Estimating Forest Vegetation Variables by Combining INSAR and POLSAR Data and Minimizing the Need for Ancillary Data
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INSAR parameter estimation vegetation characterist↗
SEARCH · Engineering Papers
Results for “data fusion”
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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Data visualization for effective rover sequencing
The Rover Sequencing and Visualization Program is a suite of toos for the commanding of planetary rovers which are subject to significant light time delay and thus are unsuitable for tele-operation.
surface operations↗
Using MISR and MODIS data for detection and analysis of smoke plume injection heights over North American during Summer 2004
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MODIS↗
Update on Integrated Optical Design Analyzer
Updated information on the Integrated Optical Design Analyzer (IODA) computer program has become available. IODA was described in Software for Multidisciplinary Concurrent Optical Design (MFS-31452), NASA Tech Briefs, Vol. 25, No. 10 (October 2001), page 8a. To recapitulate: IODA facilitates multidisciplinary concurrent engineering of highly precise optical instruments. The architecture of IODA was developed by reviewing design processes and software in an effort to automate design procedures. IODA significantly reduces design iteration cycle time and eliminates many potential sources of error. IODA integrates the modeling efforts of a team of experts in different disciplines (e.g., optics, structural analysis, and heat transfer) working at different locations and provides seamless fusion of data among thermal, structural, and optical models used to design an instrument. IODA is compatible with data files generated by the NASTRAN structural-analysis program and the Code V (Registered Trademark) optical-analysis program, and can be used to couple analyses performed by these two programs. IODA supports multiple-load-case analysis for quickly accomplishing trade studies. IODA can also model the transient response of an instrument under the influence of dynamic loads and disturbances.
Moore, James D., Jr.↗
Fusion of Satellite and Model Data to Study Hurricanes and Improve Forecasts: The JPL Tropical Cyclone Information System and Near Real Time Portal
No abstract available
satellite observations of hurricanes↗
Addressing the Big-Earth-Data Variety Challenge with the Hierarchical Triangular Mesh
We have implemented an updated Hierarchical Triangular Mesh (HTM) as the basis for a unified data model and an indexing scheme for geoscience data to address the variety challenge of Big Earth Data. We observe that, in the absence of variety, the volume challenge of Big Data is relatively easily addressable with parallel processing. The more important challenge in achieving optimal value with a Big Data solution for Earth Science (ES) data analysis, however, is being able to achieve good scalability with variety. With HTM unifying at least the three popular data models, i.e. Grid, Swath, and Point, used by current ES data products, data preparation time for integrative analysis of diverse datasets can be drastically reduced and better variety scaling can be achieved. In addition, since HTM is also an indexing scheme, when it is used to index all ES datasets, data placement alignment (or co-location) on the shared nothing architecture, which most Big Data systems are based on, is guaranteed and better performance is ensured. Moreover, our updated HTM encoding turns most geospatial set operations into integer interval operations, gaining further performance advantages.
SciDB↗
VISAGE Visualization for Integrated Satellite, Airborne and Ground-Based Data Exploration
The primary goal of the VISAGE project is to facilitate more efficient Earth Science investigations via a tool that can provide visualization and analytic capabilities for diverse coincident datasets. This proof-of-concept project will be centered around the GPM Ground Validation program, which provides a valuable source of intensive, coincident observations of atmospheric phenomena. The data are from a wide variety of ground-based, airborne and satellite instruments, with a wide diversity in spatial and temporal scales, variables, and formats, which makes these data difficult to use together. VISAGE will focus on "golden cases" where most ground instruments were in operation and multiple research aircraft sampled a significant weather event, ideally while the GPM Core Observatory passed overhead. The resulting tools will support physical process studies as well as satellite and model validation.
Data fusion↗
A Survey of Methods for Computing Best Estimates of Endoatmospheric and Exoatmospheric Trajectories
Beginning with the mathematical prediction of planetary orbits in the early seventeenth century up through the most recent developments in sensor fusion methods, many techniques have emerged that can be employed on the problem of endo and exoatmospheric trajectory estimation. Although early methods were ad hoc, the twentieth century saw the emergence of many systematic approaches to estimation theory that produced a wealth of useful techniques. The broad genesis of estimation theory has resulted in an equally broad array of mathematical principles, methods and vocabulary. Among the fundamental ideas and methods that are briefly touched on are batch and sequential processing, smoothing, estimation, and prediction, sensor fusion, sensor fusion architectures, data association, Bayesian and non Bayesian filtering, the family of Kalman filters, models of the dynamics of the phases of a rocket's flight, and asynchronous, delayed, and asequent data. Along the way, a few trajectory estimation issues are addressed and much of the vocabulary is defined.
Bernard, William P.↗
In-time System-wide Safety Assurance (ISSA) Concept of Operations and Design Considerations for Urban Air Mobility (UAM)
Emerging operations involving Advanced Air Mobility (AAM), such as Urban Air Mobility (UAM), pose a challenge to safety assurance and to accessibility within the National Airspace System (NAS).In particular, the public has a low tolerance for risk in aviation and the current NAS tends to be labor-intensive with limited ability to scale up for UAM. In response to this landscape, NASA is collaborating with industry to define a Concept of Operations (ConOps) for In-time System-Wide Safety Assurance (ISSA) for scalable UAM involving a service-oriented architecture. This architecture focuses safety investments for technological solutions that can overcome safety related barriers for emerging operations. By working with industry, consensus can be reached on desirable system traits that are based on integration and fusion of data and leverage increasingly autonomous and automated systems. These complex systems can identify anomalies, precursors, and trends that together enable more proactive management of operational risks. AAM and UAM elevate the need for risk management in relation to increasing density and heterogeneity of vehicles and operations. Whereas safety in today’s NAS is built on a history of programs and technologies that react to incidents and accidents, AAM presents an opportunity to leverage that experience and its implications and proactively integrate safety into the earliest designs of vehicles and systems. In a perfect world AAM and UAM would not be inherently dangerous but until then ensuring the highest quality of safety requirements is the bridge to mitigating risks.
In-Time System-Wide Safety Assurance↗
Regional Tropical Aboveground Biomass Mapping with L-Band Repeat-Pass Interferometric Radar, Sparse Lidar, and Multiscale Superpixels
We introduce a multiscale superpixel approach that leverages repeat-pass interferometric coherence and sparse AGB estimates from a simulated spaceborne lidar in order to extend the NISAR mission’s applicable range of aboveground biomass (AGB) in tropical forests. Airborne and spaceborne L-band radar and full-waveform airborne lidar data are used to simulate the NISAR and GEDI mission, respectively. In addition to UAVSAR data, we use spaceborneALOS-2/PALSAR-2 imagery with 14-day temporal baseline, which is comparable to NISAR’s 12-daybaseline. Our reference AGB maps are derived from the airborne LVIS data during the AfriSAR campaign for three sites (Mondah, Ogooue, and Lope). Each tropical site has mean AGB of at least 125 Mg/ha in addition to areas with AGB exceeding 700 Mg/ha. Spatially sampling from these LVIS-derived AGB reference maps, we approximate GEDI AGB estimates. To evaluate our methodology, we perform several different analyses. First, we partition each study site into low(≤100 Mg/ha) and high (>100 Mg/ha) AGB areas, in conformity with the NISAR mission requirement to provide AGB estimates for forests between 0 and 100 Mg/ha with a RMSE below 20 Mg/ha. In the low AGB areas, this RMSE requirement is satisfied in Lope and Mondah and it fell short of the requirement in Ogooue by less 3 Mg/ha with UAVSAR and 6 Mg/ha with PALSAR-2. We note that our maps have finer spatial resolution (50 m) than NISAR requires (1 hectare). In the high AGB areas, the normalized RMSE increases to 51% (i.e.,<90 Mg/ha), but with negligible bias for all three sites. Second, we train a single model to estimate AGB across both high and low AGB regimes simultaneously and obtain a normalized RMSE that is<60% (or<100 Mg/ha). Lastly, we show the use of both (a) multiscale superpixels and (b) interferometric coherence significantly improves the accuracy of the AGB estimates. The InSAR coherence improved the RMSE by approximately 8% at Mondah with both sensors, lowering the RMSE from 59 Mg/ha to 47.4 Mg/h with UAVSAR and from 57.1 Mg/ha to 46 Mg/ha. This work illustrates one of the numerous synergistic relationships between the spaceborne lidars, such as GEDI, with L-band SAR, such as PALSAR-2 and NISAR, in order to produce robust regional AGB in high biomass tropical regions.
NISAR↗
Geophysical Observations Toolkit For Evaluating Coral Health (GOTECH) Fall 2021 Final Report
The NASA Langley Research Center (LaRC) Data Science Team (DST), under the Office of the Chief Information Officer (OCIO), is investigating the capacity of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite to infer the vitality of coral reefs. This report describes the Fall 2021 period of performance for the Geophysical Observations Toolkit for Evaluating Coral Health (GOTECH) project. During this effort, two student teams at Georgia Tech developed machine-learning models to predict the vitality of coral reefs in targeted geographic regions based on backscatter data from the CALIPSO satellite. To train these models, students fused data to form a common operating picture of how coral reefs have grown and decayed worldwide. This report describes the student assignment, background, and results of the semester's research.
Machine Learning↗
NASA’s Goddard Space Flight Center’s Distributed Systems Missions Architecture
Space and Earth Science are being transformed by applying a distributed approach to missions, where the fusion of data from components, systems, instruments, models, and observation locations works in concert with timely responses and feedback mechanisms to multiply the knowledge obtained. Additionally, a disaggregated approach allows for a distributed cost and schedule that can be shared across multiple organizations to enable the greater mission. With the advances in reduced size, weight, and power for space-worthy components leading to the revolution in smaller spacecraft, the cost and timeliness proposition for launching multiple space assets has also greatly improved. Thus, the aerospace industry is undergoing a paradigm shift toward a proliferation of small satellites as a networked approach to meet mission objectives. This paper will describe the impetus, goal, and path to provide an openly available framework as a unifying catalyst for broad-ranging Distributed Systems Missions (DSMs) contributors.
Distributed Systems↗
NASA’s Goddard Space Flight Center’s Distributed Systems Missions Architecture
Space and Earth Science are being transformed by applying a distributed approach to missions, where the fusion of data from components, systems, instruments, models, and observation locations works in concert with timely responses and feedback mechanisms to multiply the knowledge obtained. Additionally, a disaggregated approach allows for a distributed cost and schedule that can be shared across multiple organizations to enable the greater mission. With the advances in reduced size, weight, and power for space-worthy components leading to the revolution in smaller spacecraft, the cost and timeliness proposition for launching multiple space assets has also greatly improved. Thus, the aerospace industry is undergoing a paradigm shift toward a proliferation of small satellites as a networked approach to meet mission objectives. This paper will describe the impetus, goal, and path to provide an openly available framework as a unifying catalyst for broad-ranging Distributed Systems Missions (DSMs) contributors.
Distributed Systems↗
Assessing Carbon Properties in Coastal Waters with a New Observing System Testbed
Large rainfall events over land can lead to a substantial flux of carbon and nutrients to estuaries and the coastal ocean. In the mid-Atlantic on the east coast of North America (35° - 42° N), these events often happen due to tropical storm activity as well as less predictable anomalously large midlatitude storms or abrupt spring snow melt runoff. Storms can directly impact the coastal carbon cycle via export of carbon from land to sea, while also stimulating phytoplankton production due to the influx of nutrients to the coastal ocean. To assess the impact of high precipitation and river flow events on the coastal carbon cycle, we have integrated multiple observing platforms in an analytical framework to dynamically observe carbon-related properties. The new observing system testbed (NOS-T) allows for an estimate of phytoplankton and organic carbon stocks in the surface ocean, with a goal of providing near real time analytical capability. A case study of high river discharge in the mid-Atlantic in the summer and fall of 2018 and 2021 were used to examine how riverine carbon manifests along the land-estuary-ocean continuum particularly in Chesapeake Bay. Chesapeake Bay was chosen as the study site because of long term monitoring by the Chesapeake Bay Program and a robust and well-developed regional biogeochemical modeling system, the Chesapeake Bay Environmental Forecast System (CBEFS), that is publicly available. There is also new capability in Chesapeake Bay to combine hyperspectral radiometric data from the Aerosol Robotic Network site that is online in 2022 with in-water observations of optical properties. Precipitation data from the Global Precipitation Measurement IMERG data set was used to establish triggering criteria for storm carbon flux observation. USGS and in-water carbon data were used to establish statistical models to estimate the mass flux of organic carbon into Chesapeake Bay using measured river discharge. The year 2018 was examined as there was record rainfall and near record river flow in the late summer. The CBEFS modeling was compared with in-water estimates of dissolved organic carbon (DOC) to assess the model’s ability to capture storm fluxes of carbon to the ecosystem. Multiple satellite platforms were also used to assess how remote sensing using passive Earth orbiting sensors can be used to observe carbon in this complex coastal region. A set of recommendations have been established to improve sensing capability to measure aquatic carbon during storm events. A unique challenge in these dynamic inland waters is how rapidly carbon fluxes can evolve in space and time, with many sources contributing to the water leaving reflectance that satellites can observe. To improve our ability to quantify carbon stocks and fluxes in near real time, a suite of satellite sensors and high-resolution modeling capability is needed, all supplemented by in situ monitoring. Future inclusion of in-water observations that would be deployed when the system reaches triggering criteria, as well as taskable orbital instruments, will improve estimates of ocean carbon properties and provide the ability to calculate major carbon stocks and fluxes in near real time following episodic storm events.
land-ocean continuum↗
Multihierarchy Gaussian Process Models for Probabilistic Aerodynamic Databases using Uncertain Nominal and Off-Nominal Configuration Data
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Gaussian Processes↗
Full Lunar Surface Visualization and Simulation Platform
This project created a visualization and simulation software platform for the entire lunar surface. Given the polar Artemis landing targets, the challenging terrain, lighting, and associated integrated crew / vehicle risk assessment, a more integrated approach to mission safety certification, potentially impacting equipment design and crew activity is required. This integrated capability will enable Safety and Mission Assurance (SMA), Flight Operations (FOD), and EVA to effectively collaborate to reduce human lunar exploration operational risk utilizing the identical tools to perform mission planning, rehearsal simulations, and providing the Safety Review Panel with integrated risk analysis capability.
information fusion↗
Enhancing Long-Term Trend Simulation of OH Through the Synergy of Model Simulations and Aura Ozone Monitoring Instrument (OMI) NO 2 and HCHO Retrievals
During the last few years, tremendous progress has been made to develop an efficient parameterization module using agile machine learning techniques. The aim of this module is to provide dynamic response of the tropospheric hydroxyl radical (OH) to its major drivers, including trace gases, aerosols, clouds, and meteorology. This module, named ECCOH (pronounced “echo”) and implemented in NASA’s GEOS-5 global model, offers an unrealized opportunity to unravel the convoluted response of OH to its underlying drivers while approaching the accuracy of full-chemistry without incurring excessive computational costs, making it suitable for climate models. However, the accurate representation of OH in ECCOH poses challenges due to the lack of representation of some of its critical inputs such as the abundance of NO 2 and HCHO concentrations. As such, we leverage the well-characterized satellite observations of NO2 and HCHO columns from Aura OMI to enhance their representation in ECCOH using an optimal interpolation method for the time period of 2005 - present. We show how the inclusion of OMI information can affect the spatiotemporal variability and long-term trends of OH, CO, and CH 4 across the globe. Additionally, we underscore the necessity of obtaining high-fidelity information regarding tropospheric ozone from the southern hemisphere from space, a region currently lacking full verification in models, posing a challenge to get a reasonable amount of chemical sink for CH 4 .
OH↗
The West-Coast Hyperspectral Microwave Sensor Intensive Experiment (WHyMSIE): A Prototype for A PBL Mission of Missions
We present an overview of the 2024 West-Coast Hyperspectral Microwave Sensor Intensive Experiment(WHyMSIE). WHyMSIE is a joint NASA-NOAA multi-sensor airborne experiment, embracing passive and active sensors from the Program of Record (PoR) along with novel technology funded through the NASA ESTO Instrument Incubation Program. At the core of this effort is the demonstration of the Conical Scanning Millimeter-wave Imaging Radiometer Hyperspectral (CoSMIR-H) instrument, a PBL DSI funded effort to develop hyperspectral sounding capability in the thermal microwave domain finalized to improved temperature and water vapor soundings in the Earth’s Planetary Boundary Layer (PBL). An overview of the field campaign design, instrument payload and validation plan is presented here.
Planetary Boundary Layer↗