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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Selection of Hyperspectral Narrowbands (HNBs) and Composition of Hyperspectral Twoband Vegetation Indices (HVIs) for Biophysical Characterization and Discrimination of Crop Types Using Field Reflectance and Hyperion-EO-1 Data

The overarching goal of this study was to establish optimal hyperspectral vegetation indices (HVIs) and hyperspectral narrowbands (HNBs) that best characterize, classify, model, and map the world's main agricultural crops. The primary objectives were: (1) crop biophysical modeling through HNBs and HVIs, (2) accuracy assessment of crop type discrimination using Wilks' Lambda through a discriminant model, and (3) meta-analysis to select optimal HNBs and HVIs for applications related to agriculture. The study was conducted using two Earth Observing One (EO-1) Hyperion scenes and other surface hyperspectral data for the eight leading worldwide crops (wheat, corn, rice, barley, soybeans, pulses, cotton, and alfalfa) that occupy approx. 70% of all cropland areas globally. This study integrated data collected from multiple study areas in various agroecosystems of Africa, the Middle East, Central Asia, and India. Data were collected for the eight crop types in six distinct growth stages. These included (a) field spectroradiometer measurements (350-2500 nm) sampled at 1-nm discrete bandwidths, and (b) field biophysical variables (e.g., biomass, leaf area index) acquired to correspond with spectroradiometer measurements. The eight crops were described and classified using approx. 20 HNBs. The accuracy of classifying these 8 crops using HNBs was around 95%, which was approx. 25% better than the multi-spectral results possible from Landsat-7's Enhanced Thematic Mapper+ or EO-1's Advanced Land Imager. Further, based on this research and meta-analysis involving over 100 papers, the study established 33 optimal HNBs and an equal number of specific two-band normalized difference HVIs to best model and study specific biophysical and biochemical quantities of major agricultural crops of the world. Redundant bands identified in this study will help overcome the Hughes Phenomenon (or "the curse of high dimensionality") in hyperspectral data for a particular application (e.g., biophysical characterization of crops). The findings of this study will make a significant contribution to future hyperspectral missions such as NASA's HyspIRI. Index Terms-Hyperion, field reflectance, imaging spectroscopy, HyspIRI, biophysical parameters, hyperspectral vegetation indices, hyperspectral narrowbands, broadbands.

Vegetation↗
NASA NTRS2015

Interannual Variability of Tropospheric Trace Gases and Aerosols: The Role of Biomass Burning Emissions

Fires are responsible for a range of gaseous and aerosol emissions. However, their influence on the interannual variability of atmospheric trace gases and aerosols has not been systematically investigated from a global perspective. We examine biomass burning emissions as a driver of interannual variability of large-scale abundances of short-lived constituents such as carbon monoxide (CO), hydroxyl radicals (OH), ozone and aerosols using the GISS ModelE composition-climate model and a range of observations, with an emphasis on satellite information. Our model captures the observed variability of the constituents examined in most cases, but with substantial underestimates in boreal regions. The strongest interannual variability on a global scale is found for carbon monoxide (10 for its global annual burden), while the lowest is found for tropospheric ozone (10 for its global annual burden). Regionally, aerosol optical depth shows variability that exceeds 50. Areas of strong variability include the tropical land regions and northern high latitudes, while even regions in the northern midlatitudes experience substantial inteannual variability of aerosols. Ozone variability peaks over Equatorial Asia in boreal autumn, partly due to varying biomass burning emissions, and over the western and central Pacific in the rest of the year, mainly due to meteorological fluctuations. We find that biomass burning emissions are almost entirely responsible for global CO interannual variability, and similarly important for OH variability. The same is true for global and regional aerosol variability, especially when not taking into account dust and sea-salt particles. We show that important implications48 can arise from such interannual influences for regional climate and air quality.

aerosols↗
NASA NTRS1993

Remote sensing of submerged vegetation canopies for biomass estimation

The visible bands of the Landsat Thematic Mapper (TM) sensor were used in an empirical assessment of seagrass biomass on shallow banks near Lee Stocking Island in the Bahamas. The TM bands were transformed to minimize the depth-dependent variance in the bottom reflectance signal. Regression analyses were performed between the transformed bands and field measurements of seagrass standing crop (above-ground biomass). Regression equations using spectral data accounted for up to 80 per cent of the variability in seagrass biomass. The unexplained variance was ascribed to variations in bottom sediment color.

Armstrong, Roy A.↗
NASA NTRS1984

Biological Oceanography

Within the framework of global biogeochemical cycles and ocean productivity, there are two areas that will be of particular interest to biological oceanography in the 1990s. The first is the mapping in space time of the biomass and productivity of phytoplankton in the world ocean. The second area is the coupling of biological and physical processes as it affects the distribution and growth rate of phytoplankton biomass. Certainly other areas will be of interest to biological oceanographers, but these two areas are amenable to observations from satellites. Temporal and spatial variability is a regular feature of marine ecosystems. The temporal and spatial variability of phytoplankton biomass and productivity which is ubiquitous at all time and space scales in the ocean must be characterized. Remote sensing from satellites addresses these problems with global observations of mesocale (2 to 20 days, 10 to 200 km) features over a long period of time.

Abbott, M. R.↗
NASA NTRS1991

Relationships between CH4 emission, biomass, and CO2 exchange in a subtropical grassland

Methane flux was linearly correlated with plant biomass (r = 0.97, n = 6 and r = 0.95, n = 8) at two locations in a Florida Everglades Cladium marsh. One location, which had burned 4 months previously, exhibited a greater increase in methane flux as a function of biomass relative to sites at an unburned location. However, methane flux data from both sites fit a single regression (r = 0.94, n = 14) when plotted against net CO2 exchange suggesting that either methanogenesis in Everglades marl sediments is fueled by root exudation below ground, or that factors which enhance photosynthetic production and plant growth are also correlated with methane production and flux in this oligotrophic environment. The data presented are the first to show a direct relationship between spatial variability in plant biomass, net ecosystem production, and methane emission in a natural wetland.

Whiting, Gary J.↗
NASA NTRS2012

Understanding Climate Policy Data Needs. NASA Carbon Monitoring System Briefing: Characterizing Flux Uncertainty, Washington D.C., 11 January 2012

Climate policy in the United States is currently guided by public-private partnerships and actions at the local and state levels. This mitigation strategy is made up of programs that focus on energy efficiency, renewable energy, agricultural practices and implementation of technologies to reduce greenhouse gases. How will policy makers know if these strategies are working, particularly at the scales at which they are being implemented? The NASA Carbon Monitoring System (CMS) will provide information on carbon dioxide fluxes derived from observations of earth's land, ocean and atmosphere used in state of the art models describing their interactions. This new modeling system could be used to assess the impact of specific policy interventions on CO2 reductions, enabling an iterative, results-oriented policy process. In January of 2012, the CMS team held a meeting with carbon policy and decision makers in Washington DC to describe the developing modeling system to policy makers. The NASA CMS will develop pilot studies to provide information across a range of spatial scales, consider carbon storage in biomass, and improve measures of the atmospheric distribution of carbon dioxide. The pilot involves multiple institutions (four NASA centers as well as several universities) and over 20 scientists in its work. This pilot study will generate CO2 flux maps for two years using observational constraints in NASA's state-of -the-art models. Bottom-up surface flux estimates will be computed using data-constrained land and ocean models; comparison of the different techniques will provide some knowledge of uncertainty in these estimates. Ensembles of atmospheric carbon distributions will be computed using an atmospheric general circulation model (GEOS-5), with perturbations to the surface fluxes and to transport. Top-down flux estimates will be computed from observed atmospheric CO2 distributions (ACOS/GOSAT retrievals) alongside the forward-model fields, in conjunction with an inverse approach based on the CO2 model of GEOS ]Chem. The forward model ensembles will be used to build understanding of relationships among surface flux perturbations, transport uncertainty and atmospheric carbon concentration. This will help construct uncertainty estimates and information on the true spatial resolution of the top-down flux calculations. The relationship between the top-down and bottom-up flux distributions will be documented. Because the goal of NASA CMS is to be policy relevant, the scientists involved in the flux modeling pilot need to understand and be focused on the needs of the climate policy and decision making community. If policy makers are to use CMS products, they must be aware of the modeling effort and begin to design policies that can be evaluated with information. Improving estimates of carbon sequestered in forests, for example, will require information on the spatial variability of forest biomass that is far more explicit than is presently possible using only ground observations. Carbon mitigation policies being implemented by cities around the United States could be designed with the CMS data in mind, enabling sequential evaluation and subsequent improvements in incentives, structures and programs. The success of climate mitigation programs being implemented in the United States today will hang on the depth of the relationship between scientists and their policy and decision making counterparts. Ensuring that there is two-way communication between data providers and users is important for the success both of the policies and the scientific products meant to support them..

Brown, Molly E.↗
NASA NTRS1974

Vegetation density as deduced from ERTS-1 MSS response

Reflectance from vegetation increases with increasing vegetation density in the 0.75- to 1.35 micron wavelength interval. Therefore, ERTS-1 bands 6 (0.7 to 0.8 micron) and 7 (0.8 to 1.1 micron) contain information that should relate to the probable yield of crops and the animal carrying capacity of rangeland. The results of an experiment designed specifically to test the relations among leaf area index (LAI), plant population, plant cover and plant height, and the ERTS-1 MSS responses for 3 corn, 10 sorghum, and 10 cotton fields are given. Plant population was as useful as LAI for characterizing the sorghum and corn fields, and plant height was as good as LAI for characterizing cotton fields. These findings generally support the utility of ERTS-1 data for explaining variability in green biomass, harvestable forage and other indicators of productivity.

Wiegand, C. L.↗
NASA NTRS1988

Ocean color observations of phytoplankton distributions and primary productivity

The primary goal of this activity is to develop the means to assess the mean and variability of phytoplankton biomass and primary productivity on global scales. There are three major approaches whose goals are to provide global scale observations. These are processing and analysis of the complete CZCS data set in a consistent manner; preparing science mission and project implementation plans for the SeaWiFS sensor to be launched on LANDSAT 6 in 1991; and providing guidance to EOS flight projects for ocean color observations using the MODIS sensor planned for the Polar Platform in the mid 1990's. This processing presents the first consistent view of phytoplankton pigments on global scales, and analysis of this temporally undersampled data set is proving very instructive in specifying mission requirements for SeaWiFS and future algorithm development.

Esaias, W.↗
NASA NTRS2017

What Factors Control the Trend of Increasing AAOD Over the United States in the Last Decade?

We examine the spatial and temporal trends of absorbing aerosol optical depth (AAOD) in the last decade over the United States (U.S.) observed by the Ozone Monitoring Instrument (OMI). Monthly average OMI AAOD has increased over broad areas of the central U.S. from 2005 to 2015, by up to a factor of 4 in some grid cells (~60 km resolution). The AAOD increases in all seasons, although the percentage increases are larger in summer (June-July-August) than in winter (December-January-February) by a factor of 3. Despite enhancements in AAOD, OMI AOD exhibits insignificant trend over most of the U.S. except parts of the central and western U.S., the latter which may partly be due to decreases in precipitation. Trends in AAOD contrast with declining trends in surface concentrations of black carbon (BC) aerosol. Interannual variability of local biomass burning emissions of BC may contribute to the positive trend in AAOD over the western U.S. Changes in both dust aerosol measured at the surface (in terms of concentration and size) and dust AAOD indicate distinct enhancements, especially over the central U.S. by 50-100%, which appears to be one of the major factors that impacts positive trends in AAOD.

Satellite retrieval↗
NASA NTRS1986

Remote sensing investigations of wetland biomass and productivity for global biosystems research

The relationship between spectral radiance and plant canopy biomass was studied in wetlands. Spectroradiometer data was gathered on Thematic Mapper wavebands 3, 4, and 5, and correlated with canopy and edaphic factors determined by harvesting. The relationship between spectral radiance and plant canopy biomass for major salt and brackish canopy types was determined. Algorithms were developed for biomass measurement in mangrove swamps. The influence of latitudinal variability in canopy structure on biomass assessment of selected plants was investigated. Brackish marsh biomass estimates were obtained from low altitude aircraft and compared with ground measurements. Annual net aerial primary productivity estimates computed from spectral radiance data were compiled for a Spartina alterniflora marsh. Spectral radiance data were expressed as vegetation or infrared index values. Biomass estimates computed from models were in close agreement with biomass estimates determined from harvests.

Klemas, V.↗
NASA NTRS1979

Relationship of red and photographic infrared spectral radiances to alfalfa biomass, forage water content, percentage canopy cover, and severity of drought stress

Red and photographic infrared spectral data were collected using a handheld radiometer for two cuttings of alfalfa. Significant linear and non-linear correlation coefficients were found between the spectral variables and plant height, biomass, forage water content, and estimated canopy cover for the earlier alfalfa cutting. The alfalfa of later cutting experienced a period of severe drought stress which limited growth. The spectral variables were found to be highly correlated with the estimated drought scores for this alfalfa cutting.

Tucker, C. J.↗
NASA NTRS1999

Canopy Cover Predictions using Ground Observations and Remotely Sensed Data

Maps of vegetation status are needed at many scales, from the field level to monitor ecosystem condition to the global level to understand the carbon cycle. Status is quantified by such variables as leaf area index, biomass, and fraction of canopy cover. Current methods of predicting vegetation variables use remote sensing data to provide a spatially exhaustive data source. In a study in western Montana, several hundred ground observations made by the US Forest Service on tenth-acre conifer plots were used to develop aspatial regression and geostatistical prediction models. Normalized Difference Vegetation Index (NDVI) values from Landsat Thematic Mapper images were used as ancillary data. These models were then used to predict canopy cover at unsampled locations in a 97 square kilometer region on the boundary of the Flathead National Forest and the Bob Marshall Wilderness. Independent data from two dates six years apart were used for validation. Given the assumption that actual canopy cover remained relatively unchanged within this time period, partial validation can be achieved by measuring the correspondence of the two maps. This criterion results in ranking the aspatial regression maps as less accurate than the geostatistically generated maps. The geostatistical approach emphasizes ground measurements more heavily than does aspatid regression. Geostatistical simulations of canopy cover also provide a means of describing uncertainty about the patterns of canopy cover.

Dungan, Jennifer L.↗
NASA NTRS1980

Relationship of crop radiance to alfalfa agronomic values

Red and photographic infrared spectral data of alfalfa were collected at the time of the third and fourth cuttings using a hand-held radiometer for the earlier alfalfa cutting. Significant linear and non-linear correlation coefficients were found between the spectral variables and plant height, biomass, forage water content, and estimated canopy cover. For the alfalfa of the later cutting, which had experienced a period of severe drought stress which limited growth, the spectral variables were found to be highly correlated with the estimated drought scores.

Tucker, C. J.↗
NASA NTRS2008

Model Effects on GLAS-Based Regional Estimates of Forest Biomass and Carbon

ICESat/GLAS waveform data are used to estimate biomass and carbon on a 1.27 million sq km study area. the Province of Quebec, Canada, below treeline. The same input data sets and sampling design are used in conjunction with four different predictive models to estimate total aboveground dry forest biomass and forest carbon. The four models include nonstratified and stratified versions of a multiple linear model where either biomass or (square root of) biomass serves as the dependent variable. The use of different models in Quebec introduces differences in Provincial biomass estimates of up to 0.35 Gt (range 4.942+/-0.28 Gt to 5.29+/-0.36 Gt). The results suggest that if different predictive models are used to estimate regional carbon stocks in different epochs, e.g., y2005, y2015, one might mistakenly infer an apparent aboveground carbon "change" of, in this case, 0.18 Gt, or approximately 7% of the aboveground carbon in Quebec, due solely to the use of different predictive models. These findings argue for model consistency in future, LiDAR-based carbon monitoring programs. Regional biomass estimates from the four GLAS models are compared to ground estimates derived from an extensive network of 16,814 ground plots located in southern Quebec. Stratified models proved to be more accurate and precise than either of the two nonstratified models tested.

Nelson, Ross↗
NASA NTRS1981

Simulated directional radiances of vegetation from satellite platforms

A computer modeling and simulation investigated the effects of off-nadir viewing, canopy geometry and density, solar zenith angle, and atmospheric conditions on the radiance of several vegetated targets. Effects on the normalized difference (ND) index were also investigated, and two wavelengths of 0.68 and 0.80 micron were simulated at nine sensor zenith angles, five sensor azimuths, and nine solar zenith angles. Seven canopies of low, medium, and high densities were observed, and bidirectional reflectance functions of other canopies were discussed. A modified Turner's (1974) atmospheric radiative transfer model was used for 2300 simulation runs. Off-nadir viewing effects were more pronounced in the red than the infrared, and the variability was found to be a function of canopy geometry. The ND index eliminated much of the variability seen in the individual bands, while the overall variability decreased with increasing biomass, and increased with increasing solar zenith angles.

Kirchner, J. A.↗
NASA NTRS1991

Basin-scale estimates of oceanic primary production by remote sensing - The North Atlantic

The monthly averaged CZCS data for 1979 are used to estimate annual primary production at ocean basin scales in the North Atlantic. The principal supplementary data used were 873 vertical profiles of chlorophyll and 248 sets of parameters derived from photosynthesis-light experiments. Four different procedures were tested for calculation of primary production. The spectral model with nonuniform biomass was considered as the benchmark for comparison against the other three models. The less complete models gave results that differed by as much as 50 percent from the benchmark. Vertically uniform models tended to underestimate primary production by about 20 percent compared to the nonuniform models. At horizontal scale, the differences between spectral and nonspectral models were negligible. The linear correlation between biomass and estimated production was poor outside the tropics, suggesting caution against the indiscriminate use of biomass as a proxy variable for primary production.

Platt, Trevor↗
NASA NTRS2010

Long-Term Time Series of Remote Sensing Observations for Development of Regulatory Water Quality Standards

Water quality standards in the U.S. consist of: designated uses (the services that a water body provides; e.g., drinking water, aquatic life, harvestable species, recreation) . criteria that define the environmental conditions that must be maintained to support the uses For estuaries and coastal waters in the Gulf of Mexico, there are no numeric (quantitative) criteria to protect designated uses from effects of nutrients. This is largely due to the absence of adequate data that would quantitatively link biological conditions to nutrient concentrations. The Gulf of Mexico Alliance, an organization fostering collaboration between the Gulf States and U.S. Federal agencies, has identified the development of the numeric nutrient criteria as a major step leading to reduction in MODIS Products Figure 6. Map of the Mobile Bay with a yellow patch indicating the Bon Secour Bay area selected in this study for averaging water clarity parameters retrieved from MODIS datasets. nutrient inputs to coastal ecosystems. Nutrient enrichment in estuaries and coastal waters can be quantified based on response variables that measure phytoplankton biomass and water clarity. Long-term, spatially and temporally resolved measurements of chlorophyll a concentration, total concentration of suspended solids, and water clarity are needed to establish reference conditions and to quantify stressor-response relationships.

Blonski, Slawomir↗
NASA NTRS2016

Analysis of Satellite and Airborne Imagery for Detection of Water Hyacinth and Other Invasive Floating Macrophytes and Tracking of Aquatic Weed Control Efficacy

Waterways of the Sacramento San Joaquin Delta have recently become infested with invasive aquatic weeds such as floating water hyacinth (Eichhoria crassipes) and water primrose (Ludwigia peploides). These invasive plants cause many negative impacts, including, but not limited to: the blocking of waterways for commercial shipping and boating; clogging of irrigation screens, pumps and canals; and degradation of biological habitat through shading. Zhang et al. (1997, Ecological Applications, 7(3), 1039-1053) used NASA Landsat satellite imagery together with field calibration measurements to map physical and biological processes within marshlands of the San Francisco Bay. Live green biomass (LGB) and related variables were correlated with a simple vegetation index ratio of red and near infra-red bands from Landsat images. More recently, the percent (water area) cover of water hyacinth plotted against estimated LGB of emergent aquatic vegetation in the Delta from September 2014 Landsat imagery showed an 80 percent overall accuracy. For the past two years, we have partnered with the U. S. Department of Agriculture (USDA) and the Department of Plant Sciences, University of California at Davis to conduct new validation surveys of water hyacinth and water primrose coverage and LGB in Delta waterways. A plan is underway to transfer decision support tools developed at NASA's Ames Research Center based on Landsat satellite images to improve Delta-wide integrated management of floating aquatic weeds, while reducing chemical control costs. The main end-user for this application project will be the Division of Boating and Waterways (DBW) of the California Department of Parks and Recreation, who has the responsibility for chemical control of water hyacinth in the Delta.

Agriculture↗