DS Adaptive Selection Method in Insar Time Series Analysis Based on Land Type

Abstract

The invention discloses a DS adaptive selection method in InSAR time series analysis based on land type. In the process of DS adaptive selection in InSAR time series analysis, homogeneous pixels on time series SAR images are identified based on land type, and then selected DS candidate points; the land type is land cover type or land use type; then, according to different land types, adaptively calculate the DS selection threshold under different land types; and then perform adaptive selection of DS based on land type. Adopting the technical solution for adaptive selection of DS targets for InSAR time-series analysis based on land types provided by the present invention can improve the quality of adaptively selected DSs; narrow the inspection search range, improve the recognition efficiency of homogeneous pixels, and further improve the efficiency of DS selection .

Description

technical field [0001] The present invention relates to a method for selecting distributed scatterers in the time series analysis of Interferometric Synthetic Aperture Radar (InSAR), in particular to a distributed scatterer (DS) based on land cover / land use type (land type). ) adaptive selection method. Background technique [0002] InSAR time-series analysis technology is an important means to monitor the slow deformation of the earth's surface. It analyzes the point-like permanent scatterer (Persistent Scatterer, PS) or surface distributed scatterer (Distributed Scatterer, DS) on the time-series SAR image, and obtains the surface deformation information of the monitoring area on the time-series. PS and DS are collectively referred to as deformation measurement points, and the quantity and quality of deformation measurement points directly affect the accuracy and reliability of InSAR timing analysis results. [0003] The initial research object of InSAR time-series analys...

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Problems solved by technology

The above method can increase the spatial distribution density of DS in the deformation monitoring area. However, it adopts a mechanically regular geometric partition method without considering the natural attributes of DS or the factors of utilization status, which reduces the correct rate of DS selection, thus affecting InSAR. The accuracy and reliability of the time series solution results, moreover, this method requires multiple repeated experiments in the process of determining the N value, which increases the time cost and calculation burden of the solution

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