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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Exploring Whether Subsurface Fluid Production Can Minimize Triggered Seismicity in Geothermal Fields

Fluid injection and production related to energy recovery and other industrial operations alter the pressure and stress state of subsurface reservoirs which can lead to induced seismicity. Here, the primary goal is to investigate the hypothesis that the modulation of stress state in subsurface reservoirs through fluid injection/production operations can reduce the likelihood of inducing seismicity. Validation of this mitigation strategy will provide an active operational method to control induced seismicity in subsurface reservoir exploitations such as geothermal energy recovery and carbon storage. In this project, we analyze the relationship between extensive fluid production and the paucity of aftershock activity at the Coso Geothermal plant (CGP) following the 2019 Ridgecrest earthquake sequence, where high rates of aftershock triggering were expected. We developed a high-fidelity multiphase coupled thermo-hydro-mechanical (THM) model to simulate fluid injection/production activities at the CGP between 1986 and 2020. THM results of surface subsidence due to high rates of fluid production agree well with field observations from global positioning system (GPS) and interferometric synthetic aperture radar (InSAR). Subsequently, the variations of pore pressure, temperature and stress state were used to drive numerical earthquake simulations of the aftershock response to the 2019 Ridgecrest earthquakes. The earthquake simulations show that seismic quiescence may occur following the Ridgecrest event, depending on the initial stress state at the time of the mainshock and at the initiation of geothermal energy production. Seismic quiescence occurs in 20% of the cases we explored, where rates are decreased by 50% of the background rate in the two years following the mainshock. In circumstances where aftershock rates increase near the CGP following Ridgecrest, the average rate change is a factor of two larger than background rates from simulations with no operations. These findings indicate that unlike many other operations that bring faults closer to failure, operations at the CGP are acting to stabilize faults such that triggering in the current stress state is minimal.

58 GEOSCIENCES↗
DOE OSTI2024

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are exploring hidden geothermal resources in the U.S.A. and designing profitable enhanced geothermal systems (EGS). Many processes and parameters control geothermal exploration and energy production from geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize subsurface geothermal conditions. Sparse and multi-scale characteristics of these datasets prohibit properly leveraging these datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) promise to resolve these issues. The tremendous challenges and risks of geothermal exploration and production bring the demand for novel ML methods and tools that can (1) analyze large field datasets, (2) assimilate model simulations (large inputs and outputs), (3) process sparse datasets, (4) perform transfer learning (between sites with different exploratory levels), (5) extract hidden geothermal signatures in the field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. To address these necessities, ML-based geothermal resources exploration and enhanced geothermal systems (EGS) design tools have been developed. The exploration tool is called GeoThermalCloud and EGS design tool is called GeoDT-ML. GeoThermalCloud (https://github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. Also, it enables the identification of critical measurements needed to identify geothermal resource signatures. Alternatively, GeoDT-ML (https://github.com/SmartTensors/GeoThermalCloud.jl/tree/master/EGS) is an ML-based alternative to GeoDT (https://github.com/GeoDesignTool/GeoDT.git), a fast, simplified multi-physics solver to evaluate EGS project designs in uncertain geologic systems. GeoDT-ML leverages recent advances in deep learning and high-performance computing. It is a faster and simpler version of GeoDT. To make this project a success, we used capabilities of LANL, PNNL, Google, Stanford, and Julia Computing. We analyzed eight datasets of the U.S.A. using GeothermalCloud and demonstrated potential highly prospective geothermal resources and identified key factors defining highly prospective sites. The first data set includes 44 locations in southwest New Mexico and 18 geological, hydrogeological, geophysical, geothermal, geochemical attributes. We defined low- and medium-temperature hydrothermal systems and discovered a new highly prospective site. The second data set analyzed 18 shallow water chemistry attributes at 14,342 locations in the Great Basin. It demarcated modestly, moderately, and highly prospective sites including key attributes for each type of prospectivity. The third data set analyzed Utah FORGE data including satellite (InSAR), geophysical (gravity, seismic), geochemical, and geothermal attributes. Here, we performed prospectivity analysis to identify future drilling locations using geological, geochemical, and geophysical attributes. Maps of temperature at depth and heat flow are constructed based on the available data. Prospectivity maps were generated, and drilling locations were proposed for future geothermal field exploration. The fourth data set analyzed 21 attributes at 120 locations in Tularosa Basin, New Mexico; data comes from past play fairway analyses in this region. ML analyses identified geothermal signatures associated with modestly, moderately, and highly hydrothermal systems. We also defined dominant attributes and spatial distribution of the geothermal signatures. The fifth, sixth, seventh, and eighth datasets include Tohatchi Springs, New Mexico, Hawaii, Brady site, Nevada, and EGS Collab, respectively. Moreover, we coupled GeothermalCloud and magnetotellurics data to pinpoint drilling locations for developing geothermal projects in the Tularosa Basin, New Mexico. GeothermalCloud found potential prospective locations for geothermal resources near White Sands Missile Range and McGregor Range at Fort Bliss. Magnetotellurics data determined the potential depth (~1800m) of geothermal prospects at McGregor Range based on apparent resistivity structures/layers in the subsurface. The McGregor Range consists of three resistivity layers and two resistivity structures. Magnetotellurics data also helps identify that the western portion of the McGregor Range has thick and low-resistivity earth materials. The low resistivity to the west is most likely for a fault system. Assuming temperature is consistent with a geothermal reservoir, the west-central part of the McGregor Range has the highest geothermal potential because of the increase in porosity and associated permeability attributed to the interpreted fault system. Also, we devised a coupling strategy between a process model and GeothermalCloud to characterize hydrogeological conditions and geothermal conditions, respectively. The process model characterizes hydrogeological and geothermal conditions on highly prospective geothermal sites provided by GeothermalCloud. We developed a physics-informed neural network (PINN) version of the Burns equation that can be easily coupled with GeothermalCloud. Furthermore, we performed an optimal design decision maximizing the economic value of an EGS power plant. This study optimized the range of well spacing between injection and production wells maximizing net present value in dollars (NPV). For this task, we used the GeoDT to simulate the Utah FORGE EGS development cycle from the initial well design to the end of production. Next, we accomplished another crucial task, which is predicting permeability of geothermal reservoirs. Predicting permeability of geothermal reservoirs is a non-trivial task because of huge computational runtime of simulation and lack of measurements. To avoid these limitations, we used easy-to-measure chemical concentrations in the subsurface as measurement data and convolutional neural network based ML model of a high-fidelity model. Next, we predicted permeability using Markov chain Monte Carlo simulation. We found that Markov chain Monte Carlo simulation predicts permeability with a high certainty if the prediction zone in the simulation area has chemical concentration data. Finally, we analyzed the DOE funded INGENIOUS and GeoDAWN projects data. For discovering hidden geothermal systems in the Great Basin, the INGENIOUS project accumulated old data, collected new data, and released them in 2022. The dataset includes a total of 24 geological, geophysical, and geochemical attributes. Data resolution and scale significantly vary prohibiting an appropriate usage. To avoid such limitations, we brought all data in the same resolution and scale by applying the inverse distance weighting interpolation technique for predicting data in unsampled locations. Subsequently, we analyzed LiDAR data of the GeoDAWN project. We received data in tiles format. The DOE’s overarching goal is to use ML on LiDAR data for finding favorable geological structures (e.g., step up faults in Brady, Nevada). To serve the purpose, we need to label favorable geologic structures that correspond to LiDAR data. We wrote an algorithm to label the LiDAR data with the favorable geologic structures.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Hydrological connectivity: a review and emerging strategies for integrating measurement, modeling, and management

This review synthesizes methods for measuring, modeling, and managing hydrologic connectivity, offering pathways to improve practices and address environmental challenges (e.g., climate change) and sustainability. As a key driver of water movement and nutrient cycling, hydrologic connectivity influences flood mitigation, water quality regulation, and biodiversity conservation. However, traditional field-based methods (e.g., dye tracing), indirect measurements (e.g., runoff analysis), and remote sensing techniques (e.g., InSAR) often struggle to capture the complexity of catchment-scale interactions. Similarly, modeling approaches—including process-based and percolation theory-based models, graph theory, and entropy-based metrics—face limitations in fully representing these interconnected processes. Both modeling and measurement techniques are constrained by inadequate spatial and temporal coverage, high data demands, computational complexity, and difficulties in representing subsurface connectivity. Subsequently, we critique current management practices that prioritize isolated variables (e.g., streamflow, sediment transport) over system-wide strategies and emphasize the need for adaptive, connectivity-based approaches in water resource planning and restoration. Moving forward, we highlight the importance of interdisciplinary collaboration, technological innovations (e.g., AI-driven modeling, real-time monitoring), and integrated frameworks to improve connectivity measurement, modeling, and adaptive management to restore fragmented hydrologic networks. This integrated approach sets the stage for transformative water resource management, fostering proactive policy development and stakeholder engagement.

Dwivedi, Dipankar↗
NASA NTRS1992

Registration of interferometric SAR images

Interferometric synthetic aperture radar (INSAR) is a new way of performing topography mapping. Among the factors critical to mapping accuracy is the registration of the complex SAR images from repeated orbits. A new algorithm for registering interferometric SAR images is presented. A new figure of merit, the average fluctuation function of the phase difference image, is proposed to evaluate the fringe pattern quality. The process of adjusting the registration parameters according to the fringe pattern quality is optimized through a downhill simplex minimization algorithm. The results of applying the proposed algorithm to register two pairs of Seasat SAR images with a short baseline (75 m) and a long baseline (500 m) are shown. It is found that the average fluctuation function is a very stable measure of fringe pattern quality allowing very accurate registration.

Lin, Qian↗
NASA NTRS1993

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.↗
NASA NTRS1995

Bayes classification of interferometric TOPSAR data

We report the Bayes classification of terrain types at different sites using airborne interferometric synthetic aperture radar (INSAR) data. A Gaussian maximum likelihood classifier was applied on multidimensional observations derived from the SAR intensity, the terrain elevation model, and the magnitude of the interferometric correlation. Training sets for forested, urban, agricultural, or bare areas were obtained either by selecting samples with known ground truth, or by k-means clustering of random sets of samples uniformly distributed across all sites, and subsequent assignments of these clusters using ground truth. The accuracy of the classifier was used to optimize the discriminating efficiency of the set of features that was chosen. The most important features include the SAR intensity, a canopy penetration depth model, and the terrain slope. We demonstrate the classifier's performance across sites using a unique set of training classes for the four main terrain categories. The scenes examined include San Francisco (CA) (predominantly urban and water), Mount Adams (WA) (forested with clear cuts), Pasadena (CA) (urban with mountains), and Antioch Hills (CA) (water, swamps, fields). Issues related to the effects of image calibration and the robustness of the classification to calibration errors are explored. The relative performance of single polarization Interferometric data classification is contrasted against classification schemes based on polarimetric SAR data.

Michel, T. R.↗
NASA NTRS1995

Estimation of penetration of forest canopies by Interferometric SAR measurements

In contrast to traditional Synthetic Aperture Radar (SAR), an Interferometric SAR (INSAR) yields two additional measurements: the phase difference and the correlation between the two interferometric channels. The phase difference has been used to estimate topographic height. For homogeneous surfaces, the correlation depends on the system signal-to-noise (SNR) ratio, the interferometer parameters, and the local slope. In the presence of volume scattering, such as that encountered in vegetation canopies, the correlation between the two channels is also dependent on the degree of penetration of the radiation into the scattering medium. In this paper, we propose a method for removing system and slope effects in order to obtain the decorrelation due to penetration alone. The sensitivities and accuracy of the proposed method are determined by Monte Carlo experiments, and we show that the proposed technique has sufficient sensitivity to provide penetration measurements for airborne SAR systems. Next, we provide a theoretical model to estimate the degree of penetration in a way which is independent of the details of the scattering medium. We also present a model for the correlation from non-homogeneous layers. We assess the sensitivity of the proposed inversion technique to these inhomogeneous situations. Finally, we present a comparison of the interferometric results against in situ data obtained by an airborne laser profilometer which provides a direct measurement of tree height and an estimate of the vegetation density profile in the forested areas around Mt. Adams, WA.

Rodriguez, Ernesto↗
NASA NTRS1996

Geocoding of AIRSAR/TOPSAR SAR Data

It has been demonstrated and recognized that radar interferometry is a promising method for the determination of digital elevation information and terrain slope from Synthetic Aperture Radar (SAR) data. An important application of Interferometric SAR (InSAR) data in areas with topographic variations is that the derived elevation and slope can be directly used for the absolute radiometric calibration of the amplitude SAR data as well as for scattering mechanisms analysis. On the other hand polarimetric SAR data has long been recognized as permitting a more complete inference of natural surfaces than a single channel radar system. In fact, imaging polarimetry provides the measurement of the amplitude and relative phase of all transmit and receive polarizations. On board the NASA DC-8 aircraft, NASA/JPL operates the multifrequency (P, L and C bands) multipolarimetric radar AIRSAR. The TOPSAR, a special mode of the AIRSAR system, is able to collect single-pass interferometric C- and/or L-band VV polarized data. A possible configuration of the AIRSAR/TOPSAR system is to acquire single-pass interferometric data at C-band VV polarization and polarimetric radar data at the two other lower frequencies. The advantage of this system configuration is to get digital topography information at the same time the radar data is collected. The digital elevation information can therefore be used to correctly calibrate the SAR data. This step is directly included in the new AIRSAR Integrated Processor. This processor uses a modification of the full motion compensation algorithm described by Madsen et al. (1993). However, the Digital Elevation Model (DEM) with the additional products such as local incidence angle map, and the SAR data are in a geometry which is not convenient, since especially DEMs must be referred to a specific cartographic reference system. Furthermore, geocoding of SAR data is important for multisensor and/or multitemporal purposes. In this paper, a procedure to geocode the new AIRSAR/TOPSAR data is presented. As an example an AIRSAR/TOPSAR image acquired in 1994 is geocoded and evaluated in terms of geometric accuracy.

Holecz, Francesco↗
NASA NTRS1996

The Information Content of Interferometric Synthetic Aperture Radar: Vegetation and Underlying Surface Topography

This paper first gives a heuristic description of the sensitivity of Interferometric Synthetic Aperture Radar to vertical vegetation distributions and underlying surface topography. A parameter estimation scenario is then described in which the Interferometric Synthetic Aperture Radar 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 Interferometric Synthetic Aperture Radar observations for single-baseline, single-frequency, single-incidence-angle, single-polarization Interferometric Synthetic Aperture Radar. Using ancillary ground-truth data to compensate for the underdetermination of the parameters, forest depths are estimated from the INSAR data. A recently-analyzed multibaseline data set is also discussed and the potential for stand-alone Interferometric Synthetic Aperture Radar parameter estimation is assessed. The potential of combining the information content of Interferometric Synthetic Aperture Radar with that of infrared/optical remote sensing data is briefly discussed.

Treuhaft, Robert N.↗
NASA NTRS1999

Deformation of Alaskan Volcanoes, Measured by Satellite Radar Inferometry

The purpose of this project was to determine the suitability of measuring active deformation of volcanoes in Alaska using Interferometric Synthetic Aperture Radar (INSAR) techniques. Work sponsored by this grant supported one graduate student (for almost 2 years) and one postdoc (for several months), and has resulted in two published peer-reviewed papers and a front-page article in EOS. An additional paper is in review and a fourth is in preparation. An additional paper in preparation was based in part on research supported by this grant and in part by a successor grant from NASA's Solid Earth Natural Hazards program. Over the course of this research, we documented measurable uplift of Trident volcano in the Katmai group, conducted a systematic study of the change in phase coherence over time on volcanic surfaces, and measured and modeled the spectacular 1.5 m deflation of Okmok caldera associated with its 1997 eruption. We also generated initial interferograms spanning the 1996 seismic swarm of Akutan volcano; however, during the period covered by this project we were not able to remove topography. That has been done under the subsequent funding and a paper is now in preparation. This report summarizes work done under two separate contracts because both were based on the same proposal to NASA's ADRO (Application Development and Research Opportunity) program. The first year was funded out of a grant from NASA Headquarters and the second and third years out of a grant through Goddard. The work, however, was a continuous three year effort.

Freymueller, Jeff↗
NASA NTRS1999

Calibration of the Geosar Dual Frequency Interferometric SAR

GeoSAR is an airborne, interferometric Synthetic Aperture Radar (INSAR) system for terrain mapping, currently under development by a consortium including NASA's Jet Propulsion Laboratory (JPL), Calgis, Inc., and the California Department of Conservation (CalDOC) with funding provided by the Topographic Engineering Center (TEC) of the U.S. Army Corps of Engineers and the Defense Advanced Research Projects Agency (DARPA). The radar simultaneously maps swaths on both sides of the aircraft at two frequencies, X-Band and P-Band. For the P-Band system, data is collected for two across track interferometric baselines and at the crossed polarization. The aircraft position and attitude are measured using two Honeywell Embedded GPS Inertial Navigation Units (EGI) and an Ashtech Z12 GPS receiver. The mechanical orientation and position of the antennas are actively measured using a Laser Baseline Metrology System (LBMS). In the GeoSAR motion measurement software, these data are optimally combined with data from a nearby ground station using Ashtech PNAV software to produce the position, orientation, and baseline information are used to process the dual frequency radar data. Proper calibration of the GeoSAR system is essential to obtaining digital elevation models (DEMS) with the required sub-meter level planimetric and vertical accuracies. Calibration begins with the determination of the yaw and pitch biases for the two EGI units. Common range delays are determined for each mode, along with differential time and phase delays between channels. Because the antennas are measured by the LBMS, baseline calibration consists primarily of measuring a constant offset between mechanical center and the electrical phase center of the antennas. A phase screen, an offset to the interferometric phase difference which is a function of absolute phase, is applied to the interferometric data to compensate for multipath and leakage. Calibration parameters are calculated for each of the ten processing modes, each of the operational bandwidths (80 and 160 MHZ), and each aircraft altitude. In this talk we will discuss the layout calibration sites, the synthesis of data from multiple flights to improve the calibration, methods for determining time and phase delays, and techniques for determining radiometric and polarimetric quantities. We will describe how calibration quantities are incorporated into the processor and pre-processor. We will demonstrate our techniques applied to GeoSar data and assess the stability and accuracy of the calibration. This will be compared to the modeled performance determined from calibrating the output of a point target simulator. The details of baseline determination and phase screen calculation are covered in related talks.

Chapine, Elaine↗
NASA NTRS2000

Shuttle Radar Topography Mission (SRTM) Flight System Design and Operations Overview

This paper provides an overview of the Shuttle Radar Topography Mission (SRTM), with emphasis on flight system implementation and mission operations from systems engineering perspective. Successfully flown in February, 2000, the SRTM's primary payload consists of several subsystems to form the first spaceborne dual-frequency (C-band and X-band) fixed baseline interferometric synthetic aperture radar (InSAR) system, with the mission objective to acquire data sets over 80% of Earth's landmass for height reconstruction. The paper provides system architecture, unique design features, engineering budgets, design verification, in-flight checkout and data acquisition of the SRTM payload, in particular for the C-band system. Mission operation and post-mission data processing activities are also presented. The complexity of the SRTM as a system, the ambitious mission objective, the demanding requirements and the high interdependency between multi-disciplined subsystems posed many challenges. The engineering experience and the insight thus gained have important implications for future spaceborne interferometric SAR mission design and implementation.

Shen, Yuhsyen↗
NASA NTRS2003

Fault Creep along the Southern San Andreas from Interferometric Synthetic Aperture Radar, Permanent Scatterers, and Stacking

Interferometric synthetic aperture radar (InSAR) provides a practical means of mapping creep along major strike-slip faults. The small amplitude of the creep signal (less than 10 mm/yr), combined with its short wavelength, makes it difficult to extract from long time span interferograms, especially in agricultural or heavily vegetated areas. We utilize two approaches to extract the fault creep signal from 37 ERS SAR images along the southem San Andreas Fault. First, amplitude stacking is utilized to identify permanent scatterers, which are then used to weight the interferogram prior to spatial filtering. This weighting improves correlation and also provides a mask for poorly correlated areas. Second, the unwrapped phase is stacked to reduce tropospheric and other short-wavelength noise. This combined processing enables us to recover the near-field (approximately 200 m) slip signal across the fault due to shallow creep. Displacement maps fiom 60 interferograms reveal a diffuse secular strain buildup, punctuated by localized interseismic creep of 4-6 mm/yr line of sight (LOS, 12-18 mm/yr horizontal). With the exception of Durmid Hill, this entire segment of the southern San Andreas experienced right-lateral triggered slip of up to 10 cm during the 3.5-year period spanning the 1992 Landers earthquake. The deformation change following the 1999 Hector Mine earthquake was much smaller (4 cm) and broader than for the Landers event. Profiles across the fault during the interseismic phase show peak-to-trough amplitude ranging from 15 to 25 mm/yr (horizontal component) and the minimum misfit models show a range of creeping/locking depth values that fit the data.

Lyons, Suzanne↗
NASA NTRS2002

The 1999 (Mw 7.1) Hector Mine, California, Earthquake: Near-Field Postseismic Deformation from ERS Interferometry

Interferometric synthetic aperture radar (InSAR) data over the area of the Hector Mine earthquake (Mw 7.1, 16 October 1999) reveal postseismic deformation of several centimeters over a spatial scale of 0.5 to 50 km. We analyzed seven SAR acquisitions to form interferograms over four time periods after the event. The main deformations seen in the line-of-sight (LOS) displacement maps are a region of subsidence (60 mm LOS increase) on the northern end of the fault, a region of uplift (45 mm LOS decrease) located to the northeast of the primary fault bend, and a linear trough running along the main rupture having a depth of up to 15 mm and a width of about 2 km. We correlate these features with a double left-bending, rightlateral, strike-slip fault that exhibits contraction on the restraining side and extension along the releasing side of the fault bends. The temporal variations in the near-fault postseismic deformation are consistent with a characteristic time scale of 135 + 42 or - 25 days, which is similar to the relaxation times following the 1992 Landers earthquake. High gradients in the LOS displacements occur on the fault trace, consistent with afterslip on the earthquake rupture. We derive an afterslip model by inverting the LOS data from both the ascending and descending orbits. Our model indicates that much of the afterslip occurs at depths of less than 3 to 4 km.

Jacobs, Allison↗
NASA NTRS2004

Understanding Sea Level Changes

Today more than 100 million people worldwide live on coastlines within one meter of mean sea level; any short-term or long-term sea level change relative to vertical ground motion is of great societal and economic concern. As palm-environment and historical data have clearly indicated the existence and prevalence of such changes in the past, new scientific information regarding to the nature and causes and a prediction capability are of utmost importance for the future. The 10-20 cm global sea-level rise recorded over the last century has been broadly attributed to two effects: (1) the steric effect (thermal expansion and salinity-density compensation of sea water) following global climate; (2) mass-budget changes due to a number of competing geophysical and hydrological processes in the Earth-atmosphere-hydrosphere-cryosphere system, including water exchange from polar ice sheets and mountain glaciers to the ocean, atmospheric water vapor and land hydrological variations, and anthropogenic effects such as water impoundment in artificial reservoirs and extraction of groundwater, all superimposed on the vertical motions of solid Earth due to tectonics, rebound of the mantle from past and present deglaciation, and other local ground motions. As remote-sensing tools, a number of space geodetic measurements of sea surface topography (e.g., TOPEX/Poseidon, Jason), ice mass (e.g., ICESat), time-variable gravity (e.g. GRACE), and ground motions (SLR, VLBI, GPS, InSAR, Laser altimetry, etc.) become directly relevant. Understanding sea level changes "anywhere, anytime" in a well-defined terrestrial reference frame in terms of climate change and interactions among ice masses, oceans, and the solid Earth, and being able to predict them, emerge as one of the scientific challenges in the Solid Earth Science Working Group (SESWG, 2003) conclusions.

Chao, Benjamin F.↗
NASA NTRS2005

Workshop on Radar Investigations of Planetary and Terrestrial Environments

Contents include the following: Salt Kinematics and InSAR. SAR Interferometry as a Tool for Monitoring Coastal Changes in the Nile River Delta of Egypt. Modem Radar Techniques for Geophysical Applications: Two Examples. WISDOM Experiment on the EXOMARS ESA Mission. An Ice Thickness Study Utilizing Ground Penetrating Radar on the Lower Jamapa. Probing the Martian Subsurface with Synthetic Aperture Radar. Planetary Surface Properties from Radar Polarimetric Observations. Imaging the Sub-surface Reflectors : Results From the RANETA/NETLANDER Field Test on the Antarctic Ice Shelf. Strategy for Selection of Mars Geophysical Analogue Sites. Observations of Low Frequency Low Altitude Plasma Oscillations at Mars and Implications for Electromagnetic Sounding of the Subsurface. Ionospheric Transmission Losses Associated with Mars-orbiting Radar. A Polarimetric Scattering Model for the 2-Layer Problem. Radars for Imaging and Sounding of Polar Ice Sheets. Strata: Ground Penetrating Radar for Mars Rovers. Scattering Limits to Depth of Radar Investigation: Lessons from the Bishop Tuff.

Source record↗
NASA NTRS2003

Plans for living on a restless planet sets NASA's solid Earth agenda

What are the most important challenges facing solid Earth science today and over the next two decades? And what is the best approach for NASA, in partnership with other agencies, to address these challenges? A new report, living on a restless planet, provides a blueprint for answering these questions. The top priority for a new spacecraft mission in the area of solid earth science over the next 5 years, according to this report, is a satellite dedicated to interferometric synthetic aperture radar(inSAR).

Earth magnetic field imaging spectroscopy solid ea↗