Cordeiro et al. (2026) Assessing SWOT's capability for surface water extent mapping: An evaluation of Level-2 High-Rate Raster water fraction

Identification

• Journal: Remote Sensing of Environment
• Year: 2026
• Date: 2026-08-02
• Authors: Maurício C. R. Cordeiro, Mohammad J. Tourian, Santiago Peña Luque, Renato Prata de Moraes Frasson, Daniel Medeiros Moreira, Fabrice Papa, Tati de Almeida
• DOI: 10.1016/j.rse.2026.115595

Research Groups

• Agˆencia Nacional de ´Aguas (ANA)
• Institute of Geodesy, University of Stuttgart
• Centre National d'Etudes Spatiales (CNES)
• Jet Propulsion Laboratory, California Institute of Technology
• Geological Survey of Brazil
• Laboratoire d'Etudes en G´eophysique et Oc´eanographie Spatiales (LEGOS), Universit´e Toulouse, IRD, CNRS, CNES, UT
• University of Brasília (UnB)

Short Summary

This study assesses the Surface Water and Ocean Topography (SWOT) mission's capability for surface water extent mapping using Level-2 High-Rate Raster water fraction data. The results show a systematic positive bias in water fraction analysis and highlight limitations of the KaRIn sensor.

Objective

• Evaluate the accuracy of SWOT-derived surface water extent maps compared to higher-resolution Sentinel-2-derived reference masks.

Study Configuration

• Spatial Scale: Global (Brazilian regions)
• Temporal Scale: Not specified

Methodology and Data

• Models used: None mentioned
• Data sources: Level-2 High-Rate Raster water fraction data from SWOT, Sentinel-2 imagery, OPERA Dynamic Surface Water Extent Products (DSWx-HLS and DSWx-S1)

Main Results

• Systematic positive bias in water fraction analysis, largest over Evergreen Broadleaf Forest and smallest over open Water Bodies.
• Best-performing threshold for converting water fraction values into binary water masks is 0.56.
• SWOT performance varies regionally, poorest over scenes with narrow channels, flat water surfaces, and near-nadir regions.

Contributions

• This study provides a systematic evaluation of the L2-HR-Raster raster product's capability for surface water extent mapping, highlighting its limitations and potential applications.

Funding

• Not specified

Citation

@article{Cordeiro2026Assessing,
  author = {Cordeiro, Maurício C. R. and Tourian, Mohammad J. and Luque, Santiago Peña and Frasson, Renato Prata de Moraes and Moreira, Daniel Medeiros and Papa, Fabrice and Almeida, Tati de},
  title = {Assessing SWOT's capability for surface water extent mapping: An evaluation of Level-2 High-Rate Raster water fraction},
  journal = {Remote Sensing of Environment},
  year = {2026},
  doi = {10.1016/j.rse.2026.115595},
  url = {https://doi.org/10.1016/j.rse.2026.115595}
}