USING COVARIANCE MATRIX FOR CHANGE DETECTION OF POLARIMETRIC SAR DATA

被引：2

作者：

Esmaeilzade, M. ^{[1
]}

Jahani, F. ^{[1
]}

Amini, J. ^{[1
]}

机构：

[1] Univ Tehran, Coll Engn, Fac Surveying & Geo Spatial Engn, Remote Sensing Dept, Tehran, Iran

来源：

ISPRS INTERNATIONAL JOINT CONFERENCES OF THE 2ND GEOSPATIAL INFORMATION RESEARCH (GI RESEARCH 2017); THE 4TH SENSORS AND MODELS IN PHOTOGRAMMETRY AND REMOTE SENSING (SMPR 2017); THE 6TH EARTH OBSERVATION OF ENVIRONMENTAL CHANGES (EOEC 2017) | 2017年 / 42-4卷 / W4期

关键词：

Change detection; UAVSAR; Wishart distribution; Statistical Model; Dual polarization; Full polarization;

D O I：

10.5194/isprs-archives-XLII-4-W4-69-2017

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Nowadays change detection is an important role in civil and military fields. The Synthetic Aperture Radar (SAR) images due to its independent of atmospheric conditions and cloud cover, have attracted much attention in the change detection applications. When the SAR data are used, one of the appropriate ways to display the backscattered signal is using covariance matrix that follows the Wishart distribution. Based on this distribution a statistical test for equality of two complex variance-covariance matrices can be used. In this study, two full polarization data in band L from UAVSAR are used for change detection in agricultural fields and urban areas in the region of United States which the first image belong to 2014 and the second one is from 2017. To investigate the effect of polarization on the rate of change, full polarization data and dual polarization data were used and the results were compared. According to the results, full polarization shows more changes than dual polarization.

引用

页码：69 / 76

页数：8

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