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NASA NTRS1993

Scattering by Venus' surface

During 1992, Magellan altimetry echoes were processed to yield scattering functions sigma(sub o)(phi) over near-nadir angles phi less than or equal to 10 deg from some 2000 Venus orbits. SAR image strips acquired simultaneously at oblique angles were also reduced to give scattering functions but over a few deg of incidence angle in the range 15 less than or equal to phi less than or equal to 45 deg. By sorting, the altimetry and SAR results can be combined to give composite scattering functions for much of Venus' surface. The data in hand should allow definition of such composite functions for 70-80 percent of Venus at resolutions of 20 km--approximately one million separate functions.

Simpson, R. A.↗

NASA NTRS2007

NASA Tech Briefs, August 2007

Topics include: Program Merges SAR Data on Terrain and Vegetation Heights; Using G(exp 4)FETs as a Data Router for In-Plane Crossing of Signal Paths; Two Algorithms for Processing Electronic Nose Data; Radiation-Tolerant Dual Data Bus; General-Purpose Front End for Real-Time Data Processing; Nanocomposite Photoelectrochemical Cells; Ultracapacitor-Powered Cordless Drill, Cumulative Timers for Microprocessors; Photocatalytic/Magnetic Composite Particles; Separation and Sealing of a Sample Container Using Brazing; Automated Aerial Refueling Hitches a Ride on AFF; Cobra Probes Containing Replaceable Thermocouples; High-Speed Noninvasive Eye-Tracking System; Detergent-Specific Membrane Protein Crystallization Screens; Evaporation-Cooled Protective Suits for Firefighters; Plasmonic Antenna Coupling for QWIPs; Electronic Tongue Containing Redox and Conductivity Sensors; Improved Heat-Stress Algorithm; A Method of Partly Automated Testing of Software; Rover Wheel-Actuated Tool Interface; and Second-Generation Electronic Nose.

Source record↗

NASA NTRS2021

Southwest Water Resources: Monitoring Surface Water Extents of Remote Stock Ponds in the Southwestern United States Using Earth Observing Systems for Enhanced Water Resources Management

Due to increasingly frequent and severe drought conditions in the southwestern US, land managers and livestock producers need to monitor stock ponds with increasing regularity. The ability to assess stock pond water levels with Earth observing satellite systems would enhance monitoring efforts of partners at the US Forest Service, Arizona Department of Game and Fish, and the Diablo Trust. This study employed Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), and Sentinel-2 Multispectral Instrument (MSI) to monitor surface water extent for hundreds of critical stock ponds in Arizona. Using methods adapted from previously developed image processing workflows, this project conducted a time-series analysis to capture seasonal and interannual variations in surface water area between 2013 to 2021. In addition, end users can monitor the surface water extent of stock ponds through the developed Google Earth Engine software tool called Surface Water Identification and Forecasting Tool (SWIFT). SWIFT incorporates the Automated Water Extraction Index, Modified Normalized Difference Water Index, and Tasseled Cap-Wetness Index for optical imagery and the incidence angle, VV and VH polarization bands for Sentinel-1 imagery to detect small water bodies in the study area with an overall accuracy range of 88-93%. These tools will empower our partners to monitor the extents of water in their stock ponds remotely, enabling them to develop data-informed and sustainable management solutions for decades to come.

Rainey Aberle↗

NASA NTRS2024

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↗

NASA NTRSDate not supplied

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↗

NASA NTRS2008

Wavenumber Domain Focusing of Squinted SAR Data with a Curved Orbit Geometry

Synthetic Aperture Radar systems provide raw data that need focusing to achieve full-resolution imaging. Current SAR applications, including interferometry, require accurate, phase-preserving, and precisely co-registered coherent images over large ground swaths with the highest achievable resolution. In addition to these challenges, stripmap SAR data may be acquired with an off-broadside (squinted) geometry, either by design or through platform motion. The precise batch focusing of these large aperture and wide bandwidth data sets is known to require a 2D frequency processing approach. The standard wave domain focusing algorithm, however, is only exact for data acquired on a rectilinear trajectory. We investigate a generalization of the standard omega-k focusing formulation that allows curved data acquisition tracks. The new formulation can be used in conjunction with a known extension for conical, squinted imaging grids. The approximations necessary to allow the generalized geometry are analyzed to determine the range of applicability of the proposed algorithm. The theory is validated using data simulated with parameters similar to the UAVSAR L-band SAR system.

curved orbit geometry↗

NASA NTRS1983

The absolute amplitude calibration of the SEASAT synthetic aperture radar - An intercomparison with other L-band radar systems

The absolute amplitude calibration of the spaceborne Seasat SAR data set is presented based on previous relative calibration studies. A scale factor making it possible to express the perceived radar brightness of a scene in units of sigma-zero is established. The system components are analyzed for error contribution, and the calibration techniques are introduced for each stage. These include: A/D converter saturation tests; prevention of clipping in the processing step; and converting the digital image into the units of received power. Experimental verification was performed by screening and processing the data of the lava flow surrounding the Pisgah Crater in Southern California, for which previous C-130 airborne scatterometer data were available. The average backscatter difference between the two data sets is estimated to be 2 dB in the brighter, and 4 dB in the dimmer regions. For the SAR a calculated uncertainty of 3 dB is expected.

Held, D.↗

NASA NTRS1985

Age-dating volcanic and alluvial surfaces with multipolarization data

A false-color multipolarization version of one of the images of Owens Valley area acquired by the JPL Synthetic Aperture Radar (SAR) is given. A geologic map of the alluvial fans there (Gillespie, 1982) is also given for comparison. In general, brightness in the multipolarization images can be seen to be inversely proportional to the age of the surfaces. A more detailed investigation of the relationship between backscatter and age of the surfaces was undertaken with calibrated aircraft SAR data. The quantitative relationship between backscatter coefficient and age for the three polarizations is shown. The straight lines connecting the measured data points imply a steady-state process, although the process or processes leading to this relationship may have operated at rates that varied with climate fluctuations, such as the glacial ages. It is expected that the relationship between radar brightness and age is a consistent one, and that with the wider availability of calibrated radar backscatter data, these relationships can be less well-known areas. The effect of variable such as past climate fluctuations, tectonic disturbance, and rock type must be understood before extension beyond the Mojave Desert region can be attempted.

Farr, T. G.↗

NASA NTRS1988

Crossed orbit interferometry - Theory and experimental results from SIR-B

Crossed orbit interferometry, which can perform measurements with only one antenna making two images of a scene during two separate passes and can operate even if the orbits are not parallel, is discussed and tested using SIR-B data. It is found that a Doppler refocusing of the SAR azimuth correlation, involving a resampling of one of the imgages in the cross-track direction, is necessary to remove the linear shift of the scene. The refocusing process also involves a terrain dependent resampling in the azimuth direction. A method for finding tie points to guide the resampling is discussed and a coarse altitude map derived only from the tie points is presented. Spatial heterodyned interferograms that contain the effects of the crossed orbit geometry are presented and a theoretical model is developed to explain them. The model is extended to calculate altitudes from the interferograms, and a final altitude map is presented.

Gabriel, Andrew K.↗

NASA NTRS1994

The 1994 International Geoscience and Remote Sensing Symposium (IGARSS 1994)

The papers presented at the symposium focus on remote sensing, particularly on global monitoring of the earth with emphasis on the solution of environmental problems. Topics discussed include remote sensing of clouds and earth troposphere, sea ice remote sensing, optical remote sensing, land monitoring and thermal sensing, atmospheric sounding and monitoring, atmospheric correction, and satellite imaging data. Other subject areas are ecosystems and vegetation monitoring; ocean winds and surface scattering; ocean waves, currents and bathymetry; satellite oceanography; SAR for remote sensing; neural nets application to remote sensing; geographical information systems; and electromagnetic wave propagation. Also discussed environmental monitoring using ERS-1; Topex/Poseidon results; spaceborne instruments; image processing and classification algorithms; and future space missions.

Source record↗

NASA NTRSDate not supplied

HydroSAR: A Cloud-based SAR Data Analysis Service to Monitor Hydrological Disasters and their Impact on Population and Agriculture

Weather-related hazards are ubiquitous around the world including: 1) hurricane storm surges, 2) rapid snowmelt and heavy rainfall, 3) severe weather leading to flash floods, and 4) seasonal freeze and thaw of rivers that may lead to ice jams. Each of these hazards affects human settlements and has the potential to impact agricultural productivity. In each setting, end-users in disaster management need access to data processing tools helpful in mapping past and current disasters. Analysis of past events supports risk mitigation by understanding what has already occurred and how to alleviate those impacts in the future. Having capabilities to generate the same products in a response setting means that lessons learned from risk analysis will carry forward to event response. Synthetic aperture radar (SAR) data are particularly useful for these activities due to their all-weather 24/7 monitoring capabilities. In this effort we present HydroSAR, a cloud-based SAR data analysis service for the mapping of meteorological and hydrological disasters as well as their impact on population and agriculture. As part of this project we have developed a series of SAR-based value added products for the monitoring of surface hydrology (image time series, change detection, flood extent, flood depth) and the assessment of impacts on population (flood depth) and agriculture (active agriculture, inundated agriculture, flood duration). We also developed a cloud-based platform for generating these products over affected areas and are working with end-users to integrate derived product into decision-making workflows The paper will briefly introduce the SAR-based products that were developed for this effort. We describe the cloud-based production pipeline that was built to automatically generate these products in near-real time over extended regions. The integration of SAR-based information into hazard preparation and response activities is described for a number of recent disasters including the 2019 forest fires in Alaska, 2019 flooding in the U.S. Midwest, the 2020 U.S. severe weather easter outbreak, 2020 tropical storm Christobal, 2020 cyclone Amphan, 2020, Alaska Spring breakup flooding, and the 2020 flood season in Eastern India, Bangladesh, and Nepal.

Franz Josef Meyer↗

NASA NTRS1980

Radar image preprocessing

Standard image processing techniques are not applicable to radar images because of the coherent nature of the sensor. Therefore there is a need to develop preprocessing techniques for radar images which will then allow these standard methods to be applied. A random field model for radar image data is developed. This model describes the image data as the result of a multiplicative-convolved process. Standard techniques, those based on additive noise and homomorphic processing are not directly applicable to this class of sensor data. Therefore, a minimum mean square error (MMSE) filter was designed to treat this class of sensor data. The resulting filter was implemented in an adaptive format to account for changes in local statistics and edges. A radar image processing technique which provides the MMSE estimate inside homogeneous areas and tends to preserve edge structure was the result of this study. Digitally correlated Seasat-A synthetic aperture radar (SAR) imagery was used to test the technique.

Frost, V. S.↗

NASA NTRS1981

NASA's oceanic remote sensing plans for the 1980's

An overview of NASA's oceanic remote sensing plans is given, focusing on an attempt to obtain time-varying three-dimensional structure data of the ocean. The first mission is the National Oceanic Satellite System, which is designed to perform an operational demonstration of global sea surface monitoring for NOAA and DOD. TOPEX is the second mission, and it is designed to observe the surface topography of the ocean in order to determine the absolute geostrophic velocity field of the ocean. The third mission, Ocean SAR, has not been defined, but the areas of physical interpretation of oceanic imagery, selection of optimal frequency and depression angle for specific observational needs, and real-time image processing must be considered. It is hoped that oceanic satellite missions will be optimally exploited by the end of the decade.

Wilson, W. S.↗

NASA NTRS2019

Assessing the Use of SAR/Optical Data Fusion and TensorFlow for Improved Mangrove Mapping

Mangrove forests are found in intertidal zones of tropical regions around the world and provide important ecological and economic benefits – they are considered carbon sequesters, habitats for flora and fauna, and natural barriers to hurricanes and tsunamis. Wood from mangrove forests are used as fuel and building materials in surrounding coastal communities, therefore promoting local livelihoods. Despite the importance of these ecosystems, mangrove forests have historically been degraded in natural processes such as severe weather, and anthropogenic factors like conversion to agriculture and aquaculture. This study assesses change in mangrove forests in Nigeria and Mozambique from 2015 to 2018 using SAR and optical data fusion. Due to frequent cloud cover over the study area, SAR and optical data is fused to obtain gap-free imagery without clouds. Landsat-8 OLI and Sentinel-1 imagery is fused with TensorFlow, an open source platform used in developing machine learning models. The resulting images are classified to discriminate mangrove forest cover from other land cover types, and change is estimated using image differencing. Understanding the rates and magnitude of mangrove change across space and time can aid in identifying priority areas for forest regeneration, and can help construct sustainable management practices for the future.

Strattman, Katherine↗

NASA NTRS2023

WET Water Resources: A Google Earth Engine Python API Tool to Automate Wetland Extent Mapping Using Radar Satellite Sensors for Wetland Management and Monitoring

Wetland ecosystems are annually or seasonally wet transition zones between land and water. They provide a range of ecosystem services such as water filtration, flood mitigation, and carbon sequestration, as well as hosting biodiversity hotspots. Although they fulfill fundamental physical and natural processes, wetland extent and health are threatened by anthropogenic influences related to urbanization, population increase, pollution, and climate change. Recognizing the need to quantitatively monitor changes in these recently threatened ecosystems in a timely and cost-effective way, we developed a Google Earth Engine (GEE) Python API tool for automated wetland extent mapping using optical and radar satellite sensors that can be applied globally. The tool will significantly improve wetland change analysis and monitoring as SAR data provides high resolution (5-10 m) imagery, unaffected by cloud cover and light availability (day vs. night), common limitations for other remotely sensed sensors. The tool utilizes Copernicus Sentinel-1 C-band and NISAR L-band (once operational and available on the GEE repository) synthetic aperture radar (SAR) imagery. During image preprocessing, we applied a Terra Moderate Resolution Imaging Spectroradiometer (MODIS) snow product to determine regional snow coverage, which affects land classification sensitivity. Calibration and validation were conducted through a historical change and sensitivity analysis of the Sudd wetland located in central Sudan. The tool was the first of its kind, as it enables NISAR data processing through an open-source GEE repository, further expanding and improving the utility of NASA Earth observations and contributing to NASA Open Science initiatives. We anticipate the tool will be used by researchers and practitioners interested in wetland monitoring and management.

Inundation↗

NASA NTRSDate not supplied

Joint ESA-NASA Multi-Mission Algorithm and Analysis Platform (MAAP)

The scientific community is faced with a need for greatly improved data sharing, analysis, visualization and advanced collaboration based firmly on open science principles. Recent and upcoming launches of new satellite missions with more complex and voluminous data, as well as the ever more urgent need to better understand the global carbon budget and related ecological processes, provided the immediate rational for the ESA-NASA Multi-mission Algorithm and Analysis Platform (MAAP). This highly collaborative joint project of ESA and NASA established a framework between ESA and NASA to share data, science algorithms and compute resources in order to foster and accelerate scientific research conducted by ESA and NASA EO data users. Presented to the public in October 2021, the current version of MAAP provides a common cloud-based platform with computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of global above-ground biomass. Data from the Global Ecosystem Dynamics Investigation (GEDI) mission on the International Space Station and the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) have been instrumental in the first products of MAAP including the first comprehensive map of Boreal above-ground Biomass and a current Global Biomass Harmonization Activity, but the platform is also being specifically designed to support the forthcoming ESA Biomass mission and incorporate data from the upcoming NASA-ISRO SAR (NISAR) mission. While these missions and the corresponding research which includes airborne, field, and calibration/validation data collection and analyses, provide a wealth of data and information relating to global biomass estimation, they also present data storing, processing and sharing challenges. The NISAR mission alone will produce about 80TB/day. These large data volumes present a challenge that would otherwise place accessibility limits on the scientific community and impact scientific progress. Other challenges being addressed by MAAP include: 1) Enabling researchers to easily discover, process, visualize and analyze large volumes of data from both agencies; 2) Providing a wide variety of data in the same coordinate reference frame to enable comparison, analysis, data evaluation, and data generation; 3) Providing a version-controlled science algorithm development environment that supports tools, co-located data and processing resources; and 4) Addressing intellectual property and sharing challenges related to collaborative algorithm development and sharing of data and algorithms. MAAP products can be explored on the MAAP Dashboard at https://earthdata.nasa.gov/maap-biomass or the joint platform entrance at scimaap.net. MAAP also can be accessed through individual NASA (https://maap-project.org) and ESA (https://esa-maap.org/) landing pages.

cloud computing↗

NASA NTRS1987

Bilateral symmetry across Aphrodite Terra

There are three main highland areas on Venus: Beta Regio, Ishtar Terra and Aphrodite Terra. The latter is least known and the least mapped, yet existing analyses of Aphrodite Terra based on available Pioneer-Venus orbiter data suggest that it may be the site of extensive rifting. Some of the highest resolution (30 km) PV data (SAR) included most of the western half of Aphrodite Terra. Recent analysis of the SAR data together with Arecibo range-doppler topographic profiling (10 X 100 km horizontal and 10 m vertical resolution) across parts of Aphrodite, further characterized the nature of possible tectonic processes in the equatorial highlands. The existence of distinct topographic and radar morphologic linear discontinuities across the nearly east-west strike of Aphrodite Terra is indicated. Another prominent set of linear features is distinctly parallel to and orthogonal to the ground tracks of the PV spacecraft and are not included because of the possibility that they are artifacts. Study of the northwest trending cross-strike discontinuities (CSD's) and the nature of topographic and morphologic features along their strike suggest the presence of bilateral topographic and morphologic symmetry about the long axis of Aphrodite Terra.

Crumpler, L. S.↗

NASA NTRS1994

Ocean-ice interaction in the marginal ice zone using synthetic aperture radar imagery

Ocean-ice interaction processes in the marginal ice zone (MIZ) by wind, waves, and mesoscale features, such as up/downwelling and eddies are studied using Earth Remote-Sensing Satellite (ERS) 1 synthetic aperture radar (SAR) images and an ocean-ice interaction model. A sequence of seven SAR images of the MIZ in the Chukchi Sea with 3 or 6 days interval are investigated for ice edge advance/retreat. Simultaneous current measurements from the northeast Chukchi Sea, as well as the Barrow wind record, are used to interpret the MIZ dynamics. SAR spectra of waves in ice and ocean waves in the Bering and Chukchi Sea are compared for the study of wave propagation and dominant SAR imaging mechanism. By using the SAR-observed ice edge configuration and wind and wave field in the Chukchi Sea as inputs, a numerical simulation has been performed with the ocean-ice interaction model. After 3 days of wind and wave forcing the resulting ice edge configuration, eddy formation, and flow velocity field are shown to be consistent with SAR observations.

Liu, Antony K.↗