this paper, we focus on satellite-observed water management to identify rice paddy fields cultivated with a traditional agricultural approach. Building on established research results, and guided by the output of experiments on real-world cases, a new method for analyzing time-series of Sentinel-1 data has been developed, which can identify traditional rice fields with a high degree of reliability. Typical watering practices for traditional rice cultivation leave distinctive marks on the yearly sequence of spaceborne radar reflectivity that are identified by the proposed classifier. The method is tested on a small sample of rice paddy fields, built by direct collection of ground reference information. Automated setting of parameters was sufficient to achieve accuracy values beyond 90%, and scanning of a range of values led to touch full score on an independent test set. This work is a part of a broader initiative to build space-based tools for collecting additional pieces of evidence to support food chain traceability; the whole system will consider various parameters, whose analysis procedures are still at their early stages of development.

Mapping European Rice Paddy Fields Using Yearly Sequences of Spaceborne Radar Reflectivity: A Case Study in Italy