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Biomass Harmonization and SAR Analysis with the Multi-mission Algorithm and Analysis Platform (MAAP)

The Multi‐mission Algorithm and Analysis Platform (MAAP) is a collaborative effort between NASA and the European Space Agency (ESA) to support above ground biomass (AGB) research in an open science framework. MAAP brings together relevant data, algorithms, and computing capabilities in a common cloud environment to address the challenges of sharing and processing data from field, airborne and satellite measurements. MAAP was publicly released in October 2021, providing computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of data. MAAP has allowed scientists from both North America and Europe to collaborate on the generation and analysis/visualization of data derived from multiple, discipline-adjacent missions in an open, collaborative environment that has reached beyond traditional scientific investigation. MAAP has been used to support multiple scientific activities. To date, existing LiDAR data from multiple platforms has been calibrated with field measurements and combined for more comprehensive and accurate estimates of above ground biomass AGB; these LiDAR platforms include airborne (e.g. LVIS), the International Space Station (NASA’s Global Ecosystem Dynamics Investigation (GEDI), and satellites (e.g. ICESat-2). The current challenge is to effectively and seamlessly combine the aforementioned LiDAR-based data with new data sources such as P-band RADAR from ESA’s upcoming BIOMASS mission, existing ESA Sentinel-1 C-band SAR, and the 30 PB/yr of high cadence global coverage L-band SAR data from the upcoming NASA-ISRO SAR (NISAR) mission. Recent analysis using MAAP merged ICESat-2 and optical data (Harmonized Landsat Sentinel) produced the most comprehensively precise estimate of boreal-wide AGB to date. Another effort using MAAP is the production and open distribution of global comparisons of AGB map estimates, including from ICESat-2 and GEDI, to bolster stakeholder uptake for policy applications. These map estimates will feed into the Intergovernmental Panel on Climate Change (IPCC) database, likely aiding the next Global Carbon Stocktake of the UNFCCC. Furthermore, the biomass retrieval intercomparison exercise BRIX-2 could benefit from the MAAP providing standardized test cases (based on airborne campaign and spaceborne data) allowing the community to develop and apply retrieval algorithms based on these test cases, while forthcoming SAR data training curricula could also use the MAAP as a teaching and learning platform. The MAAP is meeting the challenges inherent in international, open science collaboration and large scale computing with a platform that is entirely open source and cloud native, using open standards for data access, manipulation, protocols, and formats. The MAAP data system consists of a dedicated data store whose data is indexed in an online catalog conforming to established metadata, application programmatic interfaces (APIs), and service interface standards, using an implementation of the open sourced NASA Common Metadata Repository. Federation of user identities allows users from either NASA or ESA to access and consume services from the other using a unified metadata catalog for the data utilized across the ESA and NASA MAAP platforms. Similarly, we are exploring how to increase interoperability to achieve a common approach to packaging, orchestrating and executing algorithms, with interoperable access to data for subsetting, fast browse, and cloud-optimized access, all using interoperable standards such as those from the Open Geospatial Consortium (OGC). Designed for interoperability, ESA and NASA utilize a common architecture for the software platform. It provides a cloud-based algorithm development environment (ADE) that enables scientists to develop algorithms collaboratively with access to the MAAP data catalog as well as other data archives. MAAP provides an Eclipse Che-based ADE supporting both Python and R languages, popular in this biomass community. Algorithms developed and containerized within the ADE can be deployed to run to thousands of computational nodes in the MAAP’s data processing system (DPS), dramatically speeding up processing and giving scientists a rapid, iterative turnaround of results. NASA’s implementation of the DPS is based on the Hybrid Science Data System (HySDS) framework, used by NASA flight projects to produce Earth science standard products.

cloud computing↗
DOE OSTI2022

The waterSHED Model: User Guide

The ideal design and operation of small hydropower plants is a complex optimization problem with economic, social, and environmental objectives. The waterSHED (Water Allocation Tool Enabling Rapid Small Hydropower Environmental Design) model is a user-friendly tool that allows hydropower stakeholders to model the trade-offs among these objectives using the Standard Modular Hydropower (SMH) framework. The SMH framework employs modular technologies that can be represented as blackbox objects and combined within a river to create a hydropower facility. For a given site, the waterSHED model aims to determine which modules should be placed in a facility and how those modules should be operated. This user guide describes how to use the graphical user interface and related functionalities. This document also summarizes the background research and mathematical formulations that are explained indepth in the accompanying doctoral dissertation. This model is an early step toward a new hydropower design process that employs standardization and modularity to reduce costs, development timelines, and challenges regarding social and environmental mitigation measures for low-head, small hydropower development. The waterSHED model is a Python application that will require the ability to download a GitHub repository, import the necessary packages, and run a set of Python script files using an integrated development environment. The script produces a graphical user interface to coordinate inputs, simulate operation, and visualize results, so no coding experience is needed once the script is running. Additionally, the waterSHED Workbook is a Microsoft Excel file that works with the Python script to facilitate data entry

13 HYDRO ENERGY↗
DOE OSTI2025

sourcePy

Pollutant source identification techniques (of which there are many variations) are either locked behind researchers writing their own code for each use case or GUI platforms that are easy to use but inflexible and opaque. The Python package sourcePy brings together many of the pollutant source identification algorithms, giving the user full control out of the box. It aims to create a platform for source identification experiments where the full analysis from beginning to end can be done in Python, with a level of specificity in design that isn't available in the GUI options. sourcePy provides users with a few key features: -A Python interface with HYSPLIT, which can be used to generate trajectories and concentration plumes -Several Python classes which standardize the preparation and processing of data related to source identification experiments -Example scripts and notebooks that allow even new python users to get started with their own experiments quickly -Visualization methods

Arseneau, Isaac [Oak Ridge National Laboratory (OR↗
NASA NTRS1993

Volume serving and media management in a networked, distributed client/server environment

The E-Systems Modular Automated Storage System (EMASS) is a family of hierarchical mass storage systems providing complete storage/'file space' management. The EMASS volume server provides the flexibility to work with different clients (file servers), different platforms, and different archives with a 'mix and match' capability. The EMASS design considers all file management programs as clients of the volume server system. System storage capacities are tailored to customer needs ranging from small data centers to large central libraries serving multiple users simultaneously. All EMASS hardware is commercial off the shelf (COTS), selected to provide the performance and reliability needed in current and future mass storage solutions. All interfaces use standard commercial protocols and networks suitable to service multiple hosts. EMASS is designed to efficiently store and retrieve in excess of 10,000 terabytes of data. Current clients include CRAY's YMP Model E based Data Migration Facility (DMF), IBM's RS/6000 based Unitree, and CONVEX based EMASS File Server software. The VolSer software provides the capability to accept client or graphical user interface (GUI) commands from the operator's console and translate them to the commands needed to control any configured archive. The VolSer system offers advanced features to enhance media handling and particularly media mounting such as: automated media migration, preferred media placement, drive load leveling, registered MediaClass groupings, and drive pooling.

Herring, Ralph H.↗
NASA NTRS1984

Orbiter middeck/payload standard interfaces control document

The interfaces which shall be provided by the baseline shuttle mid-deck for payload use within the mid-deck area are defined, as well as all constraints which shall be observed by all the users of the defined interfaces. Commonality was established with respect to analytical approaches, analytical models, technical data and definitions for integrated analyses by all the interfacing parties. Any payload interfaces that are out of scope with the standard interfaces defined shall be defined in a Payload Unique Interface Control Document (ICD) for a given payload. Each Payload Unique ICD will have comparable paragraphs to this ICD and will have a corresponding notation of A, for applicable; N/A, for not applicable; N, for note added for explanation; and E, for exception. On any flight, the STS reserves the right to assign locations to both payloads mounted on an adapter plate(s) and payloads stored within standard lockers. Specific locations requests and/or requirements exceeding standard mid-deck payload requirements may result in a reduction in manifesting opportunities.

Source record↗
NASA NTRS1990

Process and information integration via hypermedia

Success stories for advanced automation prototypes abound in the literature but the deployments of practical large systems are few in number. There are several factors that militate against the maturation of such prototypes into products. Here, the integration of advanced automation software into large systems is discussed. Advanced automation systems tend to be specific applications that need to be integrated and aggregated into larger systems. Systems integration can be achieved by providing expert user-developers with verified tools to efficiently create small systems that interface to large systems through standard interfaces. The use of hypermedia as such a tool in the context of the ground control centers that support Shuttle and space station operations is explored. Hypermedia can be an integrating platform for data, conventional software, and advanced automation software, enabling data integration through the display of diverse types of information and through the creation of associative links between chunks of information. Further, hypermedia enables process integration through graphical invoking of system functions. Through analysis and examples, researchers illustrate how diverse information and processing paradigms can be integrated into a single software platform.

Hammen, David G.↗
NASA NTRS1988

IRDS prototyping with applications to the representation of EA/RA models

The requirements and system overview for the Information Resources Dictionary System (IRDS) are described. A formal design specification for a scaled down IRDS implementation compatible with the proposed FIPS IRDS standard is contained. The major design objectives for this IRDS will include a menu driven user interface, implementation of basic IRDS operations, and PC compatibility. The IRDS was implemented using Smalltalk/5 object oriented programming system and an ATT 6300 personal computer running under MS-DOS 3.1. The difficulties encountered in using Smalltalk are discussed.

Lekkos, Anthony A.↗
NASA NTRS1998

SoftLab: A Soft-Computing Software for Experimental Research with Commercialization Aspects

SoftLab is a software environment for research and development in intelligent modeling/control using soft-computing paradigms such as fuzzy logic, neural networks, genetic algorithms, and genetic programs. SoftLab addresses the inadequacies of the existing soft-computing software by supporting comprehensive multidisciplinary functionalities from management tools to engineering systems. Furthermore, the built-in features help the user process/analyze information more efficiently by a friendly yet powerful interface, and will allow the user to specify user-specific processing modules, hence adding to the standard configuration of the software environment.

Akbarzadeh-T, M.-R.↗
NASA NTRS2014

Exploring NASA OMI Level 2 Data With Visualization

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, such as model inputs from satellite, or extreme events (such as volcano eruptions, dust storms, etc.).Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. Such obstacles may be avoided by allowing users to visualize satellite data as images, with accurate pixel-level (Level-2) information, including pixel coverage area delineation and science team recommended quality screening for individual geophysical parameters. We present a prototype service from the Goddard Earth Sciences Data and Information Services Center (GES DISC) supporting Aura OMI Level-2 Data with GIS-like capabilities. Functionality includes selecting data sources (e.g., multiple parameters under the same scene, like NO2 and SO2, or the same parameter with different aggregation methods, like NO2 in OMNO2G and OMNO2D products), user-defined area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting, reformatting, and reprojection. The system will allow any user-defined portal interface (front-end) to connect to our backend server with OGC standard-compliant Web Mapping Service (WMS) and Web Coverage Service (WCS) calls. This back-end service should greatly enhance its expandability to integrate additional outside data-map sources.

Level 2↗
NASA NTRS2014

Exploring NASA OMI Level 2 Data With Visualization

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, such as model inputs from satellite, or extreme events (such as volcano eruptions, dust storms,... etc.). Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. Such obstacles may be avoided by allowing users to visualize satellite data as "images", with accurate pixel-level (Level-2) information, including pixel coverage area delineation and science team recommended quality screening for individual geophysical parameters. We present a prototype service from the Goddard Earth Sciences Data and Information Services Center (GES DISC) supporting Aura OMI Level-2 Data with GIS-like capabilities. Functionality includes selecting data sources (e.g., multiple parameters under the same scene, like NO2 and SO2, or the same parameter with different aggregation methods, like NO2 in OMNO2G and OMNO2D products), user-defined area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting, reformatting, and reprojection. The system will allow any user-defined portal interface (front-end) to connect to our backend server with OGC standard-compliant Web Mapping Service (WMS) and Web Coverage Service (WCS) calls. This back-end service should greatly enhance its expandability to integrate additional outside data/map sources.

Aura↗
NASA NTRS2013

Mission Operations Center (MOC) - Precipitation Processing System (PPS) Interface Software System (MPISS)

MPISS is an automatic file transfer system that implements a combination of standard and mission-unique transfer protocols required by the Global Precipitation Measurement Mission (GPM) Precipitation Processing System (PPS) to control the flow of data between the MOC and the PPS. The primary features of MPISS are file transfers (both with and without PPS specific protocols), logging of file transfer and system events to local files and a standard messaging bus, short term storage of data files to facilitate retransmissions, and generation of file transfer accounting reports. The system includes a graphical user interface (GUI) to control the system, allow manual operations, and to display events in real time. The PPS specific protocols are an enhanced version of those that were developed for the Tropical Rainfall Measuring Mission (TRMM). All file transfers between the MOC and the PPS use the SSH File Transfer Protocol (SFTP). For reports and data files generated within the MOC, no additional protocols are used when transferring files to the PPS. For observatory data files, an additional handshaking protocol of data notices and data receipts is used. MPISS generates and sends to the PPS data notices containing data start and stop times along with a checksum for the file for each observatory data file transmitted. MPISS retrieves the PPS generated data receipts that indicate the success or failure of the PPS to ingest the data file and/or notice. MPISS retransmits the appropriate files as indicated in the receipt when required. MPISS also automatically retrieves files from the PPS. The unique feature of this software is the use of both standard and PPS specific protocols in parallel. The advantage of this capability is that it supports users that require the PPS protocol as well as those that do not require it. The system is highly configurable to accommodate the needs of future users.

Ferrara, Jeffrey↗
DOE OSTI2021

Chapter 18: Learning and Tracking Ad Hoc Fiducial Markers in Spatial Augmented Reality

We describe a spatial augmented reality system with a tangible user interface used to control computer simulations of complex systems. In spatial augmented reality, the user’s physical space is augmented with projected imagery, blending real objects with projected information, and a tangible user interface enables users to manipulate physical objects as controllers for interactive visualizations. Our system learns ad hoc objects in the user’s environment as fiducial markers (i.e., objects that are visually recognized and tracked). When combined with simulation and visualization tools, these interfaces allow the user to control simulations or ensembles of simulations via physical objects using apt metaphors. While other research has leveraged the use of depth cameras, our system enables the use of standard cameras in readily available smartphones and webcams and has an implementation that runs completely in JavaScript in the web browser. We discuss the prerequisite object-recognition requirements for such tangible user interfaces and describe computer-vision and machine-learning algorithms meeting those requirements. We conclude by presenting example applications, which are also available online.

energy distribution↗
DOE OSTI2021

FIERRO V.X

FIERRO is a modern C++ code intended to simulate quasi-static solid mechanics problems and transient, compressible material dynamic problems with Lagrangian methods, which have meshes with constant mass elements that move with the material. FIERRO is designed to aid a) material model research that has historically been done using commercial implicit and explicit finite element codes, b) numerical methods research, and c) computer science research. FIERRO supports user developed material models that adhere to several industry standard formats by using a C++ to Fortran interface to couple the model to the numerical solvers. FIERRO is built on the ELEMENTS library that supports a diverse suite of element types, including high-order elements, and quadrature rules. The mesh class within the ELEMENTS library is designed for efficient calculations on unstructured meshes and to minimize memory usage. FIERRO is designed to readily accommodate a range of numerical methods including continuous finite element, finite volume, and discontinuous Galerkin methods. FIERRO is designed to support explicit and implicit time integration methods. FIERRO only supports a single material in an element. No physical data exists within the code.

Morgan, Nathaniel↗
NASA NTRS1988

Archival-System Computer Program

Files stored with various degrees of relative performance. ARCHIVE system provides permanent storage area for files to which infrequent access is required. Routines designed to provide simple mechanism by which users store and retrieve files. User treats ARCHIVE as interface to "black box" where files are stored. There are five ARCHIVE user commands, though ARCHIVE employs standard VMS directives and VAX BACKUP utility program. Special care taken to provide security needed to insure integrity of files over period of years. ARCHIVE written in DEC VAX DCL.

Scott, Peter↗
NASA NTRS1990

General purpose intelligent sensor interface

The long range goal is to develop an intelligent sensor system that will simplify the design and development of expert systems that use sensors of physical phenomena as a source of input data. This phase of the research concentrated on the integration of image processing sensors with expert system environments. The anticipated result of this research is the ability to design systems in which the user will not need to be an expert in such areas as image processing algorithms, local area networks, image processor hardware selection or interfacing, or television cameras selection. The user will be able to access data from video sensors through standard expert system statements without any need to know about the sensor hardware or software.

Mckee, J. W.↗
NASA NTRS1992

Remote observatory access via the Advanced Communications Technology Satellite

An investigation of the potential for using the ACTS to provide the data distribution network for a distributed set of users of an astronomical observatory has been conducted. The investigation consisted of gathering the data and interface standards for the ACTS network and the observatory instrumentation and telecommunications devices. A simulation based on COMNET was then developed to test data transport configurations for real-time suitability. The investigation showed that the ACTS network should support the real-time requirements and allow for growth in the observatory needs for data transport.

Horan, Stephen↗
NASA NTRS2004

Tower Mesonetwork Climatology and Interactive Display Tool

Forecasters at the 45th Weather Squadron and Spaceflight Meteorology Group use data from the tower network over the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) to evaluate Launch Commit Criteria, and issue and verify forecasts for ground operations. Systematic biases in these parameters could adversely affect an analysis, forecast, or verification. Also, substantial geographical variations in temperature and wind speed can occur under specific wind directions. To address these concerns, the Applied Meteorology Unit (AMU) developed a climatology of temperatures and winds from the tower network, and identified the geographical variation and significant tower biases. The mesoclimate is largely driven by the complex land-water interfaces across KSC/CCAFS. Towers with close proximity to water typically had much warmer nocturnal temperatures and higher wind speeds throughout the year. The strongest nocturnal wind speeds occurred from October to March whereas the strongest mean daytime wind speeds occurred from February to May. These results of this project can be viewed by forecasters through an interactive graphical user interface developed by the AMU. The web-based interface includes graphical and map displays of mean, standard deviation, bias, and data availability for any combination of towers, variables, months, hours, and wind directions.

Case, Jonathan L.↗