Engineering Papers⌕ Search
Home/Archive/NASA NTRS

NASA NTRS · 20130003282

Rapid and Reliable Damage Proxy Map from InSAR Coherence

Yun, Sang-Ho·Fielding, Eric·Simons, Mark·Agram, Piyush·Rosen, Paul·Owen, Susan·Webb, Frank
View original source ↗Export metadata ↓

Abstract

Future radar satellites will visit SoCal within a day after a disaster event. Data acquisition latency in 2015-2020 is 8 to approx. 15 hours. Data transfer latency that often involves human/agency intervention far exceeds the data acquisition latency. Need interagency cooperation to establish automatic pipeline for data transfer. The algorithm is tested with ALOS PALSAR data of Pasadena, California. Quantitative quality assessment is being pursued: Meeting with Pasadena City Hall computer engineers for a complete list of demolition/construction project 1. Estimate the probability of detection and probability of false alarm 2. Estimate the optimal threshold value.

Explore related subjects

InSARcoherencedamage

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Yun, Sang-Ho, Fielding, Eric, Simons, Mark, Agram, Piyush, Rosen, Paul, Owen, Susan, Webb, Frank. 2012-06-22. Rapid and Reliable Damage Proxy Map from InSAR Coherence. https://ntrs.nasa.gov/citations/20130003282

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

NASA NTRS2016

First Image Products from EcoSAR - Osa Peninsula, Costa Rica

Designed especially for forest ecosystem studies, EcoSAR employs state-of-the-art digital beamforming technology to generate wide-swath, high-resolution imagery. EcoSARs dual antenna single-pass imaging capability eliminates temporal decorrelation from polarimetric and interferometric analysis, increasing the signal strength and simplifying models used to invert forest structure parameters. Antennae are physically separated by 25 meters providing single pass interferometry. In this mode the radar is most sensitive to topography. With 32 active transmit and receive channels, EcoSARs digital beamforming is an order of magnitude more versatile than the digital beamforming employed on the upcoming NISAR mission. EcoSARs long wavelength (P-band, 435 MHz, 69 cm) measurements can be used to simulate data products for ESAs future BIOMASS mission, allowing scientists to develop algorithms before the launch of the satellite. EcoSAR can also be deployed to collect much needed data where BIOMASS satellite wont be allowed to collect data (North America, Europe and Arctic), filling in the gaps to keep a watchful eye on the global carbon cycle. EcoSAR can play a vital role in monitoring, reporting and verification schemes of internationals programs such as UN-REDD (United Nations Reducing Emissions from Deforestation and Degradation) benefiting global society. EcoSAR was developed and flown with support from NASA Earth Sciences Technology Offices Instrument Incubator Program.

InSAR↗
NASA NTRS2015

Time Series Analysis of Insar Data: Methods and Trends

Time series analysis of InSAR data has emerged as an important tool for monitoring and measuring the displacement of the Earth's surface. Changes in the Earth's surface can result from a wide range of phenomena such as earthquakes, volcanoes, landslides, variations in ground water levels, and changes in wetland water levels. Time series analysis is applied to interferometric phase measurements, which wrap around when the observed motion is larger than one-half of the radar wavelength. Thus, the spatio-temporal ''unwrapping" of phase observations is necessary to obtain physically meaningful results. Several different algorithms have been developed for time series analysis of InSAR data to solve for this ambiguity. These algorithms may employ different models for time series analysis, but they all generate a first-order deformation rate, which can be compared to each other. However, there is no single algorithm that can provide optimal results in all cases. Since time series analyses of InSAR data are used in a variety of applications with different characteristics, each algorithm possesses inherently unique strengths and weaknesses. In this review article, following a brief overview of InSAR technology, we discuss several algorithms developed for time series analysis of InSAR data using an example set of results for measuring subsidence rates in Mexico City.

InSAR↗
NASA NTRS2008

Observations and Mitigation of RFI in ALOS PALSAR SAR Data; Implications for the Desdyni Mission

Initial examination of ALOS PALSAR synthetic aperture radar (SAR) data has indicated significant radio frequency interference (RFI) in several geographic locations around the world. RFI causes significant reduction in image contrast, introduces periodic and quasi-periodic image artifacts, and introduces significant phase noise in repeat pass interferometric data reduction. The US National Research Council Decadal Survey of Earth Science has recommended DESDynI, a Deformation, Ecosystems, and Dynamics of Ice satellite mission comprising an L-band polarimetric radar configured for repeat pass interferometry. There is considerable interest internationally in other future L-band and lower frequency systems as well. Therefore the issues of prevalence and possibilities of mitigation of RFI in these crowded frequency bands is of considerable interest. RFI is observed in ALOS PALSAR in California, USA, and in southern Egypt in data examined to date. Application of several techniques for removing it from the data prior to SAR image formation, ranging from straightforward spectral normalization to time-domain, multi-phase filtering techniques are considered. Considerable experience has been gained from the removal of RFI from P-band acquired by the GeoSAR system. These techniques applied to the PALSAR data are most successful when the bandwidth of any particular spectral component of the RFI is narrow. Performance impacts for SAR imagery and interferograms are considered in the context of DESDynI measurement requirements.

InSAR↗