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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Using Satellite Soil Moisture and Rainfall in the Landslide Hazard Assessment for Situational Awareness System

The Landslide Hazard Assessment for Situational Awareness system(LHASA)gives a global view of landslide hazard in nearly real time. Currently, it is being upgraded from version 1 to version 2, which entails improvements along several dimensions. These include the incorporation of new predictors, machine learning, and new event-based landslide inventories. As a result, LHASA version 2 substantially improves on the prior performanceand introduces a probabilistic element to the global landslide nowcast. Data from the soil moisture active-passive (SMAP) satellite has been assimilated into a globally consistent data product with a latency less than 3 days, known as SMAP Level 4. In LHASA, thesedata representthe antecedent conditions prior to landslide-triggering rainfall. In some cases, soil moisture may have accumulated over aperiod of many months. The model behind SMAP Level 4 also estimates the amount of snow on the ground, which is an important factor in some landslide events. LHASA also incorporates this information as an antecedent condition that modulates the response torainfall. Slope, lithology, and active faults were also used as predictor variables. These factors can have a strong influence on where landslides initiate.LHASA relies on precipitation estimates from the Global Precipitation Measurement mission to identify the locations where landslides are most probable. The low latency and consistent global coverage of these data make them ideal for real-time applications at continental to global scales. LHASA relies primarily on rainfall from the last 24 hours to spothazardous sites, which is rescaled by the local 99thpercentile rainfall.However, the multi-day latency of SMAP requires the use of a 2-day antecedent rainfall variable to represent the accumulation of rain between the antecedent soil moisture and current rainfall. LHASA merges these predictors with XGBoost, a commonly used machine-learning tool, relying on historical landslide inventories to develop the relationship between landslide occurrence and various risk factors. The resulting model relies heavily on current daily rainfall, but other factors also play an important role. LHASA outputsthe probability oflandslide occurrence ona grid of roughly one kilometer over all continents from 60 North to 60 South latitude. Evaluation over the period 2019-2020 showsthat LHASA version 2 doubles the accuracy of the global landslide nowcast without increasing the global false alarm rate. LHASA also identifies the areas where the human exposure to landslide hazard is most intense. Landslide hazard is divided into 4 levels: minimal, low, moderate, and high. Next, the number of persons and the length of major roads (primary and secondary roads)within each of these areas is calculated for every second-level administrative district (county). These results can be viewedthrough a web portal hosted at the Goddard Space Flight Center. In addition, users can download daily hazard and exposure data.LHASAversion 2uses machine learning and satellite data to identify areas of probable landslide hazard within hours of heavy rainfall. Itsglobal maps are significantly more accurate, and it now includes rapid estimates of exposed populations and infrastructure. In addition, a forecast mode will be implemented soon.

Thomas Stanley↗
NASA NTRS2011

NASA's Integrated Instrument Simulator Suite for Atmospheric Remote Sensing from Spaceborne Platforms (ISSARS) and Its Role for the ACE and GPM Missions

Forward simulation is an indispensable tool for evaluation of precipitation retrieval algorithms as well as for studying snow/ice microphysics and their radiative properties. The main challenge of the implementation arises due to the size of the problem domain. To overcome this hurdle, assumptions need to be made to simplify compiles cloud microphysics. It is important that these assumptions are applied consistently throughout the simulation process. ISSARS addresses this issue by providing a computationally efficient and modular framework that can integrate currently existing models and is also capable of expanding for future development. ISSARS is designed to accommodate the simulation needs of the Aerosol/Clouds/Ecosystems (ACE) mission and the Global Precipitation Measurement (GPM) mission: radars, microwave radiometers, and optical instruments such as lidars and polarimeter. ISSARS's computation is performed in three stages: input reconditioning (IRM), electromagnetic properties (scattering/emission/absorption) calculation (SEAM), and instrument simulation (ISM). The computation is implemented as a web service while its configuration can be accessed through a web-based interface.

real-aperture instruments↗
NASA NTRS2019

A Design Methodology for Optimizing and Integrating Composite Materials in Gear Structures

The application of composite materials to gear structures is complex because of the gear shape, the need for precise dimensional tolerances, and the complex dynamic load condition. Methods are presented in this work to design and optimize an integrated composite hub-web structure that can be used as part of a hybrid composite-steel gear. The composite hub-web structure is a planar structure with a large decrease in thickness from the hub to the rim. Methods for design and optimization of this variable-thickness structure are presented along with a method for forming braided prepreg material to conform to the shape of this structure. A layered approach is presented that integrates cut plies or filler materials for thickness buildup with continuous-fiber layers for the primary load path. An additional gear design concept is presented that has an axially extended continuous-fiber composite structure that can be combined with the planar structure. A proposed optimization methodology is introduced where an optimized design is output for each type of optimization simulation. Through this process, composite knowledge can be incorporated in the optimization, and more control is given over the design during the process. The methods in this study provide a tool for designing and optimizing composite structures for gears and other high-power-density applications.

optimization↗
NASA NTRSDate not supplied

Data Sharing in Radiobiology; Towards FAIR

The value of scientific data depends on their findability, accessibility, integrability and reusability according to the FAIR principles. Together with the sustainability of data preservation and access, these principles underpin the long term benefits of scientific research. Within the domain of radiobiology we have a huge array of data types, themes and complexities which make standardisation of metadata, data structure and data integration very challenging. Moreover, it is clear that, for example, in the area of disaster preparedness, the ready discovery and availability of multiple types of data, for example on biological effects of exposure, climatology, ecology, human behavioural and attitudinal studies, is important for an integrated scientific approach. Because these data are spread over many databases, journal supplementary information resources and even the computers of the investigators, their discovery and reuse can be challenging. Despite exhortations from funding agencies and scientific institutions over the past two decades there is still a serious deficit in the willingness and in some cases the ability of investigators to share data, and although much may not be formally „Public domain“, information about the existence of the data, their metadata, and how to obtain them should always be available. We report the progress of work on three databases, the STORE and the NASA GeneLab and LSDA repositories to leverage the Radiation Biology Ontology (RBO), a structured terminology for metadata that can be used by all radiation biology-relevant databases to unite federated and automated data searches across multiple databases, for example using web services, and through semantic web technologies supporting data discovery. The initial primary use-cases for RBO were archiving data in the STORE database (https://www.storedb.org/), the repository used for the RadoNorm and Pianoforte Projects among others, and in the NASA Open Science Data Repository (https://osdr.nasa.gov/bio). The scope of radiobiology research ranges from basic physics to radiation oncology to sociolegal studies; no existing ontology had the necessary breadth or depth to fulfill this need. In addition, a formal ontology has the advantage of being usable for machine learning and, importantly, for tasks like data integration, knowledge extraction from the scientific literature and for query extension and data classification. Standardisation of metadata is one of the primary objectives of the FAIR principles for open data; RBO is an important landmark for FAIR-compliant radiation biology data sharing. The RBO is developed using the open-source tools of GitHub and the OBO Foundry-led Ontology Development Kit, and published through GitHub and the NIH/NCBI BioPortal website. This initial phase of concept modeling has yielded an ontology that has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies with relevance to radiation biology (for example, concepts from the ISO standard Basic Formal Ontology, the Environment Ontology and the Gene Ontology). We welcome input into the development of RBO and encourage its adoption.

ontologies↗
NASA NTRS2023

Data Sharing in Radiation Biology: Towards FAIR

The value of scientific data depends on their findability, accessibility, integrability and reusability according to the FAIR principles. Together with the sustainability of data preservation and access, these principles underpin the long term benefits of scientific research. Within the domain of radiobiology we have a huge array of data types, themes and complexities which make standardisation of metadata, data structure and data integration very challenging. Moreover, it is clear that, for example, in the area of disaster preparedness, the ready discovery and availability of multiple types of data, for example on biological effects of exposure, climatology, ecology, human behavioural and attitudinal studies, is important for an integrated scientific approach. Because these data are spread over many databases, journal supplementary information resources and even the computers of the investigators, their discovery and reuse can be challenging. Despite exhortations from funding agencies and scientific institutions over the past two decades there is still a serious deficit in the willingness and in some cases the ability of investigators to share data, and although much may not be formally "Public domain“, information about the existence of the data, their metadata, and how to obtain them should always be available. We report the progress of work on three databases, the STORE and the NASA GeneLab and LSDA repositories to leverage the Radiation Biology Ontology (RBO), a structured terminology for metadata that can be used by all radiation biology-relevant databases to unite federated and automated data searches across multiple databases, for example using web services, and through semantic web technologies supporting data discovery. The initial primary use-cases for RBO were archiving data in the STORE database (https://www.storedb.org/), the repository used for the RadoNorm and Pianoforte Projects among others, and in the NASA Open Science Data Repository (https://osdr.nasa.gov/bio). The scope of radiobiology research ranges from basic physics to radiation oncology to sociolegal studies; no existing ontology had the necessary breadth or depth to fulfill this need. In addition, a formal ontology has the advantage of being usable for machine learning and, importantly, for tasks like data integration, knowledge extraction from the scientific literature and for query extension and data classification. Standardisation of metadata is one of the primary objectives of the FAIR principles for open data; RBO is an important landmark for FAIR-compliant radiation biology data sharing. The RBO is developed using the open-source tools of GitHub and the OBO Foundry-led Ontology Development Kit, and published through GitHub and the NIH/NCBI BioPortal website. This initial phase of concept modeling has yielded an ontology that has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies with relevance to radiation biology (for example, concepts from the ISO standard Basic Formal Ontology, the Environment Ontology and the Gene Ontology). We welcome input into the development of RBO and encourage its adoption.

ontologies↗
NASA NTRS2009

Real-Time Assessment of Robot Performance During Remote Exploration Operations

To ensure that robots are used effectively for exploration missions, it is important to assess their performance during operations. We are investigating the definition and computation of performance metrics for assessing remote robotic operations in real-time. Our approach is to monitor data streams from robots, compute performance metrics, and provide Web-based displays of these metrics for assessing robot performance during operations. We evaluated our approach for measuring robot performance with the K10 rovers from NASA Ames Research Center during a field test at Moses Lake Sand Dunes (WA) in June 2008. In this paper we present the results of evaluating our software for robot performance and discuss our conclusions from this evaluation for future robot operations.

SBIR TOPIC X7.02 PHASE 1↗
DOE OSTI2021

Remote Home Energy Score Assessments (Feasibility Study)

The delivery of Home Energy Scores (HES) has been significantly impacted over the last year by the recent pandemic and ongoing limitations to person-to-person interactions. There are also historic challenges in providing HES to more remote geographies where assessor infrastructure is not in place. Alternative approaches to in-person, on-site home energy assessments could help address these current restrictions, while also potentially providing opportunities for the efficient delivery of HES in certain use cases after COVID-related restrictions are lifted. From the program administrator’s perspective, there needs to be confidence that the remote scores closely match what they would have been if the assessment had been performed on-site. The recommendations shown on a report generated from a remote score should closely match those of an onsite assessment. A remote assessment should be an option for all HES Partners and have direction on how to deliver those scores. From the HES partner’s and assessor’s perspective, there needs to be understanding of what level of experience is needed, what system infrastructure is required, the time expenditure of the remote assessment process, and the limitations of a remote assessment. From the homeowner’s perspective, there needs to be an awareness and comfort with the time commitment, the level of knowledge of the home, the equipment needed, and any physical requirements of the remote assessment process. During this study, Earth Advantage assessed methods for delivering Home Energy Score assessments remotely through web-based technology platforms and resident interaction in a diverse array of home types in different geographic locations. Earth Advantage developed remote assessment test protocols and integrated those testing protocols into existing Home Energy Score programs being overseen by USDOE Home Energy Score partners New York State Energy Research & Development Authority (NYSERDA), the Oregon Department of Energy (ODOE), and the City of Portland (PDX). Earth Advantage staff acted as the Remote assessor and gathered HES data remotely during the video sessions with participants. Authorized Home Energy Score assessors performed the onsite assessments that were then used to compare with the remote assessment data. This allowed the research to effectively test the efficacy of various remote assessment approaches in a diverse array of home-types. Earth advantage identified the key components of a remote assessment infrastructure which included Remote Home Energy Score Assessments Page vi processes, tools, services, methods and mechanisms that would better enable remote assessments. This report details methods, results, and findings of the HES remote assessment research. In addition, the report provides recommendations and best practices that could be used as guidance for the Home Energy Score administrator and the HES partners seeking to effectively conduct remote assessments.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2003

Compressing Aviation Data in XML Format

Design, operations and maintenance activities in aviation involve analysis of variety of aviation data. This data is typically in disparate formats making it difficult to use with different software packages. Use of a self-describing and extensible standard called XML provides a solution to this interoperability problem. XML provides a standardized language for describing the contents of an information stream, performing the same kind of definitional role for Web content as a database schema performs for relational databases. XML data can be easily customized for display using Extensible Style Sheets (XSL). While self-describing nature of XML makes it easy to reuse, it also increases the size of data significantly. Therefore, transfemng a dataset in XML form can decrease throughput and increase data transfer time significantly. It also increases storage requirements significantly. A natural solution to the problem is to compress the data using suitable algorithm and transfer it in the compressed form. We found that XML-specific compressors such as Xmill and XMLPPM generally outperform traditional compressors. However, optimal use of Xmill requires of discovery of optimal options to use while running Xmill. This, in turn, depends on the nature of data used. Manual disc0ver.y of optimal setting can require an engineer to experiment for weeks. We have devised an XML compression advisory tool that can analyze sample data files and recommend what compression tool would work the best for this data and what are the optimal settings to be used with a XML compression tool.

Patel, Hemil↗
NASA NTRS2013

Planetary Data Systems (PDS) Imaging Node Atlas II

The Planetary Image Atlas (PIA) is a Rich Internet Application (RIA) that serves planetary imaging data to the science community and the general public. PIA also utilizes the USGS Unified Planetary Coordinate system (UPC) and the on-Mars map server. The Atlas was designed to provide the ability to search and filter through greater than 8 million planetary image files. This software is a three-tier Web application that contains a search engine backend (MySQL, JAVA), Web service interface (SOAP) between server and client, and a GWT Google Maps API client front end. This application allows for the search, retrieval, and download of planetary images and associated meta-data from the following missions: 2001 Mars Odyssey, Cassini, Galileo, LCROSS, Lunar Reconnaissance Orbiter, Mars Exploration Rover, Mars Express, Magellan, Mars Global Surveyor, Mars Pathfinder, Mars Reconnaissance Orbiter, MESSENGER, Phoe nix, Viking Lander, Viking Orbiter, and Voyager. The Atlas utilizes the UPC to translate mission-specific coordinate systems into a unified coordinate system, allowing the end user to query across missions of similar targets. If desired, the end user can also use a mission-specific view of the Atlas. The mission-specific views rely on the same code base. This application is a major improvement over the initial version of the Planetary Image Atlas. It is a multi-mission search engine. This tool includes both basic and advanced search capabilities, providing a product search tool to interrogate the collection of planetary images. This tool lets the end user query information about each image, and ignores the data that the user has no interest in. Users can reduce the number of images to look at by defining an area of interest with latitude and longitude ranges.

Stanboli, Alice↗
DOE OSTI2022

Filling gaps in bacterial catabolic pathways with computation and high-throughput genetics

To discover novel catabolic enzymes and transporters, we combined high-throughput genetic data from 29 bacteria with an automated tool to find gaps in their catabolic pathways. GapMind for carbon sources automatically annotates the uptake and catabolism of 62 compounds in bacterial and archaeal genomes. For the compounds that are utilized by the 29 bacteria, we systematically examined the gaps in GapMind’s predicted pathways, and we used the mutant fitness data to find additional genes that were involved in their utilization. We identified novel pathways or enzymes for the utilization of glucosamine, citrulline, myo-inositol, lactose, and phenylacetate, and we annotated 299 diverged enzymes and transporters. We also curated 125 proteins from published reports. For the 29 bacteria with genetic data, GapMind finds high-confidence paths for 85% of utilized carbon sources. In diverse bacteria and archaea, 38% of utilized carbon sources have high-confidence paths, which was improved from 27% by incorporating the fitness-based annotations and our curation. GapMind for carbon sources is available as a web server ( http://papers.genomics.lbl.gov/carbon ) and takes just 30 seconds for the typical genome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Filaments in and between galaxy clusters at low and mid-frequency with the SKA

Context. Understanding the magnetised Universe is a major challenge in modern astrophysics, and cosmic magnetism has been acknowledged as one of the key scientific drivers of the most ambitious radio instrument ever planned, the Square Kilometre Array. Aims. With this work, we aim to investigate the potential of the Square Kilometre Array and its precursors and pathfinders in the study of magnetic fields in galaxy clusters and filaments through diffuse synchrotron radio emission. Galaxy clusters and filaments of the cosmic web are indeed unique laboratories in which to investigate turbulent fluid motions and large-scale magnetic fields in action, and much of what is known about magnetic fields in galaxy clusters comes from sensitive radio observations. Methods. Based on cosmological magneto-hydrodynamic simulations, we predict radio properties (total intensity and polarisation) of a pair of galaxy clusters connected by a cosmic-web filament. Results. We use our theoretical expectations to explore the potential of polarimetric observations to study large-scale structure magnetic fields in the frequency ranges 50–350 MHz and 950–1760 MHz. We also present predictions for galaxy cluster polarimetric observations with the Square Kilometre Array precursors and pathfinders, such as the LOw frequency ARray 2.0 and the MeerKAT+ telescope. Conclusions. Our findings point out that polarisation observations are particularly powerful for the study of large-scale magnetic fields, since they are not significantly affected by confusion noise. The unprecedented sensitivity and spatial resolution of the intermediatefrequency radio telescopes make them the favourite instruments for the study of these sources through polarimetric data, potentially allowing us to understand if the energy density of relativistic electrons is in equipartition with the magnetic field or rather coupled with the thermal gas density. Our results show that low-frequency instruments also represent a precious tool to study diffuse synchrotron emission in total intensity and polarisation.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2008

Eurasian Reindeer Pastoralism in a Changing Climate: Indigenous Knowledge and NASA Remote Sensing

It is intended that Reindeer Mapper/EALAT will be able to provide reindeer herders with an efficient tool for managing the real-time movements and migrations of their herds through enabling improved efficiency in linking different members of the herder settlements or communities and providing real-time local, satellite or other data (e.g., ice melt in lakes and rivers, weather events), thus enabling real time adjustments to herd movements to avoid problems such as changing weather/climate conditions, freeze-thaw "lock-out" problems, or take advantage of availability of better pasturelands along migration routes. The system is being designed to incorporate local data to allow users to bring their own data into the system for analysis in addition to the data provided by the system itself. With the local information of the population, up to date environmental data and habitat characteristics, the system could generate maps depicting important features of interest for reindeer managers. One of the products derived from the planned Reindeer Mapper system will be a web-based graphic display that allows analysts to quickly pinpoint areas of interest such as those with large concentrations of reindeer and provide surrounding environmental information. The system could be automatically updated with near-real-time information such as hourly precipitation and snowfall rate and accumulation, daily surface and air temperatures, and vegetation cover conditions. The system could bring attention to the proximity of human and animal populations as part of the need for control response. A local GIS will bring these many layers together with several supporting models, showing only a straightforward graphic of the real-time situation in the field. Because the system proposed will be operating in the Internet environment, it should be virtually accessible from any network computers and wireless remote access from the field. The International Center for Reindeer Husbandry in Kautokeino, Norway, is providing regional and international coordination of and access to data sets and expertise, and will act as overall clearinghouse for EALAT information.

Maynard, N. G.↗
NASA NTRS2010

Tracking the Short Term Planning (STP) Development Process

Part of the National Aeronautics and Space Administration?s mission is to pioneer the future in space exploration, scientific discovery and aeronautics research is enhanced by discovering new scientific tools to improve life on earth. Sequentially, to successfully explore the unknown, there has to be a planning process that organizes certain events in the right priority. Therefore, the planning support team has to continually improve their processes so the ISS Mission Operations can operate smoothly and effectively. The planning support team consists of people in the Long Range Planning area that develop timelines that includes International Partner?s Preliminary STP inputs all the way through to publishing of the Final STP. Planning is a crucial part of the NASA community when it comes to planning the astronaut?s daily schedule in great detail. The STP Process is in need of improvement, because of the various tasks that are required to be broken down in order to get the overall objective of developing a Final STP done correctly. Then a new project came along in order to store various data in a more efficient database. "The SharePoint site is a Web site that provides a central storage and collaboration space for documents, information, and ideas."

Price, Melanie↗
NASA NTRS2017

Weather from 250 Miles Up: Visualizing Precipitation Satellite Data (and Other Weather Applications) Using CesiumJS

Geospatial weather visualization remains predominately a two-dimensional endeavor. Even popular advanced tools like the Nullschool Earth display 2-dimensional fields on a 3-dimensional globe. Yet much of the observational data and model output contains detailed three-dimensional fields. In 2014, NASA and JAXA (Japanese Space Agency) launched the Global Precipitation Measurement (GPM) satellite. Its two instruments, the Dual-frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI) observe much of the Earth's atmosphere between 65 degrees North Latitude and 65 degrees South Latitude. As part of the analysis and visualization tools developed by the Precipitation Processing System (PPS) Group at NASA Goddard, a series of CesiumJS [Using Cesium Markup Language (CZML), JavaScript (JS) and JavaScript Object Notation (JSON)] -based globe viewers have been developed to improve data acquisition decision making and to enhance scientific investigation of the satellite data. Other demos have also been built to illustrate the capabilities of CesiumJS in presenting atmospheric data, including model forecasts of hurricanes, observed surface radar data, and gridded analyses of global precipitation. This talk will present these websites and the various workflows used to convert binary satellite and model data into a form easily integrated with CesiumJS.

web applications↗
DOE OSTI2025

Fermilab's Transition to Token Authentication

Fermilab is the first High Energy Physics institution to transition from X.509 user certificates to authentication tokens in production systems. All the experiments that Fermilab hosts are now using JSON Web Token (JWT) access tokens in their grid jobs. Many software components have been either updated or created for this transition, and most of the software is available to others as open source. The tokens are defined using the WLCG Common JWT Profile. Token attributes for all the tokens are stored in the Fermilab FERRY system which generates the configuration for the CILogon token issuer. High security-value refresh tokens are stored in Hashicorp Vault configured by htvault-config, and JWT access tokens are requested by the htgettoken client through its integration with HTCondor. The Fermilab job submission system jobsub was redesigned to be a lightweight wrapper around HTCondor. The grid workload management system GlideinWMS which is also based on HTCondor was updated to use tokens for pilot job submission. For automated job submissions a managed tokens service was created to reduce duplication of effort and knowledge of how to securely keep tokens active. The existing Fermilab file transfer tool ifdh was updated to work seamlessly with tokens, as well as the Fermilab POMS (Production Operations Management System) which is used to manage automatic job submission and the RCDS (Rapid Code Distribution System) which is used to distribute analysis code via the CernVM FileSystem. The dCache storage system was reconfigured to accept tokens for authentication in place of X.509 proxy certificates. As some services and sites have not yet implemented token support, proxy certificates are still sent with jobs for backwards compatibility, but some experiments are beginning to transition to stop using them.

Dykstra, Dave [Fermilab] (ORCID:0000000326539015)↗
DOE OSTI2023

Grid Event Signature Library Analytics Report: Signature Matching Tool Development Efforts

This report describes the purpose and features of the Signature Matching Tool (SMT), employed in the Department of Energy (DOE) Grid Event Signature Library (GESL). The SMT supports a user of GESL to identify snippets of electric signatures, usually from sensor devices measuring electric characteristics such as phase voltages and currents, frequency, etc., suspected to represent certain events in the power grid but are not known to the user. The SMT uses a classification method to identify an event of the unknown signature, using the repository of known and labeled signatures in the GESL. The classifier applies a local binary classifier per node (LCN) approach to the unique event tag taxonomy used in the GESL, where training phases are separated based on the Primary labels in the taxonomy, sensor type, and voltage level. Results show that this method helps with computing time during training, in comparison to a flat, multinomial classifier, and produces acceptable average accuracy of 83% across all Primary labels. The report concludes with planned future work including integration to the web interface and API.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2010

Updates of Land Surface and Air Quality Products in NASA MAIRS and NEESPI Data Portals

Following successful support of the Northern Eurasia Earth Sciences Partner Initiative (NEESPI) project with NASA satellite remote sensing data, from Spring 2009 the NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) has been working on collecting more satellite and model data to support the Monsoon Asia Integrated Regional Study (MAIRS) project. The established data management and service infrastructure developed for NEESPI has been used and improved for MAIRS support.Data search, subsetting, and download functions are available through a single system. A customized Giovanni system has been created for MAIRS.The Web-based on line data analysis and visualization system, Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) allows scientists to explore, quickly analyze, and download data easily without learning the original data structure and format. Giovanni MAIRS includes satellite observations from multiple sensors and model output from the NASA Global Land Data Assimilation System (GLDAS), and from the NASA atmospheric reanalysis project, MERRA. Currently, we are working on processing and integrating higher resolution land data in to Giovanni, such as vegetation index, land surface temperature, and active fire at 5km or 1km from the standard MODIS products. For data that are not archived at the GESDISC,a product metadata portal is under development to serve as a gateway for providing product level information and data access links, which include both satellite, model products and ground-based measurements information collected from MAIRS scientists.Due to the large overlap of geographic coverage and many similar scientific interests of NEESPI and MAIRS, these data and tools will serve both projects.

Shen, Suhung↗
NASA NTRS2019

Integrated Analysis of Multiple User Metrics - A “Sequel”; and Introducing the Google Analytic

For decades, the Goddard Earth Sciences Data and Information Services Center (GES DISC) has archived and distributed enormous volumes of NASA Earth science data (accompanied with many developed tools and services) to various research/applications communities and the general public. Being “immersed” in the Big Data era, we have inevitably faced the challenges of our continually increasing archived data in both volume and variety, as well as enhanced user needs and demands. In recent years, we have actively analyzed different types of user metrics, such as operational distribution metrics (recording numbers of distinct users and downloaded data files, size of distributed data volume): user publication metrics (mining info from our Giovanni users’ publications): and Bugzilla metrics (collecting info from user questions or feedback from user assistance tickets). Such metrics have helped us achieve a better understanding of user needs, demands, characteristics, and behaviors, which has then helped us improve our user services. Now we will present a “Sequel” of integrated analysis of multiple metrics at the GES DISC by introducing and adding one new kind of metrics acquired via utilizing our recently implemented Google Analytic 360 suite. Several “newer” reports, e.g., “What web site features and links are the most popular (and least)?” and “What are the top 25 dataset Keyword searches?” retrieved from this new metrics set will be presented, along with the aforementioned “traditional” metrics results.

Shie, Chung-Lin↗