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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

InVEST Urban Development: Incorporating Earth Observation Data into the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation Model Python API

Urban flooding poses as one of the biggest issues for cities today, as its impacts are amplified by both climate change and urbanization. The Natural Capital Project’s Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation (UFRM) model, which benefits from its simplicity and robustness, is commonly used in NASA DEVELOP projects for disaster mitigation, urban planning, and environmental justice issues. While InVEST UFRM model was able to produce the surface water runoff and retention map sufficient for the scopes of past projects, the model accuracy and spatial variability need improvement. Since the current InVEST UFRM model employs constant rainfall depth for all pixels in the area of interest (AOI), the model suffers from inaccurately estimating rainfall depth, runoff volume, and flood depth. Therefore, we adapted the model so that satellite-based precipitation raster datasets (i.e., Integrated Multi-satellitE Retrievals for Global Precipitation Measurement [GPM IMERG]) can be used instead of a single constant value. We simulated the flood events on August 21st and August 22nd, 2017 in Wyandotte County, Kansas using both our modified and the original InVEST UFRM model and then compared the results after incorporating the rainfall raster into the model. Areas with developed land on the land use map predicted moderate to high flood volume in the original volume regardless of the actual amount of precipitation. The modified model considered the rainfall depth’s spatial variation achieving less overestimation of flood runoff and volume at low-to-moderate rainfall area.

Son Do↗
NASA NTRS2023

InVEST Urban Development: Incorporating Earth Observation Data into the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation Model Python API

Urban flooding poses as one of the biggest issues for cities today as its impacts are amplified by both climate change and urbanization. The Natural Capital Project’s Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation (UFRM) model, which benefits from its simplicity and robustness, is commonly used in NASA DEVELOP projects for disaster mitigation, urban planning, and environmental justice issues. While the InVEST UFRM model was able to produce the surface water runoff and retention map sufficient for the scopes of past projects, the model’s accuracy and spatial variability need improvement. Since the current InVEST UFRM model employs constant rainfall depth for all pixels in the area of interest (AOI), the model suffers from inaccurately estimating rainfall depth, runoff volume, and flood depth. Therefore, we adapted the model so that satellite-based precipitation raster datasets (i.e., Integrated Multi-satellitE Retrievals for Global Precipitation Measurement [GPM IMERG]) can be used instead of a single constant value. We simulated the flood events on August 21st and August 22nd, 2017, in Wyandotte County, Kansas using both our modified and the original InVEST UFRM model and then compared the results after incorporating rainfall raster into the model. Areas with developed land on the land use map predicted moderate to high flood volume in the original volume regardless of the actual amount of precipitation. The modified model considered the rainfall depth’s spatial variation achieving less overestimation of flood runoff and volume at low-to-moderate rainfall area.

Urban flooding↗
NASA NTRS2016

Big Data in the Earth Observing System Data and Information System

Approaches that are being pursued for the Earth Observing System Data and Information System (EOSDIS) data system to address the challenges of Big Data were presented to the NASA Big Data Task Force. Cloud prototypes are underway to tackle the volume challenge of Big Data. However, advances in computer hardware or cloud won't help (much) with variety. Rather, interoperability standards, conventions, and community engagement are the key to addressing variety.

data systems↗
NASA NTRS2018

Hierarchical Data Format for Earth Observing System Data Product Developer's Guide

The "Hierarchical Data Format for Earth Observing System" talk will address the best practices for creating ESDIS data products. The work presented is done in support of Data Product Developers Guide Working Group with mission "to help data product developers make data usable for end users". During the presentation, we will use some examples of NASA data products and show how to modify them to make data more usable.

Data usability↗
NASA NTRS2001

Global Gridded Data from the Goddard Earth Observing System Data Assimilation System (GEOS-DAS)

The Goddard Earth Observing System Data Assimilation System (GEOS-DAS) timeseries is a globally gridded atmospheric data set for use in climate research. This near real-time data set is produced by the Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center in direct support of the operational EOS instrument product generation from the Terra (12/1999 launch), Aqua (05/2002 launch) and Aura (01/2004 launch) spacecrafts. The data is archived in the EOS Core System (ECS) at the Goddard Earth Sciences Data and Information Services Center/Distributed Active Archive Center (GES DISC DAAC). The data is only a selection of the products available from the GEOS-DAS. The data is organized chronologically in timeseries format to facilitate the computation of statistics. GEOS-DAS data will be available for the time period January 1, 2000, through present.

Source record↗
NASA NTRS2006

Earth Observing System Data Gateway

The Earth Observing System Data Gateway (EDG) software provides a "one-stop-shopping" standard interface for exploring and ordering Earth-science data stored at geographically distributed sites. EDG enables a user to do the following: 1) Search for data according to high-level criteria (e.g., geographic location, time, or satellite that acquired the data); 2) Browse the results of a search, viewing thumbnail sketches of data that satisfy the user s criteria; and 3) Order selected data for delivery to a specified address on a chosen medium (e.g., compact disk or magnetic tape). EDG consists of (1) a component that implements a high-level client/server protocol, and (2) a collection of C-language libraries that implement the passing of protocol messages between an EDG client and one or more EDG servers. EDG servers are located at sites usually called "Distributed Active Archive Centers" (DAACs). Each DAAC may allow access to many individual data items, called "granules" (e.g., single Landsat images). Related granules are grouped into collections called "data sets." EDG enables a user to send a search query to multiple DAACs simultaneously, inspect the resulting information, select browseable granules, and then order selected data from the different sites in a seamless fashion.

Pfister, Robin↗
NASA NTRS2015

Taming Big Data Variety in the Earth Observing System Data and Information System

Although the volume of the remote sensing data managed by the Earth Observing System Data and Information System is formidable, an oft-overlooked challenge is the variety of data. The diversity in satellite instruments, science disciplines and user communities drives cost as much or more as the data volume. Several strategies are used to tame this variety: data allocation to distinct centers of expertise; a common metadata repository for discovery, data format standards and conventions; and services that further abstract the variations in data.

Information Systems↗
NASA NTRS1991

The Earth Observing System Data and Information System

The system is described in terms of the broad context of scientific cooperation and research which are facilitated by the architecture designed and the nature of the generated data. The Earth Observing System Data and Information System (EOSDIS) is composed of earth-science and applications data systems which archive global-change data and distribute the information to system users. Several archive centers catalogue selected Pathfinder data sets and generate new data products (such as maps of sea ice, cloud studies, etc.) with consistent calibration of all data. The schedule of three versions of EOSDIS is discussed with reference to the system architecture, programmatic plans, and data policy. The critical issue for EOSDIS is international cooperation to sponsor an infrastructure of global change data of this magnitude for public benefit and scientific research.

Maiden, Martha E.↗