Damage Proxy Mapping with SAR interferometric coherence change
收藏DataCite Commons2023-11-16 更新2025-04-16 收录
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http://dataverse.jpl.nasa.gov/citation?persistentId=doi:10.48577/jpl.A00XXE
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Synthetic aperture radar (SAR) can be combined interferometrically to estimate the coherence of the SAR phase. The coherence of the phase over time depends on the stability of the major objects and surface that are reflecting the SAR signal, at spatial scales near the radar wavelength and larger. When there are major changes in the radar reflection, it causes a loss of interferometric coherence, so we use methods of detecting coherence change as a proxy for damage or other sudden change to buildings, other structures, or the land surface, which we call a damage proxy map (DPM). The most common method for estimating the interferometric coherence is with spatial phase correlation measures over small areas. The simplest damage proxy map method is to calculate the coherence of an interferometric SAR (InSAR) pair before the event and another pair that spans the event and take the difference of the coherence to measure the change likely due to the event. This method can be effective for areas where the InSAR coherence is normally very high at the radar wavelength used. SAR at L-band (24 cm) wavelength has high coherence in a wider variety of environments than the shorter wavelengths. A more advanced, but requiring more computational resources, damage proxy map method involves calculating the coherence of all possible InSAR pairs for an interval of some months or years before the event to develop statistics about the coherence of each ground location as a function of InSAR pair interval and other parameters such as interferometric spatial baseline. Then InSAR pairs that span the event are compared to the pre-event statistics to estimate the likelihood that the co-event coherence has been reduced by damage or other surface changes. We have found that damage proxy maps are useful for detecting likely damage from many different types of events, including earthquakes, hurricanes, tornados, tsunami inundation, large landslides, or other causes.
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Root
创建时间:
2023-11-12



