A grassland wind erosion pit identification method based on multi-source remote sensing data

By combining multi-source remote sensing data with SBAS-InSAR and KNDVI methods and employing local adaptive threshold segmentation technology, the problems of single data sources being susceptible to cloud and fog influences and insufficient handling of spatial heterogeneity in grassland wind erosion pit identification were solved, achieving high-precision wind erosion pit identification and early warning.

CN121121474BActive Publication Date: 2026-06-09INNER MONGOLIA UNIV OF TECH
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Patent Information

Application Number
CN202511237992.4
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-09-01
Publication Date
2026-06-09
Estimated Expiration
2045-09-01

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Abstract

The present application relates to a kind of grassland wind erosion pit identification method based on multi-source remote sensing data, belong to remote sensing and geological geography technical field.It includes the following steps: obtaining the SAR image and multispectral image of target area and pre-processing;SBAS-InSAR time series deformation monitoring technology is used to the SAR image data after pre-processing is handled, and vertical direction cumulative deformation variable data is obtained;KNDVI method is used to the multispectral image data after pre-processing is carried out kernel normalization vegetation index calculation, then vegetation change trend analysis is carried out, and significant vegetation change trend data is obtained;Vertical direction cumulative deformation variable data and significant vegetation change trend data are geographically registered and resampled;Based on vertical direction cumulative deformation variable data and significant vegetation change trend data after geographical registration and resampling, grassland wind erosion pit identification is realized by local adaptive threshold value.The present application can improve the accuracy of grassland wind erosion pit identification.
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Citation Information

Patent Citations

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