{
  "id": 5036,
  "url": "https://arxiv.org/abs/2605.02153v1",
  "title": "Cross-Polarization Fusion of VV AND VH SAR Observations for Improved Flood Mapping",
  "summary": "Synthetic Aperture Radar (SAR) imagery is widely used for flood monitoring due to its all-weather and day-night imaging capability. However, flood mapping using single-polarization SAR data remains challenging in complex environments where surface and volume scattering coexist. In this paper, we investigate the effectiveness of cross-polarization fusion of VV and VH SAR observations for improved flood mapping. A deep learning-based segmentation framework is employed to jointly exploit complement",
  "authors": "Jagrati Talreja, Tewodros Syum Gebre, Leila Hashemi Beni",
  "category": "research",
  "topics": "environment,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-04T02:35:48.000Z",
  "fetched_at": "2026-07-14T16:31:26.337Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/5036",
  "original_url": "https://arxiv.org/abs/2605.02153v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}