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A Multi-Feature Fusion-Based Two-Stage Method for Airport Crater Extraction from Remote Sensing Images.

Yalun Zhao1, Derong Chen1, Jiulu Gong1

  • 1School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China.

Entropy (Basel, Switzerland)
|December 24, 2025
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Summary
This summary is machine-generated.

This study introduces a novel two-stage method for accurately extracting airport runway craters from remote sensing images. The approach effectively handles challenging conditions like shadows and irregular crater edges, improving damage assessment.

Keywords:
crater extractiondamage information extractionimage processingmulti-feature

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Area of Science:

  • Remote Sensing
  • Geospatial Analysis
  • Image Processing

Background:

  • Accurate extraction of airport runway damage is vital for operational planning.
  • High entropy images with dark interference (trees, shadows) and irregular crater edges challenge crater detection.

Purpose of the Study:

  • To develop a robust method for extracting airport craters from remote sensing images.
  • To improve the accuracy of damage assessment and operational planning.

Main Methods:

  • A two-stage method combining multi-feature fusion.
  • Stage I: Edge arc segment grouping and matching based on crater shape.
  • Stage II: Crater modeling using regional distribution and marked point processing with a near-region search strategy for edge gradients.

Main Results:

  • Achieved high recall (R) and precision (P) for crater extraction around runways (89% R, 87% P) and within runways (94% R, 92% P).
  • The proposed method demonstrated superior performance compared to existing algorithms in both recall and precision.

Conclusions:

  • The multi-feature fusion two-stage method accurately extracts airport craters, even in challenging image conditions.
  • This technique enhances the reliability of damage information for subsequent assessment and planning.