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All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Production and Distribution of NASA MODIS Remote Sensing Products

The two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on-board NASA's Earth Observing System (EOS) Terra and Aqua satellites make key measurements for understanding the Earth's terrestrial ecosystems. Global time-series of terrestrial geophysical parameters have been produced from MODIS/Terra for over 7 years and for MODIS/Aqua for more than 4 1/2 years. These well calibrated instruments, a team of scientists and a large data production, archive and distribution systems have allowed for the development of a new suite of high quality product variables at spatial resolutions as fine as 250m in support of global change research and natural resource applications. This talk describes the MODIS Science team's products, with a focus on the terrestrial (land) products, the data processing approach and the process for monitoring and improving the product quality. The original MODIS science team was formed in 1989. The team's primary role is the development and implementation of the geophysical algorithms. In addition, the team provided feedback on the design and pre-launch testing of the instrument and helped guide the development of the data processing system. The key challenges the science team dealt with before launch were the development of algorithms for a new instrument and provide guidance of the large and complex multi-discipline processing system. Land, Ocean and Atmosphere discipline teams drove the processing system requirements, particularly in the area of the processing loads and volumes needed to daily produce geophysical maps of the Earth at resolutions as fine as 250 m. The processing system had to handle a large number of data products, large data volumes and processing loads, and complex processing requirements. Prior to MODIS, daily global maps from heritage instruments, such as Advanced Very High Resolution Radiometer (AVHRR), were not produced at resolutions finer than 5 km. The processing solution evolved into a combination of processing the lower level (Level 1) products and the higher level discipline specific Land and Atmosphere products in the MODIS Science Investigator Lead Processing System (SIPS), the MODIS Adaptive Processing System (MODAPS), and archive and distribution of the Land products to the user community by two of NASA s EOS Distributed Active Archive Centers (DAACs). Recently, a part of MODAPS, the Level 1 and Atmosphere Archive and Distribution System (LAADS), took over the role of archiving and distributing the Level 1 and Atmosphere products to the user community.

Wolfe, Robert↗
NASA NTRSDate not supplied

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗
NASA NTRS2010

The Crustal Dynamics Data Information System: A Resource to Support Scientific Analysis Using Space Geodesy

Since 1982. the Crustal Dynamics Data Information System (CDDIS) has supported the archive and distribution of geodetic data products acquired by the National Aeronautics and Space Administration (NASA) as well as national and international programs. The CDDIS provides easy, timely, and reliable access to a variety of data sets, products, and information about these data. These measurements. obtained from a global network of nearly 650 instruments at more than 400 distinct sites, include DORIS (Doppler Orbitography and Radiopositioning Integrated by Satellite), GNSS (Global Navigation Satellite System), SLR and LLR (Satellite and Lunar Laser Ranging), and VLBI (Very Long Baseline Interferometry). The CDDIS data system and its archive have become increasingly important to many national and international science communities, particularly several of the operational services within the International Association of Geodesy (IAG) and its observing system the Global Geodetic Observing System (GGOS), including the International DORIS Service (IDS), the International GNSS Service (IGS). the International Laser Ranging Service (ILRS), the International VLBI Service for Geodesy and Astrometry (IVS). and the International Earth rotation and Reference frame Service (IERS), Investigations resulting from the data and products available through the CDDIS support research in many aspects of Earth system science and global change. Each month, the CDDIS archives more than one million data and derived product files totaling over 90 Gbytes in volume. In turn. the global user community downloads nearly 1.2 TBytes (over 10.5 million files) of data and products from the CDDIS each month. The requirements of analysts have evolved since the start of the CDDIS; the specialized nature of the system accommodates the enhancements required to support diverse data sets and user needs. This paper discusses the CDDIS. including background information about the system and its. user communities. archive contents. available metadata, and future plans.

Noll. Carey E.↗
NASA NTRS2003

The NASA Earth Observing System (EOS) Terra and Aqua Mission Moderate Resolution Imaging Spectroradiometer (MODIS: Science and Applications

The Moderate Resolution Imaging Spectroradiometer (MODIS) on the Earth Observing System (EOS) Terra Mission began to produce data in February 2000. The EOS Aqua mission was launched successfully May 4,2002 with another MODIS on it and "first light" observations occurred on June 24,2002. The Terra MODIS is in a sun-synchronous orbit going north to south in the daylight portion of the orbit crossing the equator at about 1030 hours local time. The Aqua spacecraft operates in a sun-synchronous orbit going south to north in the daylight portion of the orbit crossing the equator at approximately 1330 hours local time. The spacecraft, instrument, and data systems for both MODIS instruments are performing well and are producing a wide variety of data products useful for scientific and applications studies in relatively consistent fashion extending from November 2000 to the present. Within the approximately 40 MODIS data products, several are new and represent powerful and exciting capabilities such the ability to provide observations over the globe of fire occurrences, microphysical properties of clouds and sun-stimulated fluorescence from phytoplankton in the surface waters of the ocean. The remainder of the MODIS products exceeds or, at a minimum, matches the capabilities of products from heritage sensors such as, for example, the Advanced Very High Resolution Radiometer (AVHRR). Efforts are underway to provide data sets for the greater Earth science community and to improve access to these products at the various Distributed Active Archive Centers (DAAC's) or through Direct Broadcast (DB) stations.

Salomnson, Vincent V.↗
NASA NTRS1992

Multi-frequency multi-polarization processing for spaceborne SAR

The Shuttle Imaging Radar-C (SIR-C) is the third in a series of space shuttle based synthetic aperture radars (SAR) sponsored by the National Aeronautics and Space Administration (NASA). The SIR-C ground data processing system is to process the playbacked SAR signal data into a variety of data products for distribution to the science community. An overview of the end-to-end ground data processing system with emphasis on the unique characteristics involved in the system design is presented. Included in the discussion are science requirements, radar system specifications, input data format specifications, system operations design, data products design, processing algorithm design, hardware architecture design, and software design.

Curlander, John C.↗
NASA NTRS1993

The Extreme Ultraviolet Explorer archive

The objectives and data products of the EUVE public archive, created to handle the storage, maintenance, and distribution of EUVE data and ancillary documentation, information, and software, are briefly reviewed. Archive data products presently include calibration target spectra, a catalog of past and future calibration targets, the EUVE Bright Source List, extreme ultraviolet skymaps and images of extended sources, a list of approved guest observer targets, a bibliography of EUVE publications, and C routines to calculate interstellar medium transmission at EUV wavelengths.

Polomski, E.↗
NASA NTRS1993

Multimission image processing and science data visualization

The Operational Science Analysis (OSA) Functional area supports science instrument data display, analysis, visualization and photo processing in support of flight operations of planetary spacecraft managed by the Jet Propulsion Laboratory (JPL). This paper describes the data products generated by the OSA functional area, and the current computer system used to generate these data products. The objectives on a system upgrade now in process are described. The design approach to development of the new system are reviewed, including use of the Unix operating system and X-Window display standards to provide platform independence, portability, and modularity within the new system, is reviewed. The new system should provide a modular and scaleable capability supporting a variety of future missions at JPL.

Green, William B.↗
NASA NTRS1997

NASA as a Catalyst: Use of Satellite Data in the States

NASA revolutionized our view of the world in 1972 with the launch of the first satellite to monitor the Earth. Recognizing the importance of states in governing the United States, NASA then established a program in the late 1970s to educate and assist states in using satellite data products. This report reviews this brief, but beneficial program that laid a foundation and catalyzed satellite data work that continues today in several states. More recently, outreach efforts as part of NASAs Mission to Planet Earth program and growing state government roles, responsibilities, and initiatives led NASA to begin a new effort in 1994 to understand and work effectively with states. This effort included an investigation and synthesis of current satellite data conditions in each of the 50 states that are included in this report. It provided strong evidence that some state governments are applying satellite data to an increasing array of government needs, while other states have very limited applications to date. A wide range of satellite data applications in executive branch agencies are described, as well as the recent status of the Gap Analysis Program in each of the states with this program. The report also reviews the status of satellite data and geographic information coordination efforts in each of the 50 states. In addition to this investigation, NASA convened a meeting of representatives of 12 states experienced with satellite data to identify future satellite data uses and needs, as well as NASA opportunities to enhance the utility of satellite data products. The findings and recommendations from this meeting, the 50 state investigations, and NASAs past state programs are also included in the report; they provide the rationale for NASA to establish a new outreach effort with state governments in the late 1990s.

Warnecke, Lisa↗
NASA NTRS2009

Data Processing for Atmospheric Phase Interferometers

This paper presents a detailed discussion of calibration procedures used to analyze data recorded from a two-element atmospheric phase interferometer (API) deployed at Goldstone, California. In addition, we describe the data products derived from those measurements that can be used for site intercomparison and atmospheric modeling. Simulated data is used to demonstrate the effectiveness of the proposed algorithm and as a means for validating our procedure. A study of the effect of block size filtering is presented to justify our process for isolating atmospheric fluctuation phenomena from other system-induced effects (e.g., satellite motion, thermal drift). A simulated 24 hr interferometer phase data time series is analyzed to illustrate the step-by-step calibration procedure and desired data products.

Acosta, Roberto J.↗
NASA NTRS1973

Apollo lunar sounder experiment

The four basic data products from the ALSE are sounding, profiling, imaging, and noise measurements. Attention was concentrated on the first three products, and both theory and preliminary results are presented. Background information is presented on the experiment and on the data products. Preliminary examples of the types of analyses that can be performed and the conclusions to which they can lead are included. Preliminary analysis of the data for subsurface features was successful in indicating with a high probability the capability of the ALSE to achieve its fundamental goal of substrate sounding. The imagery and profiling data are useful immediately for geologic interpretation, as demonstrated.

Phillips, R. J.↗
NASA NTRS2017

Development and Assessment of the SMAP Enhanced Passive Soil Moisture Product

Launched in January 2015, the National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) observatory was designed to provide frequent global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using a radar and a radiometer operating at L-band frequencies. Despite a hardware mishap that rendered the radar inoperable shortly after launch, the radiometer continues to operate nominally, returning more than two years of science data that have helped to improve existing hydrological applications and foster new ones.Beginning in late 2016 the SMAP project launched a suite of new data products with the objective of recovering some high-resolution observation capability loss resulting from the radar malfunction. Among these new data products are the SMAP Enhanced Passive Soil Moisture Product that was released in December 2016, followed by the SMAPSentinel-1 Active-Passive Soil Moisture Product in April 2017.This article covers the development and assessment of the SMAP Level 2 Enhanced Passive Soil Moisture Product (L2_SM_P_E). The product distinguishes itself from the current SMAP Level 2 Passive Soil Moisture Product (L2_SM_P) in that the soil moisture retrieval is posted on a 9 km grid instead of a 36 km grid. This is made possible by first applying the Backus-Gilbert optimal interpolation technique to the antenna temperature (TA) data in the original SMAP Level 1B Brightness Temperature Product to take advantage of the overlapped radiometer footprints on orbit. The resulting interpolated TA data then go through various correctioncalibration procedures to become the SMAP Level 1C Enhanced Brightness Temperature Product (L1C_TB_E). The L1C_TB_E product, posted on a 9 km grid, is then used as the primary input to the current operational SMAP baseline soil moisture retrieval algorithm to produce L2_SM_P_E as the final output. Images of the new product reveal enhanced visual features that are not apparent in the standard product. Based on in situ data from core validation sites and sparse networks representing different seasons and biomes all over the world, comparisons between L2_SM_P_E and in situ data were performed for the duration of April 1, 2015 October 30, 2016. It was found that the performance of the enhanced 9 km L2_SM_P_E is equivalent to that of the standard 36 km L2_SM_P, attaining a retrieval uncertainty below 0.040 m(exp 3)/m(exp 3) unbiased root-mean-square error (ubRMSE) and a correlation coefficient above 0.800. This assessment also affirmed that the Single Channel Algorithm using the V-polarized TB channel (SCA-V) delivered the best retrieval performance among the various algorithms implemented for L2_SM_P_E, a result similar to a previous assessment for L2_SM_P.

Enhanced↗
NASA NTRS2017

Challenges in Obtaining and Visualizing Satellite Level 2 Data in GIS

Satellite data products are important for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if the satellite data are well utilized and interpreted. Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. One way to help users better understand the satellite data is to provide data along with Images, including accurate pixel coverage area delineation, and science team recommended quality screening for individual geophysical parameters. However, there are challenges of visualizing remote sensed non-gridded products: (1) different geodetics of space-borne instruments (2) data often arranged in a long-track and a cross-track axes (3) spatially and temporally continuous data chunked into granule files: data for a portion (or all) of a satellite orbit (4) no general rule of resampling or interpolations to a grid (5) geophysical retrieval only based on pixel center location without shape information. In this presentation, we will unravel a new Goddard Earth Sciences Data and Information Services Center (GES DISC) Level 2 (L2) visualization on-demand service. The service's front end provides various visualization and data accessing capabilities, such as overlay and swipe of multiply variables and subset and download of data in different formats. The backend of the service consists of Open Geospatial Consortium (OGC) standard-compliant Web Mapping Service (WMS) and Web Coverage Service. The infrastructure allows inclusion of outside data sources served in OGC compliant protocols and allows other interoperable clients, such as ArcGIS clients, to connect to our L2 WCS/WMS.

GI↗
NASA NTRS2010

MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

Riggs, George A.↗
NASA NTRS2011

Status of Aqua MODIS Instrument On-Orbit Operation and Calibration

The Aqua MOderate resolution Imaging Spectroradiometer (MODIS) has successfully operated for nearly a decade, since its launch in May 2002. MODIS was developed and designed with improvements over its heritage sensors in terms of its overall spectral, spatial, and temporal characteristics, and with more stringent calibration requirements. MODIS carries a set of on-board calibrators that can be used to track and monitor its on-orbit radiometric, spectral, and spatial performance. Since launch, extensive instrument calibration and characterization activities have been scheduled and executed by the MODIS Characterization Support Team (MCST). These efforts are made to assure the quality of instrument calibration and L 1B data products, as well as support all science disciplines (land, ocean, and atmospheric) for continuous improvements of science data product quality. MODIS observations from both Terra and Aqua have significantly contributed to the science and user community over a wide range of research activities and applications. This paper provides an overview of Aqua MODIS on-orbit operation and calibration activities, instrument health status, and on-board calibrators (OBC) performance. On-orbit changes of key sensor parameters, such as spectral band radiometric responses, center wavelengths, and bandwidth, are illustrated and compared with those derived from its predecessor, Terra MODIS. Lessons and challenges identified from Aqua MODIS performance are also discussed in this paper. These lessons are not only critical to future improvements of Aqua MODIS on-orbit operation and calibration but also beneficial to its follow-on instrument, the Visible Infrared Imager Radiometer Suite (VIIRS) to be launched on NPOESS Preparatory Project (NPP) spacecraft.

Xiong, Jack↗
NASA NTRSDate not supplied

Hydrological Data at the NASA GES DISC: Current Capabilities and New Opportunities

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of twelve NASA Earth science data centers that document, process, archive and distribute data from Earth observation missions and projects. GES DISC maintains an archive of several hydrology datasets, including the Land Data Assimilation Systems (LDAS) and the Gravity Recovery and Climate Experiment (GRACE) Data Assimilation for Drought Monitoring (GRACE-DA-DM) data products. These datasets include model output of heat fluxes, rain, snow, soil temperature, soil moisture, and runoff; and observational forcing data, including surface pressure, temperature, precipitation, downward shortwave and longwave radiation, humidity, and wind. The temporal resolution of the hydrology data at GES DISC ranges from hourly to monthly, and spatial resolutions range from 0.1° to 1.0°. The GES DISC provides services which enable users to aggregate, temporally and spatially subset, regrid, and visualize archived data including the GES DISC Subsetter, Hydrology Data Rods, and the Geospatial Interactive Online Visualization and Analysis Infrastructure (GIOVANNI). The Hydrology Data Rods service optimally reorganizes large hydrological data sets as extended time series, providing more efficient access for the hydrological community. The time series data (aka “data rods”) were integrated into hydrology community tools, such as the Data Rods Explorer on HydroShare. Furthermore, the GES DISC is in the process of migrating its data and services to the cloud. Hydrological data available at the GES DISC are now available in the Amazon Web Services (AWS) cloud (us-west-2 region) providing users Direct S3 data access and the capability for cloud computing operations. In this presentation, the hydrology data products and services currently available at the GES DISC will be summarized. Also discussed are the migration to the cloud, user support through this transition, and the status of migrating the data rods service to the cloud.

Ashley Heath↗
NASA NTRSDate not supplied

Understanding the Uncertainty and Variability of Earth’s Radiation Budget Components Over the Past 3 Decades from the NASA’s GEWEX Surface Radiation Budget Release 4 Integrated Product

The NASA/GEWEX Surface Radiation Budget (SRB) project produced a 30+ year time series of 3-hourly Top-of-Atmosphere (TOA) and surface radiative flux components at a 1x1 degree resolution. This SRB Release 4 Integrated Productare derived using imager data products from the cross-calibrated from ISCCP (International Satellite Cloud Climatology Project) “HSeries” radiance, cloud and surface property data products. The ISCCP HXS product replaces ISCCP DX with a ninefold increase in pixel count (10km instead of 30km). ISCCP also provides an atmospheric temperature and moisture dataset known as nnHIRS which we use and discuss radiative flux sensitivities to in this presentation. Total solar irradiance is now variable consistent with SORCE measurements. Sea surface (SeaFlux v2.0) and land surface products (LandFlux) are utilized to achieve an radiative flux estimatesintegrated with global data sets from these GEWEX projects. The variable aerosol composition are specified using a detailed aerosol history from the Max Planck Institute Aerosol Climatology (MAC) also used for background aerosol in the ISCCP HX. Numerous other improvements were made to the SW and LW algorithms including improved cloud optical property treatments and specification of surface spectral albedo and emissivity for various surface conditions. Here we analyze the new SWand LWSRB datasets, comparing them to the previous Release 3, BSRN, GEBA and PMEL surface measurements, and ERBE and CERES satellite datasets. For surface flux validation besides ensemble comparisons, we show the variability of SRB vs surface measurements from BSRN beginning in 1992 and GEBA SW from 1983. We assess the variability of the surface flux anomalies, particularly the net fluxes and the cloud radiative effects, over the entire time period including the period containing CERES overlap. For the TOA fluxes, the anomalies of the fluxes in the early period are compared to the MEaSURES ERBE and the latter period to CERES EBAF/SYN1Deg datasets for a benchmark. Long-term changes in the surface radiation budget components and cloud radiative effects are shown and discussed relative to CERES and surface measurements. This includes a change point analysis that helps associate various changes in the ISCCP GEO/LEO configurations and other inputs to variations in the radiative budget components.

Earth Radiation Budget↗
NASA NTRS2011

Evolution of Space Shuttle Range Safety Ascent Flight Envelope Design

For every space vehicle launch from the Eastern Range in Florida, the range user must provide specific Range Safety (RS) data products to the Air Force's 45th Space Wing in order to obtain flight plan approval. One of these data products is a set of RS ascent flight envelope trajectories that define the normal operating region of the vehicle during powered flight. With the Shuttle Program launching 135 manned missions over a 30-year period, 135 envelope sets were delivered to the range. During this time, the envelope methodology and design process evolved to support mission changes, maintain high data quality, and reduce costs. The purpose of this document is to outline the shuttle envelope design evolution and capture the lessons learned that could apply to future spaceflight endeavors.

Brewer, Joan↗
NASA NTRS2007

Online Remote Sensing Interface

BasinTools Module 1 processes remotely sensed raster data, including multi- and hyper-spectral data products, via a Web site with no downloads and no plug-ins required. The interface provides standardized algorithms designed so that a user with little or no remote-sensing experience can use the site. This Web-based approach reduces the amount of software, hardware, and computing power necessary to perform the specified analyses. Access to imagery and derived products is enterprise-level and controlled. Because the user never takes possession of the imagery, the licensing of the data is greatly simplified. BasinTools takes the "just-in-time" inventory control model from commercial manufacturing and applies it to remotely-sensed data. Products are created and delivered on-the-fly with no human intervention, even for casual users. Well-defined procedures can be combined in different ways to extend verified and validated methods in order to derive new remote-sensing products, which improves efficiency in any well-defined geospatial domain. Remote-sensing products produced in BasinTools are self-documenting, allowing procedures to be independently verified or peer-reviewed. The software can be used enterprise-wide to conduct low-level remote sensing, viewing, sharing, and manipulating of image data without the need for desktop applications.

Lawhead, Joel↗