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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 NTRS1998

Monitoring of Volcanogenic CO2-Induced Tree Kills with AVIRIS Image Data at Mammoth Mountain, California

Elevated cold CO2 emissions from the flank of Mammoth Mountain volcano on the southwest rim of the Long Valley Caldera, eastern California, have been the cause of over 100 acres of dead trees in that area since 1990. The source of the CO2 gas is thought to be from one or more magmatic intrusion(s) beneath Mammoth Mountain and is probably related to a period of seismic unrest that began in 1989. The gas rises to the surface probably from depths of a few kilometers, along faults and fracture zones. The gas is at ambient temperature and diffuses from the soil rather than discharging from distinct vents. Typically, soil gas concentrations in tree-kill areas range from 10% to over 90% CO2 by volume, as compared to normal background of < 1% in healthy forest. The gas composition is predominantly CO2 mixed with air (sulfur gases are not elevated), and C and He isotopic ratios are consistent with a magmatic origin for the gas. The total CO2 emission has been estimated at 1200 tons/day, comparable to the emissions at Kilauea. Some of the dead trees are as old as 250 years, suggesting that similar anomalous gas discharge has not occurred over the previous few hundred years. The delta C-13/12 ratio in the Mammoth Mountain CO2 emission averages about -4.5 (PDB standard). This is consistent with a mantle source for the carbon. However, the large volume of the emission suggests that not all of the CO2 is necessarily being generated from the 1989 intrusion. The voluminous gas could be leaking from a vapor-rich zone, capped by an impermeable layer, that was supplied CO2 from degassing of many small magma bodies that intruded beneath the mountain over a period of decades or centuries. Earthquakes in 1989 could have fractured the capping layer and provided pathways for the escape Of CO2 to the surface. Alternatively, some of the CO2 could be derived from contact metamorphism of carbonate rocks intruded by magma. Carbonate-bearing Paleozoic roof pendents crop out in close proximity to Mammoth Mountain. It is possible that similar rocks could occur at depth beneath Mammoth Mountain, and could have contributed CO2 from thermal decomposition caused from recent intrusions. We hope to determine the C-13/12 ratio of a suite of samples to demonstrate if the carbonate rocks could be the source of at least part of the 1990-97 CO2 emission. To better understand the behavior of the CO2 gas, we have used hyperspectral imagery data of Mammoth Mountain acquired from the Airborne Visual/Infrared Imaging Spectrometer (AVIRIS) to map out areas of dead trees. The areas of tree kill have increased in size from about 50 acres in 1994 to about 100 acres in 1997. Tree kill is the major surface manifestation of the carbon dioxide flux at Mammoth Mountain, is widely dispersed, and has been cursorily mapped by regular field mapping techniques in the area. Initial investigations using airborne digital imagery from the Thematic Mapper Simulator (NS001) and AVIRIS instruments have shown extremely encouraging results for complete delineation of the vegetation anomalies. The most successful maps (when compared with ground truth) were developed using AVIRIS data with spectral angle mapper and matched filter algorithms with a data set that was reduced to maximum variance via the minimum noise fraction transformation. The result of this work is a series of maps that show the tree kill areas occurring in an halo-pattern surrounding the base of Mammoth Mountain. We are applying these same techniques to earlier AVIRIS images of Mammoth Mountain to examine the progression of the tree kill areas over time. Temporal maps of the tree kill areas may assist in constructing a picture of the structure beneath Mammoth Mountain.

Hausback, Brian P.↗
NASA NTRS1977

Inventory of forest resources (including water) by multi-level sampling

The author has identified the following significant results. A stratified random sample using LANDSAT band 5 and 7 panchromatic prints resulted in estimates of water in counties with sampling errors less than + or - 9% (67% probability level). A forest inventory using a four band LANDSAT color composite resulted in estimates of forest area by counties that were within + or - 6.7% and + or - 3.7% respectively (67% probability level). Estimates of forest area for counties by computer assisted techniques were within + or - 21% of operational forest survey figures and for all counties the difference was only one percent. Correlations of airborne terrain reflectance measurements with LANDSAT radiance verified a linear atmospheric model with an additive (path radiance) term and multiplicative (transmittance) term. Coefficients of determination for 28 of the 32 modeling attempts, not adverseley affected by rain shower occurring between the times of LANDSAT passage and aircraft overflights, exceeded 0.83.

Aldrich, R. C.↗
NASA NTRS2021

The Role of Fire in Global Forest Loss Dynamics

Fires, among other forms of natural and anthropogenic disturbance, play a central role in regulating the location, composition and biomass of forests. Understanding the role of fire in global forest loss is crucial in constraining land-use change emissions and the global carbon cycle. We analysed the relationship between forest loss and fire at 500 m resolution based on satellite-derived data for the 2003–2018 period. Satellite fire data included burned area and active fire detections, to best account for large and small fires, respectively. We found that, on average, 38 ± 9% (± range) of global forest loss was associated with fire, and this fraction remained relatively stable throughout the study period. However, the fraction of fire-related forest loss varied substantially on a regional basis, and showed statistically significant trends in key tropical forest areas. Decreases in the fraction of fire-related forest loss were found where deforestation peaked early in our study period, including the Amazon and Indonesia while increases were found for tropical forests in Africa. The inclusion of active fire detections accounted for 41%, on average, of the total fire-related forest loss, with larger contributions in small clearings in interior tropical forests and human-dominated landscapes. Comparison to higher-resolution fire data with resolutions of 375 and 20 m indicated that commission errors due to coarse resolution fire data largely balanced out omission errors due to missed small fire detections for regional to continental-scale estimates of fire-related forest loss. Besides an improved understanding of forest dynamics, these findings may help to refine and separate fire-related and non-fire-related land-use change emissions in forested ecosystems.

Dan van Wees↗
NASA NTRS2013

United States Forest Disturbance Trends Observed Using Landsat Time Series

Disturbance events strongly affect the composition, structure, and function of forest ecosystems; however, existing U.S. land management inventories were not designed to monitor disturbance. To begin addressing this gap, the North American Forest Dynamics (NAFD) project has examined a geographic sample of 50 Landsat satellite image time series to assess trends in forest disturbance across the conterminous United States for 1985-2005. The geographic sample design used a probability-based scheme to encompass major forest types and maximize geographic dispersion. For each sample location disturbance was identified in the Landsat series using the Vegetation Change Tracker (VCT) algorithm. The NAFD analysis indicates that, on average, 2.77 Mha/yr of forests were disturbed annually, representing 1.09%/yr of US forestland. These satellite-based national disturbance rates estimates tend to be lower than those derived from land management inventories, reflecting both methodological and definitional differences. In particular the VCT approach used with a biennial time step has limited sensitivity to low-intensity disturbances. Unlike prior satellite studies, our biennial forest disturbance rates vary by nearly a factor of two between high and low years. High western US disturbance rates were associated with active fire years and insect activity, while variability in the east is more strongly related to harvest rates in managed forests. We note that generating a geographic sample based on representing forest type and variability may be problematic since the spatial pattern of disturbance does not necessarily correlate with forest type. We also find that the prevalence of diffuse, non-stand clearing disturbance in US forests makes the application of a biennial geographic sample problematic. Future satellite-based studies of disturbance at regional and national scales should focus on wall-to-wall analyses with annual time step for improved accuracy.

Masek, Jeffrey G.↗
NASA NTRS2020

Structure and Parameter Uncertainty in Centennial Projections of Forest Community Structure and Carbon Cycling

Secondary forest regrowth shapes community succession and biogeochemistry for decades, including in the Upper Great Lakes region. Vegetation models encapsulate our understanding of forest function, and whether models can reproduce multi‐decadal succession patterns is an indication of our ability to predict forest responses to future change. We test the ability of a vegetation model to simulate C cycling and community composition during 100 years of forest regrowth following stand‐replacing disturbance, asking (a) Which processes and parameters are most important to accurately model Upper Midwest forest succession? (b) What is the relative importance of model structure versus parameter values to these predictions? We ran ensembles of the Ecosystem Demography model v2.2 with different representations of processes important to competition for light. We compared the magnitude of structural and parameter uncertainty and assessed which sub‐model–parameter combinations best reproduced observed C fluxes and community composition. On average, our simulations underestimated observed net primary productivity (NPP) and leaf area index (LAI) after 100 years and predicted complete dominance by a single plant functional type (PFT). Out of 4,000 simulations, only nine fell within the observed range of both NPP and LAI, but these predicted unrealistically complete dominance by either early hardwood or pine PFTs. A different set of seven simulations were ecologically plausible but under‐predicted observed NPP and LAI. Parameter uncertainty was large; NPP and LAI ranged from ~0% to >200% of their mean value, and any PFT could become dominant. The two parameters that contributed most to uncertainty in predicted NPP were plant–soil water conductance and growth respiration, both unobservable empirical coefficients. We conclude that (a) parameter uncertainty is more important than structural uncertainty, at least for ED‐2.2 in Upper Midwest forests and (b) simulating both productivity and plant community composition accurately without physically unrealistic parameters remains challenging for demographic vegetation models.

canopy radiative transfer↗
NASA NTRS1987

Evaluation of several classification schemes for mapping forest cover types in Michigan

Landsat MSS data were evaluated for mapping forest cover types in the northern Lower Peninsula of Michigan. The study examined seasonal variations, interpretation procedures and vegetation composition/distribution and their effect on overall classification accuracy and ability to identify individual pine species. Photographic images were used for visual interpretations while digital analysis was performed using a common (ERDAS) microcomputer image processing system. The classification schemes were evaluated using contingency tables and were ranked using the KAPPA statistic. The various classification schemes were ranked differentially according to study site location. Visual interpretation procedures ranked best, or least accurate, depending on the spatial distribution and complexity of the forest cover. Supervised classification techniques were more accurate than unsupervised clustering over all sites and seasons. Maximum likelihood classification of June data was superior to any digital classification technique of February data. The study indicates that classification accuracy is more dependent on the composition and distribution of forests in the northern lower Peninsula of Michigan than on the selection of a particular classification scheme.

Hudson, W. D.↗
NASA NTRS1984

Thematic Mapper simulator research for forest resource mapping in the Clearwater National Forest, Idaho

Per-pixel maximum likelihood digital classification and photo interpretation of Thematic Mapper Simulator (TMS) composited images for a managed conifer forest were used to evaluate both land cover and forest structure characteristics. TMS channels 4, 7, 5 and 3, which were found to be optimal for forest vegetation analysis, used the full range of the Thematic Mapper's spectral capability. Photo interpretation results indicate that a false color composite from TMS channels 4, 7, and 2 provided the highest accuracies; the combination of improved spatial, spectral and radiometric resolution of the Thematic Mapper yielded greater sensitivity to forest structural characteristics.

Brass, J. A.↗
NASA NTRS1990

Multiband radar characterization of forest biomes

The utility of airborne and orbital SAR in classification, assessment, and monitoring of forest biomes is investigated through analysis of orbital synthetic aperature radar (SAR) and multifrequency and multipolarized airborne SAR imagery relying on image tone and texture. Preliminary airborne SAR experiments and truck-mounted scatterometer observations demonstrated that the three dimensional structural complexity of a forest, and the various scales of temporal dynamics in the microwave dielectric properties of both trees and the underlying substrate would severely limit empirical or semi-empirical approaches. As a consequence, it became necessary to develop a more profound understanding of the electromagnetic properties of a forest scene and their temporal dynamics through controlled experimentation coupled with theoretical development and verification. The concatenation of various models into a physically-based composite model treating the entire forest scene became the major objective of the study as this is the key to development of a series of robust retrieval algorithms for forest biophysical properties. In order to verify the performance of the component elements of the composite model, a series of controlled laboratory and field experiments were undertaken to: (1) develop techniques to measure the microwave dielectric properties of vegetation; (2) relate the microwave dielectric properties of vegetation to more readily measured characteristics such as density and moisture content; (3) calculate the radar cross-section of leaves, and cylinders; (4) improve backscatter models for rough surfaces; and (5) relate attenuation and phase delays during propagation through canopies to canopy properties. These modeling efforts, as validated by the measurements, were incorporated within a larger model known as the Michigan Microwave Canopy Scattering (MIMICS) Model.

Dobson, M. Craig↗
NASA NTRS1972

Task 1: Correlation of satellite and ground data in air pollution studies. Task 2: Investigation to relate the chlorophyll and suspended sediment content in the waters of the lower Chesapeake Bay to ERTS-1 imagery. Task 3: The use of ERTS-1 to more fully utilize and apply marine station data to the study of productivity along the Eastern Shelf expanded waters of the United States

The author has identified the following significant results. Analysis of U-2 imagery of CARETS site indicates smoke plumes can be easily detected. First look at selected ERTS-1 color composites demonstrates plumes from forest fires can be detected.

Copeland, G. E.↗
NASA NTRS1984

Anaysis of the quality of image data required by the LANDSAT-4 Thematic Mapper and Multispectral Scanner

The spatial, geometric, and radiometric qualities of LANDSAT 4 thematic mapper (TM) and multispectral scanner (MSS) data were evaluated by interpreting, through visual and computer means, film and digital products for selected agricultural and forest cover types in California. Multispectral analyses employing Bayesian maximum likelihood, discrete relaxation, and unsupervised clustering algorithms were used to compare the usefulness of TM and MSS data for discriminating individual cover types. Some of the significant results are as follows: (1) for maximizing the interpretability of agricultural and forest resources, TM color composites should contain spectral bands in the visible, near-reflectance infrared, and middle-reflectance infrared regions, namely TM 4 and TM % and must contain TM 4 in all cases even at the expense of excluding TM 5; (2) using enlarged TM film products, planimetric accuracy of mapped poins was within 91 meters (RMSE east) and 117 meters (RMSE north); (3) using TM digital products, planimetric accuracy of mapped points was within 12.0 meters (RMSE east) and 13.7 meters (RMSE north); and (4) applying a contextual classification algorithm to TM data provided classification accuracies competitive with Bayesian maximum likelihood.

Colwell, R. N.↗
NASA NTRS1988

A composite L-band HH radar backscattering model for coniferous forest stands

The radar backscattering model developed by Richards et al. (1987), has been improved and further tested in this research. The trunk term may now be calculated from the exact solution to the electromagnetic wave equations instead of the corner reflector equation. Rough surface models have been introduced into the radar model, so that the forward reflectance and the backscattering from the ground surface are now calculated from the same model and, thus, are consistent. The number of trees in an individual pixel is assumed to be Poisson distributed, with tree height in a stand log-normally distributed. The simulated results show that the match of backscattering coefficients for eight forest stands between SIR-B image data and the simulated results are satisfying, and that the trunk term now seems to be convincingly established as the dominant term in the L-band HH radar return from coniferous forest stands.

Sun, Guoquing↗
NASA NTRS1989

Multipolarization P-, L-, and C-band radar for coastal zone mapping - The Louisiana example

Multipolarization P-, L-, and C-band airborne SAR data sets were acquired over a coastal zone and a forested wetland of southern Louisiana. The data sets were used with field-collected surface-parameter data in order to determine the value of SAR systems in assessing and mapping coastal-zone surface features. The coastal-zone surface features in this study are sediments, sediment distribution, and the formation of new isles and banks. Results of the data analysis indicate that the P-band radar with 68-cm wavelength is capable of detecting the submerged sediment if the area is very shallow (i.e., a water depth of less than one meter). The penetration capability of P-band radar is also demonstrated in the forested wetland area. The composition and condition of the ground surface can be detected, as well as the standing water beneath dense tree leaves.

Wu, Shih-Tseng↗
NASA NTRS2018

Mapping Mangrove Extent and Change: A Globally Applicable Approach

This study demonstrates a globally applicable method for monitoring mangrove forest extent at high spatial resolution. A 2010 mangrove baseline was classified for 16 study areas using a combination of ALOS PALSAR and Landsat composite imagery within a random forests classifier. A novel map-to-image change method was used to detect annual and decadal changes in extent using ALOS PALSAR/JERS-1 imagery. The map-to-image method presented makes fewer assumptions of the data than existing methods, is less sensitive to variation between scenes due to environmental factors (e.g., tide or soil moisture) and is able to automatically identify a change threshold. Change maps were derived from the 2010 baseline to 1996 using JERS-1 SAR and to 2007, 2008 and 2009 using ALOS PALSAR. This study demonstrated results for 16 known hotspots of mangrove change distributed globally, with a total mangrove area of 2,529,760 ha. The method was demonstrated to have accuracies consistently in excess of 90% (overall accuracy: 92.2–93.3%, kappa: 0.86) for mapping baseline extent. The accuracies of the change maps were more variable and were dependent upon the time period between images and number of change features. Total change from 1996 to 2010 was 204,850 ha (127,990 ha gain, 76,860 ha loss), with the highest gains observed in French Guiana (15,570 ha) and the highest losses observed in East Kalimantan, Indonesia (23,003 ha). Changes in mangrove extent were the consequence of both natural and anthropogenic drivers, yielding net increases or decreases in extent dependent upon the study site. These updated maps are of importance to the mangrove research community, particularly as the continual updating of the baseline with currently available and anticipated spaceborne sensors. It is recommended that mangrove baselines are updated on at least a 5-year interval to suit the requirements of policy makers.

Thomas, Nathan↗
NASA NTRS1974

Application of ERTS-1 imagery to land use, forest density and soil investigations in Greece

Photographic and digital imagery received from ERTS-1 was analyzed and evaluated as to its usefulness for the assessment of agricultural and forest land resources. Black and white, and color composite imagery provided spectral and spatial data, which, when matched with temporal land information, provided the basis for a semidetailed land use and forest site evaluation cartography. Color composite photographs have provided some information on the status of irrigation of agricultural lands. Computer processed digital imagery was successfully used for detailed crop classification and semidetailed soil evaluation. The results and techniques of this investigation are applicable to ecological and geological conditions similar to those prevailing in the Eastern Mediterranean.

Yassoglou, N. J.↗
NASA NTRS2010

Use of Current 2010 Forest Disturbance Monitoring Products for the Conterminous United States in Aiding a National Forest Threat Early Warning System

This presentation discusses contributions of near real time (NRT) MODIS forest disturbance detection products for the conterminous United States to an emerging national forest threat early warning system (EWS). The latter is being developed by the USDA Forest Service s Eastern and Western Environmental Threat Centers with help from NASA Stennis Space Center and the Oak Ridge National Laboratory. Building off work done in 2009, this national and regional forest disturbance detection and viewing capability of the EWS employs NRT MODIS NDVI data from the USGS eMODIS group and historical NDVI data from standard MOD13 products. Disturbance detection products are being computed for 24 day composites that are refreshed every 8 days. Products for 2010 include 42 dates of the 24 day composites. For each compositing date, we computed % change in forest maximum NDVI products for 2010 with respect to each of three historical baselines of 2009, 2007-2009, and 2003-2009,. The three baselines enable one to view potential current, recent, and longer term forest disturbances. A rainbow color table was applied to each forest change product so that potential disturbances (NDVI drops) were identified in hot color tones and growth (NDVI gains) in cold color tones. Example products were provided to end-users responsible for forest health monitoring at the Federal and State levels. Large patches of potential forest disturbances were validated based on comparisons with available reference data, including Landsat and field survey data. Products were posted on two internet mapping systems for US Forest Service internal and collaborator use. MODIS forest disturbance detection products were computed and posted for use in as little as 1 day after the last input date of the compositing period. Such products were useful for aiding aerial disturbance detection surveys and for assessing disturbance persistence on both inter- and intra-annual scales. Multiple 2010 forest disturbance events were detected across the nation, including damage from ice storms, tornadoes, caterpillars, bark beetles, and wildfires. This effort enabled improved NRT forest disturbance monitoring capabilities for this nation-wide forest threat EWS.

Spruce, Joseph P.↗
NASA NTRS2020

Acoustic space occupancy: Combining ecoacoustics and lidar to model biodiversity variation and detection bias across heterogeneous landscapes

There is global interest in quantifying changing biodiversity in human-modified landscapes. Ecoacoustics may offer a promising pathway for supporting multi-taxa monitoring, but its scalability has been hampered by the sonic complexity of biodiverse ecosystems and the imperfect detectability of animal-generated sounds. The acoustic signature of a habitat, or soundscape, contains information about multiple taxa and may circumvent species identification, but robust statistical technology for characterizing community-level attributes is lacking. Here, we present the Acoustic Space Occupancy Model, a flexible hierarchical framework designed to account for detection artifacts from acoustic surveys in order to model biologically relevant variation in acoustic space use among community assemblages. We illustrate its utility in a biologically and structurally diverse Amazon frontier forest landscape, a valuable test case for modeling biodiversity variation and acoustic attenuation from vegetation density. We use complementary airborne lidar data to capture aspects of 3D forest structure hypothesized to influence community composition and acoustic signal detection. Our novel analytic framework permitted us to model both the assembly and detectability of soundscapes using lidar-derived estimates of forest structure. Our empirical predictions were consistent with physical models of frequency-dependent attenuation, and we estimated that the probability of observing animal activity in the frequency channel most vulnerable to acoustic attenuation varied by over 60%, depending on vegetation density. There were also large differences in the biotic use of acoustic space predicted for intact and degraded forest habitats, with notable differences in the soundscape channels predominantly occupied by insects. This study advances the utility of ecoacoustics by providing a robust modeling framework for addressing detection bias from remote audio surveys while preserving the rich dimensionality of soundscape data, which may be critical for inferring biological patterns pertinent to multiple taxonomic groups in the tropics. Our methodology paves the way for greater integration of remotely sensed observations with high-throughput biodiversity data to help bring routine, multi-taxa monitoring to scale in dynamic and diverse landscapes.

Airborne lidar↗
NASA NTRS1977

Investigation of the effects of construction and stage filling of reservoirs on the environment and ecology: Preproject baseline

The author has identified the following significant results: (1) LANDSAT imagery can be used effectively as a baseline for detection of environmental change, resulting from construction of a major inland reservoir. (2) Forest cover can be observed adequately on two-band composite enlargements at a scale of 1:130,000. (3) Forest cover delineated on LANDSAT enlargements compares accurately with ground truth at a scale of 1:250,000. (4) A dual image mapping technique superimposing winter, summer, and spring scenes using the zoom transfer scope facilitates the determination. (5) The same technique can be used to detect changes in the project area, resulting from construction activities. (6) High altitude aircraft imagery can also be used to interpret changes in land use and forest type. (7) Construction operations can be more clearly detailed on the air photos than on LANDSAT imagery.

Riggins, R. E.↗