Mapping of Rice Varieties and Sowing Date Using X-Band SAR Data.

Area of Science:

• Agricultural Remote Sensing
• Geospatial Analysis
• Crop Monitoring

Background:

• Rice is a vital global food source, yet precise cultivation data is often lacking.
• Accurate field-level information on rice sowing dates and varieties is crucial for effective management and market assessment, especially in regions with diverse cropping patterns like the Mekong Delta.
• Existing methods for rice monitoring using Synthetic Aperture Radar (SAR) data have limitations in providing practical, user-specific information.

Purpose of the Study:

• To develop and assess methods using X-band SAR data for retrieving rice cultivation area, sowing dates, and differentiating between long and short cycle rice varieties.
• To address the need for detailed, field-specific agricultural information in complex cropping systems.
• To enhance the practical application of SAR data in rice production management and market analysis.

Main Methods:

• Utilized COSMO-SkyMed X-band SAR data acquired between August and November 2013 for specific districts in Vietnam.
• Analyzed SAR data, focusing on temporal and polarization behaviors of radar backscatter in relation to rice parameters.
• Developed novel backscatter indicators for detecting rice paddy areas, estimating sowing dates, and mapping rice varieties.

Main Results:

• Achieved 92% accuracy in identifying rice-grown areas.
• Demonstrated 96% accuracy in distinguishing between long and short cycle rice varieties.
• Estimated sowing dates with a root mean square error of 4.3 days.

Conclusions:

• The developed SAR-based methods provide accurate and practical information for rice cultivation monitoring.
• These techniques are valuable for field management, including irrigation, fertilization, and harvest timing.
• The findings support the broader application of SAR data in precision agriculture and market assessment for rice production.