Successes and Challenges of MT-InSAR Methods in Coastal Regions: A Case Study on the Island of Tutuila, American Samoa
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Stacey A Huang↗
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Results for “InSAR”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Creating a Deformation Time Series Utilizing InSAR to Assess Hazards and Detect Volcanic Unrest in Clear Lake Volcanic Field, California
According to the U.S Geological Survey, the Clear Lake Volcanic Field (CLVF) in northern California is at a high threat potential for volcanic hazards. Eruptions leading to increased seismic activity could result in silicic domes, cinder cones, and flows that would be dangerous to the residential areas near the volcanic field. Remotely sensed Earth observations can reveal volcanic processes in the subsurface, which are essential to the timely monitoring of potential volcanic activity. In particular, Sentinel-1 C-band Synthetic Aperture Radar (C-SAR) and Digital Elevation Model (DEM) data capture relative surface deformation at unprecedented high spatial and temporal resolutions. Leveraging C-SAR and DEMs, we conducted interferometric analysis from January 2016 to December 2023. Our results demonstrate 1) the mean surface displacement velocity of the Clear Lake Volcanic field is measured to undergo 5 to 10-centimeter scale deformation and shows a strong correlation with the surrounding faults, 2) apparent seasonal differences in rates of surface change, and 3) seismic activity associated with the geyser geothermal field has a strong correlation with cumulative surface displacement, with active fault zones having 2 to 5 cm of additional displacement. Results indicate that deformation is linked to deep pressure sources causing stresses on the surficial environment that should be considered in hazard mitigation. This study provides a baseline of historic deformation, aiding hazard analysts in communication efforts and streamlining decision-making for potential risks to region residents.
Ivan Tochimani-Hernandez↗
Transfer Learning of InSAR Atmospheric Effects for Earthquake Characterization
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Cody Rude↗
Time-Varying Elevation Change at the Centralia Coal Mine in Centralia, Washington (USA), Constrained with InSAR, ASTER, and Optical Imagery
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Veronica B. Prush↗
Multichannel singular spectrum analysis (M-SSA) of InSAR data sets: data-adaptive interpolation and decomposition of Sentinel-1 time-series at Pacaya Volcano, Guatemala
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D Walwer↗
Evaluation of Vegetation Bias in InSAR Time Series for Agricultural Areas Within the San Joaquin Valley, CA
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Kelly R. Devlin↗
The Information Content of Interferometric Synthetic Aperture Radar: Vegetation and Underlying Surface Topography
Drawing from recently submitted work, this paper first gives a heuristic description of the sensitivity of interferometric synthetic aperture radar (INSAR) to vertical vegetation distribution and under laying surface topography. A parameter estimation scenario is then described in which the INSAR cross correlation amplitude and phase are the observations from which vegetation and surface topographic parameters are estimated. It is shown that, even in the homogeneous layer model of the vegetation, the number of parameters needed to describe the vegetation and underlying topography exceeds the number of INSAR observations for single baseline, single frequency, single incidence-angle, single polarization INSAR. Using ancillary ground truth data to compensate for the under determination of the parameters, forest depths are estimated from the INSAR data. A recently analyzed multi-baseline data set is also discussed and the potential for stand alone INSAR parameter estimation is assessed. The potential of combining the information content of INSAR with that of infrared/optical remote sensing data is briefly discussed.
Treuhaft, Robert N.↗
Forest Attributes from Radar Interferometric Structure and its Fusion with Optical Remote Sensing
The possibility of global, three-dimensional remote sensing of forest structure with interferometric synthetic aperture radar (InSAR) bears on important forest ecological processes, particularly the carbon cycle. InSAR supplements two-dimensional remote sensing with information in the vertical dimension. Its strengths in potential for global coverage complement those of lidar (light detecting and ranging), which has the potential for high-accuracy vertical profiles over small areas. InSAR derives its sensitivity to forest vertical structure from the differences in signals received by two, spatially separate radar receivers. Estimation of parameters describing vertical structure requires multiple-polarization, multiple-frequency, or multiple-baseline InSAR. Combining InSAR with complementary remote sensing techniques, such as hyperspectral optical imaging and lidar, can enhance vertical-structure estimates and consequent biophysical quantities of importance to ecologists, such as biomass. Future InSAR experiments will supplement recent airborne and spaceborne demonstrations, and together with inputs from ecologists regarding structure, they will suggest designs for future spaceborne strategies for measuring global vegetation structure.
InSAR↗
Radar Interferometer for Topographic Mapping of Glaciers and Ice Sheets
A report discusses Ka-band (35-GHz) radar for mapping the surface topography of glaciers and ice sheets at high spatial resolution and high vertical accuracy, independent of cloud cover, with a swath-width of 70 km. The system is a single- pass, single-platform interferometric synthetic aperture radar (InSAR) with an 8-mm wavelength, which minimizes snow penetration while remaining relatively impervious to atmospheric attenuation. As exhibited by the lower frequency SRTM (Shuttle Radar Topography Mission) AirSAR and GeoSAR systems, an InSAR measures topography using two antennas separated by a baseline in the cross-track direction, to view the same region on the ground. The interferometric combination of data received allows the system to resolve the pathlength difference from the illuminated area to the antennas to a fraction of a wavelength. From the interferometric phase, the height of the target area can be estimated. This means an InSAR system is capable of providing not only the position of each image point in along-track and slant range as with a traditional SAR but also the height of that point through interferometry. Although the evolution of InSAR to a millimeter-wave center frequency maximizes the interferometric accuracy from a given baseline length, the high frequency also creates a fundamental problem of swath coverage versus signal-to-noise ratio. While the length of SAR antennas is typically fixed by mass and stowage or deployment constraints, the width is constrained by the desired illuminated swath width. As the across-track beam width which sets the swath size is proportional to the wavelength, a fixed swath size equates to a smaller antenna as the frequency is increased. This loss of antenna size reduces the two-way antenna gain to the second power, drastically reducing the signal-to-noise ratio of the SAR system. This fundamental constraint of high-frequency SAR systems is addressed by applying digital beam-forming (DBF) techniques to synthesize multiple simultaneous receive beams in elevation while maintaining a broad transmit illumination. Through this technique, a high antenna gain on receive is preserved, thereby reducing the required transmit power and thus enabling high-frequency SARs and high-precision InSAR from a single spacecraft.
Moller, Delwyn K.↗
Polarimetric SAR Interferometry Evaluation in Mangroves
TanDEM-X (TDX) enables to generate an interferometric coherence without temporal decorrelation effect that is the most critical factor for a successful Pol-InSAR inversion, as have recently been used for forest parameter retrieval. This paper presents mangrove forest height estimation only using single-pass/single-baseline/dual-polarization TDX data by means of new dual-Pol-InSAR inversion technique. To overcome a lack of one polarization in a conventional Pol- InSAR inversion (i.e. an underdetermined problem), the ground phase in the Pol-InSAR model is directly estimated from TDX interferograms assuming flat underlying topography in mangrove forest. The inversion result is validated against lidar measurement data (NASA's G-LiHT data).
Mangrove↗
Simulation Studies of Forest Structure using 3D Lidar and Radar Models
The use of lidars and radars to measure forest structure attributes such as height and biomass are being considered for future Earth Observation missions. Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield information about the vertical profile of the canopy. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and is useful for estimating biomass. Interferometric SAR (InSAR) has been shown to yield forest canopy height information. For example, the height of scattering phase retrieved from InSAR data is considered to be correlated with the three height and the spatial structure of the forest stand. There is much interest in exploiting these technologies separately and together to get important information for carbon cycle and ecosystem science. More detailed information of the electromagnetic radiation interactions within forest canopies is needed. And backscattering models can be of much utility here. As part of a NASA funded project to explore data fusion, a three-dimensional (3D) coherent radar backscattering model and a 3D lidar backscatter models were used to investigate the use of large footprint lidar, SAR and InSAR for characterizing realistic forest scenes. For this paper, we use stem maps and other forest measurements to develop a realistic spatial structure of a spruce-hemlock forest canopy found in Maine, USA. The radar and lidar models used measurements of the 3D forest scene as input and simulated the coherent radar backscattering signature and 1064nm energy backscatter, respectively. The relationships of backscatter derived forest structure were compared with field measurements. In addition, we also had detailed airborne lidar (Laser Imaging Vegetation Sensor, LVIS) data available over the stem map sites that was used to study the accuracies of tree height derived from modeled SAR backscatter and the scattering phase center retrieved from the simulated InSAR data will be compared with the height indices, or other structure parameters derived from the lidar data. These results will address the possible synergies between lidar and radar in data in terms of forest structural information.
Sun, Guoqing↗
GPS Position Time Series @ JPL
Different flavors of GPS time series analysis at JPL - Use same GPS Precise Point Positioning Analysis raw time series - Variations in time series analysis/post-processing driven by different users. center dot JPL Global Time Series/Velocities - researchers studying reference frame, combining with VLBI/SLR/DORIS center dot JPL/SOPAC Combined Time Series/Velocities - crustal deformation for tectonic, volcanic, ground water studies center dot ARIA Time Series/Coseismic Data Products - Hazard monitoring and response focused center dot ARIA data system designed to integrate GPS and InSAR - GPS tropospheric delay used for correcting InSAR - Caltech's GIANT time series analysis uses GPS to correct orbital errors in InSAR - Zhen Liu's talking tomorrow on InSAR Time Series analysis
Precise Point Positioning (PPP)↗
Multibaseline TanDEM-X Mangrove Height Estimation: The Selection of the Vertical Wavenumber
We generated a large-scale mangrove forest height map using multiple TanDEM-X (TDX) interferometric synthetic aperture radar (InSAR) acquisitions with various spatial baselines in order to improve the height estimation accuracy across a wide range of forest heights. The forest height inversion using InSAR data is strongly dependent upon the vertical wavenumber (i.e., perpendicular baseline). First, we investigated the role of the vertical wavenumber in forest height inversion from InSAR data using the sensitivity of the interferometric (volume) coherence to forest height. We used corrected but lower resolution and accuracy Shuttle Radar Topography Mission (SRTM) mangrove height maps as a priori information over Akanda and Pongara National Parks in Gabon to estimate lower and upper boundaries of the vertical wavenumber over test sites from the measured coherence-to-height sensitivity. Only TDX acquisitions within the boundaries of the vertical wavenumber were selected and combined for multibaseline mangrove height inversion. Mangrove forest height was obtained with multibaseline TDX acquisitions and was validated against the reference height derived from field measurement data providing improvements in multibaseline inversion over existing height estimates (i.e., SRTM height) and single-baseline inversions (multibaseline inversion: r(exp 2) = 0.98, root mean square error (RMSE) of 2.73 m; SRTM height: r(exp 2) = 0.86, RMSE = 7.21 m; single-baseline inversions: r(exp 2) = 0.08-0.97, RMSE = 3.86-11.10 m). As a result, to accurately estimate forest heights over a wide range (3-60 m), multibaseline InSAR acquisitions (at least three different baselines) are needed to exclude biases associated with the vertical wavenumber in forest height inversion.
vertical wavenumber.↗
Large-scale product of forest height using a new approach from spaceborne repeat-pass SAR interferometry and LIDAR
Spaceborne SAR interferometry (InSAR) has the potential of mapping the forest height on a global scale and a monthly/weekly basis under all weather conditions, which can improve our understanding of the global carbon dynamics. In previous work, repeatpass SAR interferometry from spaceborne sensors is utilized to create large-scale forest height maps (that are particularly interested for large-scale ecological research) based on a newly developed approach. This paper thus serves as a summary paper and also sheds light on the future directions with improved results. In particular, it will be shown that repeat-pass SAR interferometry is able to create a large-scale forest height mosaic product with RMSE 4 m for forest stands on the order of 20 hectares through using the past spaceborne repeat-pass InSAR observations (i.e. JAXA’s ALOS-1 and ALOS-2) combined with sparse airborne lidar training samples over the forested areas in New England, US. Moreover, the results and performance of this approach can be remarkably improved with several enhancement techniques that can be easily satisfied with use of future spaceborne repeat-pass InSAR and lidar missions (e.g. NASA-ISRO’s NISAR and NASA’s GEDI). The methodology described in this paper can be considered as a complimentary tool to the existing PolInSAR technique and also serves as an observing prototype for the future spaceborne missions of repeatpass InSAR in fusion with lidar (e.g. NISAR and GEDI).
Treuhaft, Robert↗
Remote sensing of ocean wave spectra by interferometric synthetic aperture radar
Ocean surface waves can be clearly observed by SAR in the interferometric configuration (INSAR) due to the ability of INSAR to provide images of the local surface velocity field. It is shown here that INSAR can be used to obtain wavenumber spectra that are in agreement with power spectra measured in situ. This new method has considerable potential to provide instantaneous spatial information about the structure of ocean wave fields.
Marom, M.↗
Relating Vegetation Aerodynamic Roughness Length to Interferometric SAR Measurements
In this paper, we investigate the feasibility of estimating aerodynamic roughness parameter from interferometric SAR (INSAR) measurements. The relation between the interferometric correlation and the rms height of the surface is presented analytically. Model simulations performed over realistic canopy parameters obtained from field measurements in boreal forest environment demonstrate the capability of the INSAR measurements for estimating and mapping surface roughness lengths over forests and/or other vegetation types. The procedure for estimating this parameter over boreal forests using the INSAR data is discussed and the possibility of extending the methodology over tropical forests is examined.
Saatchi, Sassan↗
Estimating Forest Vertical Structure from Multialtitude, Fixed-Baseline Radar Interferometric and Polarimetric Data
Parameters describing the vertical structure of forests, for example tree height, height-to-base-of-live-crown, underlying topography, and leaf area density, bear on land-surface, biogeochemical, and climate modeling efforts. Single, fixed-baseline interferometric synthetic aperture radar (INSAR) normalized cross-correlations constitute two observations from which to estimate forest vertical structure parameters: Cross-correlation amplitude and phase. Multialtitude INSAR observations increase the effective number of baselines potentially enabling the estimation of a larger set of vertical-structure parameters. Polarimetry and polarimetric interferometry can further extend the observation set. This paper describes the first acquisition of multialtitude INSAR for the purpose of estimating the parameters describing a vegetated land surface. These data were collected over ponderosa pine in central Oregon near longitude and latitude -121 37 25 and 44 29 56. The JPL interferometric TOPSAR system was flown at the standard 8-km altitude, and also at 4-km and 2-km altitudes, in a race track. A reference line including the above coordinates was maintained at 35 deg for both the north-east heading and the return southwest heading, at all altitudes. In addition to the three altitudes for interferometry, one line was flown with full zero-baseline polarimetry at the 8-km altitude. A preliminary analysis of part of the data collected suggests that they are consistent with one of two physical models describing the vegetation: 1) a single-layer, randomly oriented forest volume with a very strong ground return or 2) a multilayered randomly oriented volume; a homogeneous, single-layer model with no ground return cannot account for the multialtitude correlation amplitudes. Below the inconsistency of the data with a single-layer model is followed by analysis scenarios which include either the ground or a layered structure. The ground returns suggested by this preliminary analysis seem too strong to be plausible, but parameters describing a two-layer compare reasonably well to a field-measured probability distribution of tree heights in the area.
Treuhaft, Robert N.↗
Integrated Analysis of Interferometric SAR, Satellite Altimetry and Hydraulic Modeling to Quantify Louisiana Wetland Dynamics
Wetland loss in Louisiana has been accelerating due primarily to anthropogenic and nature processes, and is being advocated as a problem with national importance. Accurate measurement or modeling of wetland-wide water level changes, its varying extent, its storage and discharge changes resulting in part from sediment loads, erosion and subsidence are fundamental to assessment of hurricane-induced flood hazards and wetland ecology. Here, we use innovative method to integrate interferometric SAR (InSAR) and satellite radar altimetry for measuring absolute or geocentric water level changes and applied the methodology to remote areas of swamp forest in coastal Louisiana. Coherence analysis of InSAR pairs suggested that the HH polarization is preferred for this type of observation, and polarimetric analysis can help to identi:fy double-bonnce backscattering areas in the wetland. Envisat radar altimeter-measured 18- Hz (along-track sampling of 417 m) water level data processed with regional stackfile method have been used to provide vertical references for water bodies separated by levees. The high-resolution (approx.40 m) relative water changes measured from ALOS PALSAR L-band and Radarsat-l C-band InSAR are then integrated with Envisat radar altimetry to obtain absolute water level. The resulting water level time series were validated with in situ gauge observations within the swamp forest. Furthermore, we compare our water elevation changes with 2D flood modeling from LISFLOOD hydrodynamic model. Our study demonstrates that this new technique allows retrospective reconstruction and concurrent monitoring of water conditions and flow dynamics in wetlands, especially those lacking gauge networks.
Lee, Hyongki↗