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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Forest Classification and Inventory System using Landsat, digital terrain, and ground sample data

Accurate timber inventory data for cost-effective forest management is the primary goal of a Forest Classification and Inventory System (FOCIS) designed to provide estimates of timber volume by species aggregated by compartments, townships, or other spatial management units. FOCIS uses Landsat spectral data, including a synthesized texture channel, and Forest Service ground sample data to produce timber volume-homogeneous classes through a two-step unsupervised clustering process. Registered digital terrain data, including derived slope angle and slope aspect channels, are used to predict species proportions through a trend surface model, again using ground sample data for model calibration. In the final stage of FOCIS, volume estimates and predicted species proportions are merged and aggregated to yield timber volumes by species within management areas.

Strahler, A. H.↗
NASA NTRS2018

Spatially-Explicit Monitoring of Crop Photosynthetic Capacity Through the Use of Space-Based Chlorophyll Fluorescence Data

Plant functional traits such as photosynthetic capacity are critical parameters for terrestrial biosphere models. However, their spatial and temporal characteristics are still poorly represented. In this study, we used satellite observations of sun-induced fluorescence (SIF) to estimate top-of-canopy photosynthetic capacity (maximum carboxylation rate, V(sub cmax) at a reference temperature of 25 deg C) for crops, which was in turn utilized to simulate regional gross primary production (GPP). We first estimate the key parameter, V(sub cmax), in the widely-used FvCB photosynthesis model using field measurements of CO2 and water fluxes during 2007-2012 at seven crop eddy covariance flux sites over the US Corn Belt. The results showed that satellite far-red SIF retrievals have a stronger link to V(sub cmax) at the seasonal scale (R(squared)=0.70 for C4 and R(squared)=0.63 for C3 crop) as compared with widely-used vegetation indices. We calibrate an empirical model linking V(sub cmax) with SIF that was used to estimate spatially and temporally varying crop V(sub cmax) for the US Corn Belt region. The resulting V(sub cmax) maps are used together with meteorological data from MERRA reanalysis data and vegetation structural parameters derived from the satellite- based spectral reflectance data to constrain the Soil-Canopy Observation of Photosynthesis and Energy (SCOPE) balance model in order to estimate regional crop GPP. Our results show a substantial improvement in the seasonal and spatial patterns of cropland GPP when compared with crop yield inventory data. The evaluation with tall tower atmospheric CO2 measurements further supports our estimation of spatiotemporal V(sub cmax) from space-borne SIF. Considering that SIF has a direct link to photosynthetic activity, our findings highlight the potential to infer regional V(sub cmax) using remotely sensed SIF data and to use this information for a better quantification of regional cropland carbon cycles.

Drought↗
NASA NTRSDate not supplied

Using remotely sensed information to support landslide hazard and exposure assessment throughout the disaster lifecycle

The global coverage and temporal frequency that satellites provide offers a unique opportunity to estimate landslide hazard and exposure throughout the disaster lifecycle, from pre-event planning and forecasting to post-event mapping and impact assessment, and finally to recovery and mitigation. The relevance of satellite-derived data and model products is largely contingent on the spatiotemporal sampling, the hazard characteristics, and the needs from the research or applications community. This work presents an advanced Landslide Hazard Assessment for Situational Awareness (LHASA) framework that brings together satellite and model products with new machine learning techniques and global inventory data to better model landslide hazard and exposure. We present several new ways to map, model, and assess landslide hazard using a range of satellite data. Two new thrusts of this work are to better account for the exacerbating impacts of fires and to provide a multi-day forecast of potential hazard. Together, these additional components blend information from a suite of satellite and model sources to improve early warning of potentially hazardous areas, identify landslide occurrence and impacts in near real-time, and better characterize the spatiotemporal patterns of landslide hazard and exposure more broadly for future awareness and planning. This suite of tools and products is open to the public and provides information to better assess the potential occurrence and impacts of landslides within different regions of the world. This presentation explores both the architecture behind this framework and examples of how the model components and products have been used by different stakeholders around the world.

Thomas Stanley↗
NASA NTRS2020

Satellite Monitoring of Global Surface Soil Organic Carbon Dynamics Using the SMAP Level 4 Carbon Product

Soil organic carbon (SOC) is an important metric of soil health and the terrestrial carbon balance. Short‐term climate variations affect SOC through changes in temperature and moisture, which control vegetation growth and soil decomposition. We evaluated a satellite data‐driven carbon model, operating under the NASA Soil Moisture Active‐Passive (SMAP) mission, as a means of monitoring global surface SOC dynamics. The SMAP Level 4 Carbon (L4C) product estimates a daily global carbon budget including surface (0‐ to 5‐cm depth) SOC. We found that the L4C mean latitudinal SOC distribution is generally consistent with alternative assessments from static soil inventory records and dynamic global vegetation models (r ≥ 0.89). Within forest systems, based on inventory data, L4C SOC is most similar in magnitude to litterfall but is correlated with coarse woody debris ( urn:x-wiley:jgrg:media:jgrg21790:jgrg21790-math-0001) and total SOC ( urn:x-wiley:jgrg:media:jgrg21790:jgrg21790-math-0002). L4C SOC is sensitive to seasonal and annual climate variability, with mean residence times that range from 1.5 years in the wet tropics to 17 years in the cold tundra. Incorporating soil moisture retrievals from the SMAP L‐band (1.4 GHz) microwave radiometer within the L4C algorithm provides enhanced soil moisture sensitivity under low‐to‐moderate vegetation cover (<5 kg/sq.m vegetation water content). The L‐band soil moisture had the greatest impact on the L4C carbon budget in semiarid regions, which span almost 60% of the globe and account for substantial variability in the terrestrial carbon sink. The L4C operational product enables prognostic investigations into effects of recent climate trends and anomalies (e.g., droughts and pluvials) on shallow soil carbon dynamics.

K. Arthur Endsley↗
NASA NTRS2010

Advances in Landslide Hazard Forecasting: Evaluation of Global and Regional Modeling Approach

A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that exhibit a high potential for landslide activity by combining a calculation of landslide susceptibility with satellite-derived rainfall estimates. A recent evaluation of this algorithm framework found that while this tool represents an important first step in larger-scale landslide forecasting efforts, it requires several modifications before it can be fully realized as an operational tool. The evaluation finds that the landslide forecasting may be more feasible at a regional scale. This study draws upon a prior work's recommendations to develop a new approach for considering landslide susceptibility and forecasting at the regional scale. This case study uses a database of landslides triggered by Hurricane Mitch in 1998 over four countries in Central America: Guatemala, Honduras, EI Salvador and Nicaragua. A regional susceptibility map is calculated from satellite and surface datasets using a statistical methodology. The susceptibility map is tested with a regional rainfall intensity-duration triggering relationship and results are compared to global algorithm framework for the Hurricane Mitch event. The statistical results suggest that this regional investigation provides one plausible way to approach some of the data and resolution issues identified in the global assessment, providing more realistic landslide forecasts for this case study. Evaluation of landslide hazards for this extreme event helps to identify several potential improvements of the algorithm framework, but also highlights several remaining challenges for the algorithm assessment, transferability and performance accuracy. Evaluation challenges include representation errors from comparing susceptibility maps of different spatial resolutions, biases in event-based landslide inventory data, and limited nonlandslide event data for more comprehensive evaluation. Additional factors that may improve algorithm performance accuracy include incorporating additional triggering factors such as tectonic activity, anthropogenic impacts and soil moisture into the algorithm calculation. Despite these limitations, the methodology presented in this regional evaluation is both straightforward to calculate and easy to interpret, making results transferable between regions and allowing findings to be placed within an inter-comparison framework. The regional algorithm scenario represents an important step in advancing regional and global-scale landslide hazard assessment and forecasting.

Kirschbaum, Dalia B.↗
NASA NTRS1987

Advanced Data Collection for Inventory Management

Bar-coding, radio-frequency, and voice-operated systems selected. Report discusses study of state-of-the-art in automated collection of data for management of large inventories. Study included comprehensive search of literature on data collection and inventory management, visits to existing automated inventory systems, and tours of selected supply and transportation facilities at Kennedy Space Center. Information collected analyzed in view of needs of conceptual inventory-management systems for Kennedy Space Center and for manned space station and other future space projects.

Opresko, G. A.↗
NASA NTRS1974

Predict ephemeral and perennial range quantity and quality during normal grazing season

The author has identified the following significant results. Collection and update of resource inventory data has historically been a difficult, time consuming task. Accurate resource data is necessary as a basis for wise management decisions made by a resource management agency such as the Bureau of Land Management. Black and white and color infrared composites of ERTS satellite imagery at 1:1,000,000 and enlarged scales can be used as data gathering tools. No investment in expensive sophisticated equipment is necessary. A photointerpreter can map boundaries of soils, plant communities, levels of forage production, areas revegetated by man, and areas burned by wildlife directly from satellite imagery. The ERTS system of producing and distributing imagery must be improved greatly before satellite imagery can be useful to the resource manager.

Bentley, R. G., Jr.↗
NASA NTRS1975

Remote-sensing applications in the State of Mississippi

A computer derived land use classification scheme for infrared LANDSAT imagery was developed and applied to update existing Mississippi coastline data. Inventory classifications were accomplished by photographic enlargement and photointerpretations showing color coded resources on the ground.

Bankston, P. T.↗
NASA NTRS1976

Planning applications of remote sensing in Arizona

Planners in Arizona have been experiencing the inevitable problems which occur when large areas of rural and remote lands are converted to urban-recreational uses over a relatively short period of time. Among the planning problems in the state are unplanned and illegal subdivisions, surburban sprawl, surface hydrologic problems related to ephemeral stream overflow, rapidly changing land use patterns, large size of administrative units, and lack of land use inventory data upon which to base planning decisions.

Clark, R. B.↗
NASA NTRS1987

Space station integrated propulsion and fluid system study: Fluid systems configuration databook

This databook contains fluid system requirements and system descriptions for Space Station program elements including the United States and International modules, integrated fluid systems, attached payloads, fluid servicers and vehicle accommodation facilities. Separate sections are devoted to each of the program elements and include a discussion of the overall system requirements, specific fluid systems requirements and systems descriptions. The systems descriptions contain configurations, fluid inventory data and component lists. In addition, a list of information sources is referenced at the end of each section.

Rose, L.↗
NASA NTRS1992

Production of SSM/I data sets

This Final Report is a summary of the work that was performed under Contract NAS8-38075 between NASA Marshall Space Flight Center and Remote Sensing Systems from September 1989 to September 1992. The primary accomplishment was the delivery of Special Sensor Microwave/Imager (SSM/I) data tapes containing sensor and geophysical products. In all, 515 tapes (80 gigabytes) were delivered. These tapes contained the F08 SSM/I data for the period from July 1988 through December 1991 and the F10 SSM/I data for the period from December 1990 through December 1991. For the F08 SSM/I, a data inventory was compiled and an engineering assessment was done. Ephemeris tables for the F08 and F10 spacecrafts were computed. Scientific studies on the oceanic wind vector and water vapor field were published, and color atlases of monthly ocean products were produced. This investigation was part of NASA's WETNET program.

Wentz, Frank J.↗
NASA NTRS2011

Monitoring Spacecraft Telemetry Via Optical or RF Link

A patent disclosure document discusses a photonic method for connecting a spacecraft with a launch vehicle upper-stage telemetry system as a means for monitoring a spacecraft fs health and status during and right after separation and deployment. This method also provides an efficient opto-coupled capability for prelaunch built-in-test (BIT) on the ground to enable more efficient and timely integration, preflight checkout, and a means to obviate any local EMI (electromagnetic interference) during integration and test. Additional utility can be envisioned for BIT on other platforms, such as the International Space Station (ISS). The photonic telemetry system implements an optical free-space link with a divergent laser transmitter beam spoiled over a significant cone angle to accommodate changes in spacecraft position without having to angle track it during deployment. Since the spacecraft may lose attitude control and tumble during deployment, the transmitted laser beam interrogates any one of several low-profile meso-scale retro-reflective spatial light modulators (SLMs) deployed over the surface of the spacecraft. The return signal beam, modulated by the SLMs, contains health, status, and attitude information received back at the launch vehicle. Very compact low-power opto-coupler technology already exists for the received signal (requiring relatively low bandwidths, e.g., .200 kbps) to enable transfer to a forward pass RF relay from the launch vehicle to TDRSS (Tracking and Data Relay Satellite System) or another recipient. The link would be active during separation and post-separation to monitor spacecraft health, status, attitude, or other data inventories until attitude recovery and ground control can be re-established. An optical link would not interfere with the existing upper stage telemetry and beacon systems, thus meeting launch vehicle EMI environmental constraints.

Fielhauer, K. B.↗
NASA NTRS2014

Birch Stands Growth Increase in Western Siberia

Birch (Betula pendula Roth) growth within the Western Siberia forest-steppe was analyzed based on long-term (1897-2006) inventory data (height, diameter at breast height [dbh], and stand volume). Analysis of biometry parameters showed increased growth at the beginning of twenty-first century compared to similar stands (stands age = 40-60 years) at the end of nineteenth century. Mean height, dbh, and stem volume increased from 14 to 20 m, from 16 to 22 cm, and from approx. 63 to approx. 220 cu m/ha, respectively. Significant correlations were found between the stands mean height, dbh, and volume on the one hand, and vegetation period length (r(sub s) = 0.71 to 0.74), atmospheric CO2 concentration (r(sub s) = 0.71 to 0.76), and drought index (Standardized Precipitation-Evapotranspiration Index, r(sub s) = −0.33 to −0.51) on the other hand. The results obtained have revealed apparent climate-induced impacts (e.g. increase of vegetation period length and birch habitat drying due to drought increase) on the stands growth. Along with this, a high correlation of birch biometric parameters and [CO2] in ambient air indicated an effect of CO2 fertilization. Meanwhile, further drought increase may switch birch stand growth into decline and greater mortality as has already been observed within the Trans-Baikal forest-steppe ecotone.

climate-induced tree growth↗
NASA NTRS2017

Kepler: A Search for Terrestrial Planets. K2 Handbook

The Kepler spacecraft was repurposed for the K2 mission a year after the failure of the second of Kepler's four reaction wheels in 2013 May. The purpose of this document, the K2 Handbook (K2H), is to describe features of K2 operations, performance, data analysis, and archive products which are common to most K2 campaigns, but different in degree or kind from the corresponding features of the Kepler mission.The K2 Handbook is meant to be read with the following companion documents, which are all publicly available:1. Kepler Instrument Handbook (KSCI-19033) provides information about the design, performance and operational constraints of the instrument and an overview of the types of pixel data that are available.2. Kepler Data Processing Handbook (KSCI-19081) describes how pixels downloaded from the spacecraft are converted by the Kepler Data Processing Pipeline into the data products available at the MAST archive3. Kepler Archive Manual (KDMC-100008) describes the format and content of the data products and how to search for them.4. Kepler Data Characteristics Handbook (KSCI-19040) describes recurring non-astrophysical features of the Kepler data due to instrument signatures, spacecraft events or solar activity and explains how these characteristics are handled by the Kepler pipeline.5. The Ecliptic Plane Input Catalog describes the provenance of the positions and Kepler magnitudes used for target management and aperature photometry.6. K2 Data Release Notes (DRN) are on-line documents available on the K2 science website which describe the data inventory, instrumental signatures and events peculiar to individual observing campaigns.

K2↗
NASA NTRS2018

Top-Down NOx Emissions of European Cities Based on the Downwind Plume of Modelled and Space-Borne Tropospheric NO2 Columns

Top-down estimates of surface NOX emissions were derived for 23 European cities based on the downwind plume decay of tropospheric nitrogen dioxide (NO2) columns from the LOTOS-EUROS (Long Term Ozone Simulation-European Ozone Simulation) chemistry transport model (CTM) and from Ozone Monitoring Instrument (OMI) satellite retrievals, averaged for the summertime period (April-September) during 2013. Here we show that the top-down NOX emissions derived from LOTOS-EUROS for European urban areas agree well with the bottom-up NOX emissions from the MACC-III inventory data (R(exp 2) = 0.88) driving the CTM demonstrating the potential of this method. OMI top-down NOX emissions over the 23 European cities are generally lower compared with the MACC-III emissions and their correlation is slightly lower (R(exp 2) = 0.79). The uncertainty on the derived NO2 lifetimes and NOX emissions are on average ~55% for OMI and ~63% for LOTOS-EUROS data. The downwind NO2 plume method applied on both LOTOS-EUROS and OMI tropospheric NO2 columns allows to estimate NOX emissions from urban areas, demonstrating that this is a useful method for real-time updates of urban NOX emissions with reasonable accuracy.

NOx emissions↗
NASA NTRS2018

Improving NASA GEOS Atmospheric CO2 Simulations by Calibrating CASA Surface Fluxes with an Empirical Sink

With the adoption of the Paris climate accord, efforts to monitor and understand both anthropogenic and natural carbon sources and sinks are increasing across the world. Given their low latency and global coverage, satellite observations of atmospheric carbon dioxide (CO2) are poised to make important contributions to this field. The combination of satellite data and high resolution global models can be used to monitor changes in carbon fluxes and to evaluate the consistency of nationally reported emissions estimates in support of multiple stakeholder communities. However, a consistent challenge to such work has been the high latency of surface carbon flux estimates, which are often not available for a year or more. This presentation describes the construction of surface carbon flux estimates meant to improve the near real time simulation of atmospheric CO2 with NASA's Goddard Earth Observing System (GEOS) general circulation model. The surface flux estimates begin with a collection of bottom-up fluxes which incorporate satellite measurements in their construction, e.g. vegetation indices in the Carnegie-Ames-Stanford Approach (CASA) and nighttime lights in the Open-source Data Inventory for Anthropogenic CO2 (ODIAC). From there, we take the additional step of using an empirical sink to calibrate terrestrial net biospheric exchange (NBE) to estimated values from atmospheric inversion systems. This approach removes a known, systematic bias in predicted atmospheric mixing ratios. Using these fluxes in a free running simulation, the model is able to reproduce in situ measurements with the same skill as when it uses gridded fluxes from a flux inversion system. Using these fluxes as a prior in an assimilation system, e.g. one incorporating retrievals of column CO2 from the Orbiting Carbon Observatory 2 (OCO-2), allows the analysis to capture variability in CO2 on scales that would be missed otherwise. This approach supports NASA's capability to forecast atmospheric CO2 up to two weeks in advance by leveraging a GEOS system used to produce quasi-operational weather analyses and forecasts, providing a valuable new tool to the carbon monitoring research and applications communities.

Weir, B.↗
NASA NTRS2020

Fisher's Peak Ecological Forecasting - Mapping Biomass to Inform Conservation Planning of a Future State Park in Southern Colorado

Fisher’s Peak is a 77.5 km2 property southeast of Trinidad, Colorado that is planned to become Colorado’s newest state park. The area has experienced limited anthropogenic disturbance and is home to an abundance of unique habitats and species. A rapid, approximately 900 m change in elevation over the extent of the area nurtures a variety of plants and animals, including the endangered New Mexico meadow jumping mouse. In 2019, the State of Colorado obtained Fisher’s Peak with plans to make it Colorado’s second largest state park. A diverse group of collaborators, including the Colorado State Forest Service and The Nature Conservancy, worked closely to design the state park to maximize recreation opportunity while conserving the property’s rich habitats and biodiversity. The Fisher’s Peak Ecological Forecasting Team utilized Light Detection and Ranging (LiDAR) surveys, in situ forest inventory data, and Earth observations from Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), Sentinel-2 Multispectral Instrument (MSI), Advanced Land Observing Satellite 2 (ALOS-2) Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) and the Shuttle Radar Topography Mission (SRTM) to quantify and map biomass over the extent of the study area. The results from modeling biomass had an out-of-bag root mean square error of 55 Mg/ha and an R2 of 12. The resulting map indicates areas where carbon storage on the property is high, informing decision-making processes for future park development. While more in situ training data may improve modeling capacity for biomass in the Fisher’s Peak area, this work represents a feasible attempt to better understand biomass distribution using earth observation

Lauren Lad↗