Unsupervised segmentation of multitemporal interferometric SAR images

1999 ◽  
Vol 37 (5) ◽  
pp. 2259-2271 ◽  
Author(s):  
P.B.G. Dammert ◽  
J.I.H. Askne ◽  
S. Kuhlmann
Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2336 ◽  
Author(s):  
Takashi Nonaka ◽  
Tomohito Asaka ◽  
Keishi Iwashita

High-resolution synthetic aperture radar (SAR) data are widely used for disaster monitoring. To extract damaged areas automatically, it is essential to understand the relationships among the sensor specifications, acquisition conditions, and land cover. Our previous studies developed a method for estimating the phase noise of interferograms using several pairs of TerraSAR-X series (TerraSAR-X and TanDEM-X) datasets. Atmospheric disturbance data are also necessary to interpret the interferograms; therefore, the purpose of this study is to estimate the atmospheric effects by focusing on the difference in digital elevation model (DEM) errors between repeat-pass (two interferometric SAR images acquired at different times) and single-pass (two interferometric SAR images acquired simultaneously) interferometry. Single-pass DEM errors are reduced due to the lack of temporal decorrelation and atmospheric disturbances. At a study site in the city of Tsukuba, a quantitative analysis of DEM errors at fixed ground objects shows that the atmospheric effects are estimated to contribute 75% to 80% of the total phase noise in interferograms.


Author(s):  
D. Oxoli ◽  
P. Boccardo ◽  
M. A. Brovelli ◽  
M. E. Molinari ◽  
A. Monti Guarnieri

<p><strong>Abstract.</strong> During disaster response, the availability of relevant information, delivered in a proper format enabling its use among the different actors involved in response efforts, is key to lessen the impact of the disaster itself. Focusing on the contribution of geospatial information, meaningful advances have been achieved through the adoption of satellite earth observations within emergency management practices. Among these technologies, the Synthetic Aperture Radar (SAR) imaging has been extensively employed for large-scale applications such as flood areas delineation and terrain deformation analysis after earthquakes. However, the emerging availability of higher spatial and temporal resolution data has uncovered the potential contribution of SAR to applications at a finer scale. This paper proposes an approach to enable pixel-wise earthquake damage assessments based on Coherent Change Detection methods applied to a stack of repeated-pass interferometric SAR images. A preliminary performance assessment of the procedure is provided by processing Sentinel-1 data stack related to the 2016 central Italy earthquake for the towns of Ametrine and Accumoli. Damage assessment maps from photo-interpretation of high-resolution airborne imagery, produced in the framework of Copernicus EMS (Emergency Management Service &amp;ndash; European Commission) and cross-checked with field survey, is used as ground truth for the performance assessment. Results show the ability of the proposed approach to automatically identify changes at an almost individual building level, thus enabling the possibility to empower traditional damage assessment procedures from optical imagery with the centimetric change detection sensitivity characterizing SAR. The possibility of disseminating outputs in a GIS-like format represents an asset for an effective and cross-cutting information sharing among decision makers and analysts.</p>


2008 ◽  
Vol 46 (8) ◽  
pp. 2185-2196 ◽  
Author(s):  
J. Morio ◽  
P. Refregier ◽  
F. Goudail ◽  
P.C. Dubois-Fernandez ◽  
X. Dupuis

1994 ◽  
Author(s):  
Jong-Sen Lee ◽  
Thomas L. Ainsworth ◽  
Mitchell R. Grunes ◽  
Raymond M. Goldstein

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