Zhang (2025) An Automated Labeling Method for Lakes from Remote Sensing Images Guided by Visual and Structural Features

Identification

• Journal: Mendeley Data
• Year: 2025
• Date: 2025-12-11
• Authors: Zhang, Yiqing
• DOI: 10.17632/c8z6v284s8.1

Research Groups

Yiqing Zhang (Contributor)

Short Summary

The paper introduces an automated method for lake labeling in remote sensing images using visual and structural features, with an accompanying dataset provided for its evaluation.

Objective

• To develop and evaluate an automated method for labeling lakes in remote sensing images, guided by visual and structural features.

Study Configuration

• Spatial Scale: Image patches capturing diverse lake types with variations in size, morphology, brightness, and background complexity.
• Temporal Scale: Not specified.

Methodology and Data

• Models used: An automated lake-labeling framework based on visual and structural features.
• Data sources: Raw remote sensing image patches and corresponding lake masks.

Main Results

The provided text describes a dataset for evaluating a method; the results of the method's evaluation are not presented here.

Contributions

The dataset provides a valuable resource for the development and standardized evaluation of automated lake-labeling methods from remote sensing imagery.

Funding

Not specified in the provided text.

Citation

@article{Zhang2025Automated,
  author = {Zhang, Yiqing},
  title = {An Automated Labeling Method for Lakes from Remote Sensing Images Guided by Visual and Structural Features},
  journal = {Mendeley Data},
  year = {2025},
  doi = {10.17632/c8z6v284s8.1},
  url = {https://doi.org/10.17632/c8z6v284s8.1}
}