The GeoSAR topographic mapping instrument: The design, development and implementation of a precision EM interferometric SAR
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interferometric SAR radar remote sensing↗
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Repeat Pass Synthetic Aperture Radar Interferometry for Environmental Monitoring
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Radar↗
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.↗
Rapid subsidence over oil fields measured by SAR
The Lost Hills and Belridge oil felds are in the San Joaquin Valley, California. The major oil reservoir is high porosity and low permeability diatomite. Extraction of large volumes from shallow depths causes reduction in pore pressure and subsequent compaction, forming a surface subsidence bowl. We measure this subsidence from space using interferometric analysis of SAR (Synthetic Aperture Radar) data collected by the European Space Agency Remote Sensing Satellites (ERS-1 and ERS-2). Maximum subsidence rates are as high as 40 mm in 35 days or > 400 mm/yr, measured from interferograms with time separations ranging from one day to 26 months. The 8- and 26-month interferograms contain areas where the subsidence gradient exceeds the measurement possible with ERS SAR, but shows increased detail in areas of less rapid subsidence. Synoptic mapping of subsidence distribution from satellite data powerfully complements ground-based techniques, permits measurements where access is difficult, and aids identification of underlying causes.
synthetic aperture radar remote sensing oil fields↗
Utah FORGE: InSAR Data 2019
This dataset contains Interferometric Synthetic Aperture Radar (InSAR) data used for ground deformation monitoring during Phase 2C of the Utah FORGE project. The dataset includes measurements of the mean rate of range change and associated standard errors, provided in both CSV and NetCDF formats. Supporting materials include histograms, maps, and MATLAB scripts used for data processing, as well as unit vector information describing the satellite's sensor orientation. Compressed archives contain additional metadata and masked range change data for individual interferometric pairs. A README file is included to provide further details on the dataset's structure and contents.
15 GEOTHERMAL ENERGY↗
Porotomo: InSAR Data from San Emidio Geothermal Field, Nevada, 1992-2010
This submission contains tarred pair directories for interferometric synthetic aperture radar (InSAR) data covering San Emidio Geothermal Field in Nevada, USA as part of the porotomo project. Data included within this submission are the following: > ENVI_T120_GDR.tgz: Tarred directory containing 39 Envisat track 120 tarred, pair subdirectories spanning from 2003-Oct-29 to 2010-Jun-09. > ENVI_T27_GDR.tgz: Tarred directory containing 32 Envisat track 27 tarred, pair subdirectories spanning from 2004-Jun-23 to 2010-Apr-28. > ERS_T27_GDR.tgz: Tarred directory containing 35 ERS track 27 tarred, pair subdirectories spanning from 1992-Jun-07 to 2000-Sep-27. > ENVI_T27_SQR_drange_utm_cut.grd: SqueeSAR-derived data product for Enivsat track 27 from Eneva, et al. (2011) (provided by TRE Altamira) in terms of unwrapped range change rate. > MSTvsSQR_GDR.tgz: Tarred directory containing Easting gradient files for each satellite and track corresponding to the MST data products and the SqueeSAR data products. > sanem_dem_utm.grd: Digital elevation model (DEM) used in the creation of the interferograms. Explanation of pair subdirectories (contained within ENVI_T120_GDR, ENVI_T27_GDR, ERS_T27_GDR): Pairs are chosen based on a minimum spanning tree (MST) algorithm with image quality (as measured by the amount of phase noise within an interferometric pair) as the weighting criterion. Pairs are formed using the InSAR processing software GMT5SAR (Sandwell et al., 2011). Pair subdirectories are named by starting and ending epochs in YYYYMMDD_YYYYMMDD format. Each tarred pair directory contains GRD files for wrapped phase data (radians) and wrapped phase data after application of a modified Goldstein filter that depends on coherence (Goldstein & Werner, 1997; Baran et al., 2003; Sandwell et al., 2011). The data are given in both latitude/longitude and Universal Transverse Mercator (Zone 11N). Raw Synthetic Aperture Radar (SAR) data from the Envisat and ERS satellite missions operated by the European Space Agency (ESA) are copyrighted by ESA and were provided through the WInSAR consortium at the UNAVCO facility.
15 GEOTHERMAL ENERGY↗
Recent Advances in Radar Polarimetry and Polarimetric SAR Interferometry
The development of Radar Polarimetry and Radar Interferometry is advancing rapidly, and these novel radar technologies are revamping Synthetic Aperture Radar Imaging decisively. In this exposition the successive advancements are sketched; beginning with the fundamental formulations and high-lighting the salient points of these diverse remote sensing techniques. Whereas with radar polarimetry the textural fine-structure, target-orientation and shape, symmetries and material constituents can be recovered with considerable improvements above that of standard amplitude-only Polarization Radar ; with radar interferometry the spatial (in depth) structure can be explored. In Polarimetric-Interferometric Synthetic Aperture Radar (POL-IN-SAR) Imaging it is possible to recover such co-registered textural plus spatial properties simultaneously. This includes the extraction of Digital Elevation Maps (DEM) from either fully Polarimetric (scattering matrix) or Interferometric (dual antenna) SAR image data takes with the additional benefit of obtaining co-registered three-dimensional POL-IN-DEM information. Extra-Wide-Band POL-IN-SAR Imaging - when applied to Repeat-Pass Image Overlay Interferometry - provides differential background validation and measurement, stress assessment, and environmental stress-change monitoring capabilities with hitherto unattained accuracy, which are essential tools for improved global biomass estimation. More recently, by applying multiple parallel repeat-pass EWB-POL-D(RP)-IN-SAR imaging along stacked (altitudinal) or displaced (horizontal) flight-lines will result in Tomographic (Multi- Interferometric) Polarimetric SAR Stereo-Imaging , including foliage and ground penetrating capabilities. It is shown that the accelerated advancement of these modern EWB-POL-D(RP)-IN-SAR imaging techniques is of direct relevance and of paramount priority to wide-area dynamic homeland security surveillance and local-to-global environmental ground-truth measurement and validation, stress assessment, and stress-change monitoring of the terrestrial and planetary covers. In addition, various closely related topics of (i) acquiring additional and protecting existing spectral windows of the Natural Electromagnetic Spectrum (NES) pertinent to Remote Sensing; (ii) mitigating against common "Radio Frequency Interference (RFI)" and intentional Directive Jamming of Airborne & Space borne POL-IN-SAR Imaging Platforms are appraised.
Boerner, Wolfgang-Martin↗
Central Valley Water Resources II: Groundwater Sustainability Management Support in the California Central Valley using GRACE and InSAR Datasets
California’s Central Valley is one of the most productive agricultural regions in the United States, producing a fourth of the nation’s food supply. The water demand in this region is heavily dependent on groundwater resources, resulting in over pumping of aquifers at unsustainable rates during recent periods of severe drought. Over the past century, Central Valley aquifers have experienced a significant decline in groundwater levels, resulting in land subsidence and irreversible loss in groundwater storage. In 2014, the state enacted the Sustainable Groundwater Management Act, requiring high and medium priority subbasins to suspend overdraft and achieve sustainable levels of pumping and recharge by 2042.The California Department of Water Resources (DWR) oversees subbasin groundwater management; however, monitoring remains challenging due to sparse and inconsistent in situ data. To assist the DWR, this project developed a user-friendly executable application and an interactive visualization tool to quantify groundwater storage and land subsidence trends using remotely sensed and in situ data. The team utilized NASA’s Gravity Recovery and Climate Experiment (GRACE), GRACE Follow-On (GRACE-FO), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR) interferograms, and Advanced Land Observing Satellite 2 (ALOS-2) Phased Array L-band Synthetic Aperture Radar 2 (PALSAR-2) interferograms in conjunction with well and GPS measurements to analyze groundwater and subsidence trends. GRACE and well data returns produced a strong Pearson correlation of .84, while Sentinel-1 and GPS data returns produced a Pearson correlation of .41 over the entire Central Valley. These findings suggest remotely sensed GRACE and interferometric SAR data can be used in the absence of in situ data.
DEVELOP Project Summary↗
Clear Lake Volcanic Field Disasters: Creating a Deformation Record Using InSAR to Assess Hazards and Detect Volcanic Unrest in Clear Lake Volcanic Field
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 relationship 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 association 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.
remote sensing↗
Fusion of AIRSAR and TM Data for Parameter Classification and Estimation in Dense and Hilly Forests
The expanded remotely sensed data space consisting of coincident radar backscatter and optical reflectance data provides for a more complete description of the Earth surface. This is especially useful where many parameters are needed to describe a certain scene, such as in the presence of dense and complex-structured vegetation or where there is considerable underlying topography. The goal of this paper is to use a combination of radar and optical data to develop a methodology for parameter classification for dense and hilly forests, and further, class-specific parameter estimation. The area to be used in this study is the H. J. Andrews Forest in Oregon, one of the Long-Term Ecological Research (LTER) sites in the US. This area consists of various dense old-growth conifer stands, and contains significant topographic relief. The Andrews forest has been the subject of many ecological studies over several decades, resulting in an abundance of ground measurements. Recently, biomass and leaf-area index (LAI) values for approximately 30 reference stands have also become available which span a large range of those parameters. The remote sensing data types to be used are the C-, L-, and P-band polarimetric radar data from the JPL airborne SAR (AIRSAR), the C-band single-polarization data from the JPL topographic SAR (TOPSAR), and the Thematic Mapper (TM) data from Landsat, all acquired in late April 1998. The total number of useful independent data channels from the AIRSAR is 15 (three frequencies, each with three unique polarizations and amplitude and phase of the like-polarized correlation), from the TOPSAR is 2 (amplitude and phase of the interferometric correlation), and from the TM is 6 (the thermal band is not used). The range pixel spacing of the AIRSAR is 3.3m for C- and L-bands and 6.6m for P-band. The TOPSAR pixel spacing is 10m, and the TM pixel size is 30m. To achieve parameter classification, first a number of parameters are defined which are of interest to ecologists for forest process modeling. These parameters include total biomass, leaf biomass, LAI, and tree height. The remote sensing data from radar and TM are used to formulate a multivariate analysis problem given the ground measurements of the parameters. Each class of each parameter is defined by a probability density function (pdf), the spread of which defines the range of that class. High classification accuracy results from situations in which little overlap occurs between pdfs. Classification results provide the basis for the future work of class-specific parameter estimation using radar and optical data. This work was performed in part by the Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, and in part by the NASA Ames Research Center, Moffett Field, CA, both under contract from the National Aeronautics and Space Administration.
Moghaddam, Mahta↗
Source Physics Experiment: Rock Valley Interferometric Synthetic Aperture RADAR Earthquake Detection Study
Seismic signals from 1993 show a series of magnitude (Mw) 3.7 or less seismic events in Rock Valley on the Nevada National Security Site (NNSS). Historic synthetic aperture radar images of that location were found that could provide interferometric synthetic aperture radar (InSAR) measures of the ground height during 1993. Given this historic SAR imagery, we explore answering the question if ground movement from the 1993 Rock Valley earthquake activity could be sensed by remote sensing means. Finding earthquake surface movement would assist in locating the Rock Valley fault and the 1993 earthquake hypocenter where the Source Physics Experiment Phase III series of experiments will be conducted. In this report, we show that InSAR can sense very small height differences, and for the European Radar Satellite-1 InSAR collections during 1992 and 1993 over Rock Valley earth surface movements were measured with 8 mm uplift and 12.5 mm subsidence over isolated areas. One of these earth movement areas coincides with an InSAR image pair coherence drop between March 5, 1993 and June 18, 1993. The coherence drop is over an approximately 13 square km area south southeast of Skull Mountain centered at 36° 43' 30" N latitude and 116° 05' 00" W longitude. Measured small surface movement and a loss of InSAR coherence may be caused by the series of earthquakes. The location of these InSAR detections may also coincide with water drainage or erosion displacement. There are no records to disambiguate the earthquake and erosion earth surface motion possibilities. Therefore, the InSAR findings of earth surface movement by InSAR are inconclusive.
58 GEOSCIENCES↗
Application of Radar Data to Remote Sensing and Geographical Information Systems
The field of synthetic aperture radar changed dramatically over the past decade with the operational introduction of advance radar techniques such as polarimetry and interferometry. Radar polarimetry became an operational research tool with the introduction of the NASA/JPL AIRSAR system in the early 1980's, and reached a climax with the two SIR-C/X-SAR flights on board the space shuttle Endeavour in April and October 1994. Radar interferometry received a tremendous boost when the airborne TOPSAR system was introduced in 1991 by NASA/JPL, and further when data from the European Space Agency ERS-1 radar satellite became routinely available in 1991. Several airborne interferometric SAR systems are either currently operational, or are about to be introduced. Radar interferometry is a technique that allows one to map the topography of an area automatically under all weather conditions, day or night. The real power of radar interferometry is that the images and digital elevation models are automatically geometrically resampled, and could be imported into GIS systems directly after suitable reformatting. When combined with polarimetry, a technique that uses polarization diversity to gather more information about the geophysical properties of the terrain, a very rich multi-layer data set is available to the remote sensing scientist. This talk will discuss the principles of radar interferometry and polarimetry with specific application to the automatic categorization of land cover. Examples will include images acquired with the NASA/JPL AIRSAR/TOPSAR system in Australia and elsewhere.
vanZyl, Jakob J.↗
Forest Structure Retrieval From EcoSAR P-Band Single-Pass Interferometry
EcoSAR is a single-pass (dual antenna) digital beamforming, P-band radar system that is designed for remote sensing of dense forest structure. Forest structure retrievals require the measurement related to the vertical dimension, for which several techniques have been developed over the years. These techniques use polarimetric and interferometric aspects of the SAR data, which can be collected using EcoSAR. In this paper we describe EcoSAR system in light of its interferometric capabilities and investigate forest structure retrieval techniques.
SAR↗
Forest Structure Retrieval from Ecosar P-Band Single-Pass Interferometry
EcoSAR is a single-pass (dual antenna) digital beamforming, P-band radar system that is designed for remote sensing of dense forest structure. Forest structure retrievals require the measurement related to the vertical dimension, for which several techniques have been developed over the years. These techniques use polarimetric and interferometric aspects of the SAR data, which can be collected using EcoSAR. In this paper we describe EcoSAR system in light of its interferometric capabilities and investigate forest structure retrieval techniques.
Osmanoglu, Batuhan↗
Forest Structure Characterization Using JPL's UAVSAR Multi-Baseline Polarimetric SAR Interferometry and Tomography
This paper concerns forest remote sensing using JPL's multi-baseline polarimetric interferometric UAVSAR data. It presents exemplary results and analyzes the possibilities and limitations of using SAR Tomography and Polarimetric SAR Interferometry (PolInSAR) techniques for the estimation of forest structure. Performance and error indicators for the applicability and reliability of the used multi-baseline (MB) multi-temporal (MT) PolInSAR random volume over ground (RVoG) model are discussed. Experimental results are presented based on JPL's L-band repeat-pass polarimetric interferometric UAVSAR data over temperate and tropical forest biomes in the Harvard Forest, Massachusetts, and in the La Amistad Park, Panama and Costa Rica. The results are partially compared with ground field measurements and with air-borne LVIS lidar data.
UAVSAR (Uninhabited Aerial Vehicle SAR)↗
Interferometric synthetic aperture radar imagery of the Gulf Stream
The advent of interferometric synthetic aperture radar (INSAR) imagery brought to the ocean remote sensing field techniques used in radio astronomy. Whilst details of the interferometry differ between the two fields, the basic idea is the same: Use the phase information arising from positional differences of the radar receivers and/or transmitters to probe remote structures. The interferometric image is formed from two complex synthetic aperture radar (SAR) images. These two images are of the same area but separated in time. Typically the time between these images is very short -- approximately 50 msec for the L-band AIRSAR (Airborne SAR). During this short period the radar scatterers on the ocean surface do not have time to significantly decorrelate. Hence the two SAR images will have the same amplitude, since both obtain the radar backscatter from essentially the same object. Although the ocean surface structure does not significantly decorrelate in 50 msec, surface features do have time to move. It is precisely the translation of scattering features across the ocean surface which gives rise to phase differences between the two SAR images. This phase difference is directly proportional to the range velocity of surface scatterers. The constant of proportionality is dependent upon the interferometric mode of operation.
Ainsworth, T. L.↗
Observations of the Sea Ice Cover Using Satellite Radar Interferometry
The fringes observed in repeat pass interferograms are expressions of surface relief and relative displacements. The limiting condition in the application of spaceborne radar interferometry to the remote sensing of the sea ice cover is the large magnitude of motion between repeat passes. The translation and rotation of ice floes tend to decorrelate the observations rendering radar interferometry ineffective. In our study, we have located three images in the high Arctic during a period when there was negligible motion between repeat observations. The fringes obtained from these images show a wealth of information about the sea ice cover which is important in atmosphere-ice interactions and sea ice mechanics. These measurements provide the first detailed remote sensing view of the sea ice cover. Ridges can be observed and their heights estimated if the interferometric baseline allows. We have observed ridges with heights greater than 4m. The variability in the phase measurements over an area provides an indication of the large scale roughness. Relative centimetric displacements between rigid ice floes have been observed. We illustrate these observations with examples extracted from the interferograms formed from this set of ERS-1 SAR images.
sea ice cover, satellite, radar, interferometry↗