Chantaveerod et al. (2025) Adaptive Physically Based Contour Framework for Robust and Efficient Catchment Estimation on Large-Scale Terrain Using Super-Resolution DEMs

Identification

• Journal: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
• Year: 2025
• Date: 2025-12-03
• Authors: Ajalawit Chantaveerod, Kampol Woradit, Andrew Seagar
• DOI: 10.1109/jstars.2025.3639901

Research Groups

[List the main research groups, labs, or departments involved in the study.]

Short Summary

This paper introduces an adaptive physically based contour framework designed for robust and efficient catchment estimation across large-scale terrains, leveraging super-resolution Digital Elevation Models.

Objective

• To develop and evaluate an adaptive physically based contour framework for robust and efficient catchment estimation on large-scale terrain, utilizing super-resolution Digital Elevation Models (DEMs).

Study Configuration

• Spatial Scale: Large-scale terrain
• Temporal Scale: [Description]

Methodology and Data

• Models used: Adaptive Physically Based Contour Framework
• Data sources: Super-Resolution Digital Elevation Models (DEMs)

Main Results

[Key findings, synthetic and quantitative]

Contributions

[Original value of the article with respect to existing literature]

Funding

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Citation

@article{Chantaveerod2025Adaptive,
  author = {Chantaveerod, Ajalawit and Woradit, Kampol and Seagar, Andrew},
  title = {Adaptive Physically Based Contour Framework for Robust and Efficient Catchment Estimation on Large-Scale Terrain Using Super-Resolution DEMs},
  journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  year = {2025},
  doi = {10.1109/jstars.2025.3639901},
  url = {https://doi.org/10.1109/jstars.2025.3639901}
}