DS self-adaptive selection method in InSAR time sequence analysis based on land type

Abstract

The invention discloses a DS self-adaptive selection method in an InSAR time sequence analysis based on a land type. The DS self-adaptive selection method comprises the steps that in the process of the DS self-adaptive selection method in the InSAR time sequence analysis, the recognition of homogeneous pixels on a time sequence SAR image is carried out based on the land type, and then DS candidatepoints are selected; the land type is a land coverage type or a land utilization type; aiming at different land types, DS selection thresholds under different land types are self-adaptively calculated; and DS self-adaptive selection based on the land type is carried out. By adopting the self-adaptive selection technical scheme for performing the InSAR time sequence analysis on a DS target based on the land type provided by the invention, DS quality of self-adaptive selection can be improved; and an inspection search range is reduced, identification efficiency of homogeneous pixels is improved, and DS selection efficiency is further improved.

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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