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NASA NTRS1992

Radar Analysis and Visualization Environment (RAVEN): Software for polarimetric radar analysis

Imaging radar data provides information about the geometric and dielectric properties of the Earth's surface. The Jet Propulsion Laboratory (JPL) polarimetric Airborne Synthetic Aperture Radar (AIRSAR) is currently obtaining imaging radar data for use in geologic, vegetation, snow and ice, and ocean studies. In the near future, the Shuttle Imaging Radar C (SIR-C/X-SAR) and the Earth Observing System Synthetic Aperture Radar (EOS SAR) will also collect polarimetric radar data. A need exists for a user-friendly, interactive software package for analysis of these polarimetric radar data sets. Previous software packages, such as JPL's Multiview, while providing some analysis capabilities for these data, did not allow interactive viewing and were tied to specific image display hardware with operating system dependencies. A prototype software system, the 'Radar Analysis and Visualization Environment' (RAVEN) under development at the Center for the Study of Earth from Space (CSES) at the University of Colorado, is designed to deal with data from the JPL AIRSAR instrument and other proposed polarimetric radar instruments. RAVEN is being developed using the Interactive Data Language (IDL). It takes advantage of high speed disk access and fast processors running under the UNIX operating system in an X-windows environment to allow for rapid, interactive visualization of AIRSAR data in both image and graphical ways. It provides a user-friendly interface through the use of menus, sliders, buttons, and display windows.

Kierein-Young, K. S.↗

NASA NTRSDate not supplied

Application of Lidar-Radar Combined Data Products during the IMPACTS 2020 Field Campaign

The Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) is a three-year field campaign investigating the formation and lifecycle of banded, precipitation structures within intense wintertime cyclones impacting the highly-populated northeast United States. Unlike previous campaigns in the region, IMPACTS mission scientists have access to and coordinate the NASA ER-2 and P-3 aircraft to collect observations from both a remote sensing and in-situ perspective, respectively. For IMPACTS, the ER-2 aircraft was equipped with lidar (CPL), radar (CRS, HIWRAP, EXRAD), microwave radiometer (CoSMIR, AMPR) instruments, each with their own unique capabilities and limitations. Our on-going work effort aims to develop IMPACTS lidar and radar merged data products, which can be used to supplement the raw data sources, tease out additional aspects of the mechanisms underpinning wintertime cyclones, and enhance our understanding of microphysical properties in sensor overlap regions. Preliminary merged data products combine CPL lidar with any one of the NASA High Altitude Radar (HAR) radar products (CRS, HIWRAP, EXRAD) and represent these data as both normalized values and translated to reflectivity signal (dB). Continuing work will further refine our merged data product algorithm to provide additional information on hydrometeor species identification, ice crystal habit, and ice-water content, which will help IMPACTS achieve its mission goal of improving microphysical properties retrievals from both airborne and spaceborne platforms.

Stephen D. Nicholls↗

DOE OSTI2020

Synthetic-aperture radar (SAR) imaging with range-resolved reflection data

SAR imaging may be performed with range-resolved reflection data, where a spread-spectrum signal, such as a code division multiple access (CDMA) signal, is transmitted instead of a simple frequency chirp. The reflected spread-spectrum signal may be analyzed to gather range-resolved reflection data. Range-resolved reflection data may be gathered at each angular view. This data may be used to construct a more accurate approximation of the Fourier transform of the desired image than can be done by a conventional SAR approach. The image may be reconstructed from this Fourier transform using Fourier inversion techniques similar to those used in conventional SAR approaches. The range-resolved reflection scheme generally requires somewhat more processing to recover the image as compared with conventional SAR systems, but provides a significantly more stable image with less degradation from effects that plague conventional SAR systems. This can eliminate the need for phase coherency altogether and also eliminate “phase drift,” which leads to image distortion. This may be especially well suited for high resolution imaging of relatively large targets.

47 OTHER INSTRUMENTATION↗

NASA NTRS1998

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↗

NASA NTRS1984

Development of the Centralized Storm Information System (CSIS) for use in severe weather prediction

The centralized storm information system is now capable of ingesting and remapping radar scope presentations on a satellite projection. This can be color enhanced and superposed on other data types. Presentations from more than one radar can be composited on a single image. As with most other data sources, a simple macro establishes the loops and scheduling of the radar ingestions as well as the autodialing. There are approximately 60 NWS network 10 cm radars that can be interrogated. NSSFC forecasters have found this data source to be extremely helpful in severe weather situations. The capability to access lightning frequency data stored in a National Weather Service computer was added. Plans call for an interface with the National Meteorological Center to receive and display prognostic fields from operational computer forecast models. Programs are to be developed to plot and display locations of reported severe local storm events.

Mosher, F. R.↗

NASA NTRS2006

A-Train Data Depot: Integrating and Visualizing Atmospheric Measurements Along the A-Train Tracks

The succession of US and international satellites that follow each other, seconds to minutes apart, across the local afternoon equator crossing is called the ATrain. The A-Train consists of the following satellites, in order of equator crossing: OCO, EOS Aqua, CloudSat, CALIPSO, PARASOL, and EOS Aura. Flying in such formation increases the number of observations, validates observations, and enables coordination between science observations, resulting in a more complete virtual science platform (Kelly, 2000) The goal of this project is to create the first ever A-Train virtual data portal/center, the A-Train Data Depot, to process, archive, access, visualize, analyze and correlate distributed atmosphere measurements from various A-Train instruments along A-Train tracks. The A-Train Data Depot (ATDD) will enable the free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth s Atmosphere along the A-Train tracks. Once the infrastructure of the ATDD is in place, it will be easily evolved to serve data from all A-Train data measurements: one stop shopping. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) will be accommodated by reusing the GSFC Atmospheric Composition Data and Information Services Center (ACDISC) visualization and analysis tool, GIOVANNI, existing data reduction tools, on-line archwing for fast data access, and Cooperative Institute for Research in the Atmosphere (CRA) data co-registration tools. Initial measurements utilized include CALIPSO lidar backscatter, CloudSat radar reflectivity, clear air relative humidity, water vapor and temperature from AIRS, and cloud properties and aerosols from both MODIS. This will be followed by associated measurements from MLS, OMI, HIRDLS, and TES. Given the independent nature of instrument/platform development, the ATDD project has been met with many interesting challenges that, once resolved, will provide a much greater understanding of the relative flight dynamics and data co-registration of the suite of A-Train instruments, thus greatly increasing the accuracy of A-Train data analysis. Some of these challenges will be discussed. The project s resulting visualizations and analysis illustrate the importance of managing data so that measurements from various missions can be combined to enhance the understanding of the atmosphere. A-Train data management coordination, as performed here, is extremely significant in facilitating the A-Train science of clouds, precipitation, aerosol and chemistry.

Kempler, Steven↗

NASA NTRS2016

Methods for Determining Aircraft Surface State at Lesser-Equipped Airports

Tactical departure scheduling within a terminal airspace must accommodate a wide spectrum of surveillance and communication capabilities at multiple airports. The success of such a scheduler is highly dependent upon the knowledge of a departure's state while it is still on the surface. Airports within a common Terminal RAdar CONtrol (TRACON) airspace possess varying levels of surface surveillance infrastructure which directly impacts uncertainties in wheels-off times. Large airports have access to surface surveillance data, which is shared with the TRACON, while lesser-equipped airports still rely solely on controllers in Air Traffic Control Towers (Towers). Coordination between TRACON and Towers can be greatly enhanced when the TRACON controller has access to the surface surveillance and the associated decision-support tools at well-equipped airports. Similar coordination at lesser-equipped airports is still based on verbal communications. This paper investigates possible methods to reduce the uncertainty in wheels-off time predictions at the lesser-equipped airports through the novel use of Over-the-Air (OTA) data transmissions. We also discuss the methods and equipment used to collect sample data at lesser-equipped airports within a large US TRACON, as well as the data evaluation to determine if meaningful information can be extracted from it.

departure scheduling↗

NASA NTRS1984

Prospects for three-dimensional projective and tomographic imaging radar networks

Results of a study demonstrating the feasibility of broadband and speckle-free projective imaging of a complex shaped scattering object in the 6-17 GHz range with centimeter resolution are presented. It is shown how angular, spectral, and polarization diversities can be combined in the data acquisition process with a unique target-derived reference technique to access the three-dimensional Fourier space of the scatterer cost-effectively. Imagea retrieval algorithms, based on the projection slice theorem and knowledge of object symmetry, are utilized in obtaining images of a model aircraft with near optical resolution. The implications for high-resolution three-dimensional tomographic imaging radar networks are discussed.

Farhat, N. H.↗

NASA NTRS1981

AVE-SESAME program for the REEDA System

The REEDA system software was modified and improved to process the AVE-SESAME severe storm data. A random access file system for the AVE storm data was designed, tested, and implemented. The AVE/SESAME software was modified to incorporate the random access file input and to interface with new graphics hardware/software now available on the REEDA system. Software was developed to graphically display the AVE/SESAME data in the convention normally used by severe storm researchers. Software was converted to AVE/SESAME software systems and interfaced with existing graphics hardware/software available on the REEDA System. Software documentation was provided for existing AVE/SESAME programs underlining functional flow charts and interacting questions. All AVE/SESAME data sets in random access format was processed to allow developed software to access the entire AVE/SESAME data base. The existing software was modified to allow for processing of different AVE/SESAME data set types including satellite surface and radar data.

Hickey, J. S.↗

NASA NTRS1976

Radar characteristics of Viking 1 landing sites

Radar observations of Mars at centimeter wavelengths in May, June, and July 1976 provided estimates of surface roughness and reflectivity in three potential landing areas for Viking 1. Surface roughness is characterized by the distribution of surface landing slopes or tilts on lateral scales of the order of 1 to 10 meters; measurements of surface reflectivity are indicators of bulk surface density in the uppermost few centimeters. By these measures, the landing site at 47.5 deg W, 22.4 deg N is rougher than the Martian average, although it may be near the average for elevations accessible to Viking, and is estimated to be near the Mars average in reflectivity. The site at the center of Chryse Planitia, 43.5 deg W, 23.4 deg N, may be an area of anomalous radar characteristics, indicative of extreme, small-scale roughness, very low surface density, or a combination of these two characteristics. Observations of the original Chryse site at 34 deg W, 19.5 deg N indicate that that area is at least twice as rough as the Mars average.

Tyler, G. L.↗

NASA NTRS2006

A-Train Data Depot: Integrating, Visualizing, and Extracting Cloudsat, CALIPSO, MODIS, and AIRS Atmospheric Measurements Along the A-Train Tracks

The succession of US and international Earth observing satellites that follow each other, seconds to minutes apart, across the local afternoon equator crossing is called the ATrain. The A-Train consists of the following satellites, in order of equator crossing: OCO, EOS Aqua, CloudSat, CALIPSO, PARASOL, and EOS Aura. Flying in such formation increases the number of observations, validates observations, and enables coordination between science observations, resulting in a more complete virtual science platform (Kelly, 2000). The goal of this project is to create the first ever A-Train virtual data portal/center, the A-Train Data Depot (ATDD), to process, archive, access, visualize, analyze and correlate distributed atmosphere measurements from various A-Train instruments along A-Train tracks. The ATDD will enable the free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. Once the infrastructure of the ATDD is in place, it will be easily evolved to serve data from all A-Train data measurements: one stop shopping. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) will be accommodated by reusing the GSFC Atmospheric Composition Data and Information Services Center (ACDISC) visualization and analysis tool, GIOVANNI, existing data reduction tools, on-line archiving for fast data access, access to remote data without unnecessary data transfers, and data retrieval by users finding data desirable for further study. Initial measurements utilized include CALIPSO lidar backscatter, CloudSat radar reflectivity, clear air relative humidity, water vapor and temperature from AIRS, and cloud properties and aerosols from both MODIS. This will be foilowed by associated measurements from TVILS, =MI, HIRDLS, sad TES. Given the independent nature of instrumentlplatform development, the ATDD project has been met with many interesting challenges that, once resolved, will provide a much greater understanding of the relative flight dynamics and data co-registration of the suite of A-Train instruments, thus greatly increasing the accuracy of A-Train data analysis. Some of these challenges will be illustrated and discussed. The project's early visualizations and analysis efforts illustrate the importance of managing data so that measurements from various missions can be combined to enhance the understanding of the atmosphere. A-Train data management coordination, as performed here, is extremely significant in facilitating the A-Train science of clouds, precipitation, aerosol and chemistry.

Kempler, Steven↗

NASA NTRSDate not supplied

Florida Water Resources: Assessing Coastal Resiliency Across Florida's Aquatic Preserves Response To Hurricane Forces

Intensifying weather events, sea level rise, and extensive coastal development in Southwestern Florida are escalating the need for Florida’s mangrove conservation. These mangroves are imperative for coastline stabilization, habitat provision for native species, and water quality management. Our partner, the Florida Department of Environmental Protection (FDEP), Office of Resilience and Coastal Protection is tasked with monitoring and conserving the Charlotte Harbor, Estero Bay, Rookery Bay, and Pinellas County Aquatic Preserves. We developed the Growth, Resilience, and Optical Vegetation Evaluator (GROVE) Google Earth Engine toolset for partners to determine mangrove forest extent through time, analyze mangrove forest health, and collect several water quality parameters within the preserves from January 2002–August 2022. The toolset provides easily accessible data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Landsat 9 Operational Land Imager 2 (OLI-2), and the Shuttle Radar Topography Mission (SRTM). Using training datasets of known mangrove forest locations, we also established a machine learning approach to create mangrove extent maps. Maps from all four preserves indicated migration of mangrove forests inland as the greatest areas of change were transitional zones. Additionally, normalized difference vegetation index (NDVI), normalized difference turbidity index (NDTI), and chlorophyll-a maps were generated for the partners. This project provides decision makers with a useful tool for understanding temporal changes in Florida’s aquatic preserves, identifying areas of ecological stress, and providing actionable data to make informed plans for mangrove preservation.

Samuel Perrello↗

NASA NTRS2022

Florida Water Resources: Assessing Coastal Resiliency Across Florida's Aquatic Preserves in Response to Hurricane Forces

Remote sensing↗

NASA NTRS1999

"An On-Line Access System for TRMM Data"

The Tropical Rainfall Measuring Mission (TRMM), jointly sponsored by the National Aeronautics and Space Administration (NASA) of United States and the National Space Development Agency (NASDA) of Japan, provides visible, infrared, and microwave observations of tropical and subtropical rain system. The satellite observations are complemented by ground radar and rain gauge measurements to validate satellite rain estimation techniques. TRMM satellite was launched on November 27, 1997(EST). Data from TRMM are being archived, processed, and disseminated by DAAC at the Goddard Space Flight Center (GSFC) of NASA. The Goddard DAAC has been archiving Tropical Rainfall Measuring Mission (TRMM) data since the launch. The TRMM level 1 and level 2 products first have been released to public on June 15, 1998. Now, most of TRMM products, including some ground validation products are released to public. TRMM data are useful for forecast model research, disaster mitigation, climatological studies, agricultural predictions, and many other applications. An online system or user interface is designed for easy, friendly, and quick display, access, and ordering of the TRMM data. Components, features, and limitations of the system will be discussed and demonstrated. The TRMM standard products and variety of the subsets and ancillary data will be shown, and their availability will be discussed.

Rui, Hualan↗

NASA NTRS2022

Assessing Several Non-Traditional Data Sources for Value in Aviation Safety

The NASA System-Wide Safety (SWS) project and its predecessor projects have been developing Machine Learning (ML) algorithms for commercial aviation safety for many years. These algorithms have been applied to Flight Operations Quality Assurance (FOQA); radar track data (e.g., Threaded Track); and safety reports, including Aviation Safety Reporting System (ASRS) and Aviation Safety Action Plan (ASAP). SWS is working with partners to get access to other data that air carriers provide, such as maintenance data, and has been assisting carriers in working with other data, such as Line Operations Safety Audit (LOSA) data, using manual methods. However, the project has discussed whether there are other data that are not traditionally used in aviation safety analysis that may be useful. This paper discusses four sets of data and models that are not traditionally used in aviation safety but that have shown promise for such use. In the future, we plan to incorporate such data into ML algorithms to use with data that we have used before and determine the additional benefit that is actually achieved under different contexts from the inclusion of these non-traditional data sources.

Nikunj C. Oza↗

NASA NTRS1999

Radar Reconnaissance of Near-Earth Asteroids

Groundbased radar observations of NEAs can help identify space resources with commercial potential and can dramatically reduce the cost and risk of the initial spacecraft missions to those objects. The near Earth asteroid (NEA) population is thought to contain approx. 1500 objects as large as a kilometer, approx. 300,000 as large as 100 meters, and more than 100,000,000 as large as 10 meters. More than 10% of the NEAs are more accessible in terms of mission delta-V (i.e., fuel required) than the Moon, Mars, or the moons of Mars. Fewer than 1000 NEAs have been found, but the discovery rate is increasing rapidly. Once an asteroid is discovered (necessarily by wide-field optical telescopes), radar can provide otherwise unavailable information about its size, shape, spin state, and surface properties if it approaches within the range of the Goldstone (California) or Arecibo (Puerto Rico) radar telescopes. Asteroids generally appear as unresolved points through groundbased optical telescopes, but radar measurements of the distribution of echo power in time delay (range) and Doppler frequency (radial velocity) can yield images with resolution as fine as a decameter. Image sequences that furnish adequate orientational coverage can be inverted to construct geologically detailed 3-D models, to define the rotation state precisely, and to constrain the object's internal density distribution. Estimates of radar scattering properties characterize the surface's cm-to-m-scale roughness as well as its bulk density, which for asteroids depends primarily on porosity and metal concentration. A useful spin-off of radar detection is orbit refinement that simplifies navigation of flyby and rendezvous spacecraft.

Ostro, S. J.↗

NASA NTRS1999

Radar Reconnaissance of Near-Earth Asteroids

Groundbased radar observations of NEAs can help identify space resources with commercial potential and can dramatically reduce the cost and risk of the initial spacecraft missions to those objects. The near-Earth asteroid (NEA) population is thought to contain approximately 1500 objects as large as a kilometer, approximately 300,000 as large as 100 meters, and more than 100,000,000 as large as 10 meters. More than 10% of the NEAs are more accessible in terms of mission delta-V (i.e., fuel required) than the Moon, Mars, or the moons of Mars. Fewer than 1000 NEAs have been found, but the discovery rate is increasing rapidly. Once an asteroid is discovered (necessarily by wide-field optical telescopes), radar can provide otherwise unavailable information about its size, shape, spin state, and surface properties if it approaches within the range of the Goldstone (California) or Arecibo (Puerto Rico) radar telescopes. Asteroids generally appear as unresolved points through groundbased optical telescopes, but radar measurements of the distribution of echo power in time delay (range) and Doppler frequency (radial velocity) can yield images with resolution as fine as a decameter. Image sequences that furnish adequate orientational coverage can be inverted to construct geologically detailed 3-D models, to define the rotation state precisely, and to constrain the object's internal density distribution. Estimates of radar scattering properties characterize the surface's cm-to-m-scale roughness as well as its bulk density, which for asteroids depends primarily on porosity and metal concentration. A useful spin-off of radar detection is orbit refinement that simplifies navigation of flyby and rendezvous spacecraft.

Ostro, S. J.↗

NASA NTRS2016

Supporting Hydrometeorological Research and Applications with Global Precipitation Measurement (GPM) Products and Services

Precipitation is an important dataset in hydrometeorological research and applications such as flood modeling, drought monitoring, etc. On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http:pmm.nasa.govGPM). The GPM mission consists of an international network of satellites in which a GPM Core Observatory satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data. The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). GPM products currently available include the following:1. Level-1 GPM Microwave Imager (GMI) and partner radiometer products2. Goddard Profiling Algorithm (GPROF) GMI and partner products (Level-2 and Level-3)3. GPM dual-frequency precipitation radar and their combined products (Level-2 and Level-3)4. Integrated Multi-satellitE Retrievals for GPM (IMERG) products (early, late, and final run)GPM data can be accessed through a number of data services (e.g., Simple Subset Wizard, OPeNDAP, WMS, WCS, ftp, etc.). A newly released Unified User Interface or UUI is a single interface to provide users seamless access to data, information and services. For example, a search for precipitation products will not only return TRMM and GPM products, but also other global precipitation products such as MERRA (Modern Era Retrospective-Analysis for Research and Applications), GLDAS (Global Land Data Assimilation Systems), etc.New features and capabilities have been recently added in GIOVANNI to allow exploring and inter-comparing GPM IMERG (Integrated Multi-satelliE Retrievals for GPM) half-hourly and monthly precipitation products as well as other precipitation products such as TRMM, MERRA, NLDAS, GLDAS, etc. GIOVANNI is a web-based tool developed by the GES DISC, to visualize and analyze Earth science data without having to download data and software. During the GPM era, the GES DISC will continue to develop and provide data services for supporting applications. We will update and enhance existing TRMM applications (Current Conditions, the USDA Crop Explorer, etc.) with higher spatial resolution IMERG products. In this presentation, we will present GPM data products and services with examples.

GPM↗