Garrido et al. (2026) A Scalable Method to Delineate Active River Channels and Quantify Cross-Sectional Morphology from Multi-Sensor Imagery in Google Earth Engine Using the Photo Intensive System for Channel Observation (PISCOb)

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Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-03-18
• Authors: Víctor Garrido, DIEGO CAAMAÑO, Daniel C. White, Hernán Alcayaga, Andrew W. Tranmer
• DOI: 10.3390/rs18060920

Research Groups

Not explicitly stated in the provided text.

Short Summary

This study developed and validated an automated Google Earth Engine workflow using multispectral indices from Landsat and Sentinel-2 to delineate active channel width, finding Sentinel-2 with MNDWI-EVI provided the highest accuracy and highlighting the importance of local geomorphic and ecological conditions for threshold selection.

Objective

• To develop and validate an automated, open-source workflow in Google Earth Engine (GEE) for delineating active channel width (ACW) from multispectral satellite imagery, addressing limitations of spatial and temporal spectral variability.

Study Configuration

• Spatial Scale: 34 km segment of the Lircay River, Chile.
• Temporal Scale: 20-year period (2003–2023).

Methodology and Data

• Models used: Google Earth Engine (GEE) workflow utilizing multispectral indices: Modified Normalized Difference Water Index (MNDWI), Normalized Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI).
• Data sources: Annual composite Landsat and Sentinel-2 imagery.

Main Results

• Sentinel-2 annual composites, particularly with the MNDWI-EVI pairing, achieved the highest overall accuracy in estimating ACW (mean Kling-Gupta Efficiency = 0.72; Percent Bias = 12.69 across study reaches).
• Using cross-section-specific thresholds significantly enhanced the accuracy of ACW estimation, indicating that threshold performance is strongly conditioned by local characteristics.
• Spectral threshold selection is sensitive to small-scale factors varying across the river corridor, emphasizing the need to explicitly consider local geomorphic and ecological conditions when defining thresholds.

Contributions

• Developed a reproducible, open-source workflow that links automated channel delineation with cross-section-based morphology.
• Explicitly quantifies uncertainty arising from spatiotemporal spectral variability in active channel width measurements.
• Enables high-resolution, repeatable measurements of river corridor change over time.
• Underscores the critical need to consider evolving spectral and vegetation conditions when interpreting remotely sensed geomorphic indicators.

Funding

Not explicitly stated in the provided text.

Citation

@article{Garrido2026Scalable,
  author = {Garrido, Víctor and CAAMAÑO, DIEGO and White, Daniel C. and Alcayaga, Hernán and Tranmer, Andrew W.},
  title = {A Scalable Method to Delineate Active River Channels and Quantify Cross-Sectional Morphology from Multi-Sensor Imagery in Google Earth Engine Using the Photo Intensive System for Channel Observation (PISCOb)},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18060920},
  url = {https://doi.org/10.3390/rs18060920}
}