Method, system, device, and medium for detecting forest disturbances based on fully polarized SAR images

The method leverages full-polarization SAR images with preprocessing and optimized models to improve forest disturbance detection accuracy, addressing limitations in optical data availability and SAR image noise, enabling effective ecological monitoring.

JP7717301B1Active Publication Date: 2025-08-01MINISTRY OF ECOLOGY & ENVIRONMENT CENT FOR SATELLITE APPL ON ECOLOGY ENVIRONMENT
3 Cites 4 Cited by

Patent Information

Application Number
JP2025090577
Authority / Receiving Office
JP · JP
Patent Type
Patents
Current Assignee / Owner
Priority Date
2024-05-07
Filing Date
2025-05-30
Publication Date
2025-08-01
Estimated Expiration
2045-05-30

AI Technical Summary

Technical Problem

Current remote sensing technologies face challenges in accurately monitoring forest land disturbances due to limitations in optical image data availability in cloudy and rainy conditions, and SAR images are hindered by speckle noise, geometric distortion, and shadow, making it difficult to detect human activities effectively.

Method used

A method utilizing full-polarization SAR images for forest land disturbance detection, involving image classification, preprocessing with polarization matrix transformation, Refined Lee filtering, false color composition, and optimized surface change detection models, combined with radar vegetation index (RVI) to extract and visualize disturbance patches.

Benefits of technology

Enhances the accuracy and reliability of forest disturbance detection, providing high-quality data under various weather conditions, reducing false detection rates, and offering timely ecological protection and management support.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The present invention discloses a method for detecting forest disturbances based on a full-polarization SAR image, which includes obtaining a full-polarization SAR image within a target area, performing image classification for the reference time phase and the monitoring time phase, performing pre-processing including introduction of the SAR image, polarization matrix transformation of the SAR image, Refined Lee filtering, and false-color synthesis on the classified full-polarization SAR image to obtain a false-color synthesized SAR image, inputting the false-color synthesized SAR image into an optimized surface change detection model to extract surface change patches, combining with a radar vegetation index RVI image to obtain initial forest disturbance patches, performing an overlay check on the initial forest disturbance patches to obtain forest disturbance patches within the target area, and generating a visualization result. It has efficient, accurate, and reliable detection capabilities, can observe the ground all day long, all-weather, and penetrate clouds and fog, can be widely applied in fields such as forest resource monitoring and environmental protection, and can better serve ecological protection restoration supervision and management.
Need to check novelty before this filing date? Find Prior Art