Mirandilla et al. (2025) Phenological Monitoring and Discrimination of Rice Ecosystems Using Multi-Temporal and Multi-Sensor Polarimetric SAR

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Identification

• Journal: Remote Sensing
• Year: 2025
• Date: 2025-12-11
• Authors: Jean Rochielle F. Mirandilla, M. Yamashita, Mitsunori Yoshimura
• DOI: 10.3390/rs17244007

Research Groups

• [Not specified in the provided text]

Short Summary

This study developed a method using multi-temporal polarimetric dual-polarization SAR data from Sentinel-1B and ALOS PALSAR-2 to monitor and discriminate irrigated and favorable rainfed rice ecosystems. The integration of backscatter and polarimetric parameters from both sensors achieved an 81.81% overall accuracy in distinguishing these two rice types.

Objective

• To monitor and discriminate irrigated and favorable rainfed rice ecosystems in the province of Iloilo, Philippines, using multi-temporal polarimetric dual-polarization SAR data from Sentinel-1B and ALOS PALSAR-2.

Study Configuration

• Spatial Scale: Province of Iloilo, Philippines (regional scale)
• Temporal Scale: Multi-temporal (spanning rice phenological stages)

Methodology and Data

• Models used: H–A–α decomposition, model-based dual-pol decomposition, Segmented regression, Random Forest classifier.
• Data sources: Multi-temporal polarimetric dual-polarization (dual-pol) Synthetic Aperture Radar (SAR) data from Sentinel-1B and ALOS PALSAR-2 satellites.

Main Results

• Sentinel-1B polarimetric parameters (entropy, anisotropy, and alpha) effectively captured rice phenological dynamics.
• ALOS PALSAR-2 polarimetric parameters (span and volume scattering) were more sensitive to water conditions.
• Irrigated rice exhibited more stable and predictable scattering patterns compared to favorable rainfed rice.
• The highest classification accuracy for discriminating between irrigated and favorable rainfed rice was 81.81% (overall accuracy; Kappa = 0.6345), achieved by combining backscatter (Sentinel-1B VH, ALOS PALSAR-2 HH, and HV) and polarimetric parameters from both sensors.

Contributions

• Demonstrated a novel method for separately monitoring and discriminating irrigated and favorable rainfed rice ecosystems using multi-temporal polarimetric dual-polarization SAR data.
• Highlighted the distinct capabilities of Sentinel-1B (phenology) and ALOS PALSAR-2 (water conditions) polarimetric parameters for rice characterization.
• Showcased the improved discrimination accuracy achieved by integrating data and parameters from both Sentinel-1B and ALOS PALSAR-2 sensors.

Funding

• [Not specified in the provided text]

Citation

@article{Mirandilla2025Phenological,
  author = {Mirandilla, Jean Rochielle F. and Yamashita, M. and Yoshimura, Mitsunori},
  title = {Phenological Monitoring and Discrimination of Rice Ecosystems Using Multi-Temporal and Multi-Sensor Polarimetric SAR},
  journal = {Remote Sensing},
  year = {2025},
  doi = {10.3390/rs17244007},
  url = {https://doi.org/10.3390/rs17244007}
}