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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Remote sensing of canopy chemistry and nitrogen cycling in temperate forest ecosystems

The use of images acquired by the Airborne Imaging Spectrometer, an experimental high-spectral resolution imaging sensor developed by NASA, to estimate the lignin concentration of whole forest canopies in Wisconsin is reported. The observed strong relationship between canopy lignin concentration and nitrogen availability in seven undisturbed forest ecosystems on Blackhawk Island, Wisconsin, suggests that canopy lignin may serve as an index for site nitrogen status. This predictive relationship presents the opportunity to estimate nitrogen-cycling rates across forested landscapes through remote sensing.

Wessman, Carol A.↗
NASA NTRS1985

Mapping diverse forest cover with multipolarization airborne radar

Imaging radar backscatter in continuously forested areas contains information about the forest canopy; it also contains data about topography, landforms, and terrain texture. For purposes of radar image interpretation and geologic mapping researchers were interested in identifying and separating forest canopy effects from geologic or geomorphic effects on radar images. The objectives of this investigation was to evaluate forest canopy variables in multipolarization radar images under conditions where geologic and topographic variables are at a minimum. A subsidiary objective was to compare the discriminatory capabilities of the radar images with corresponding optical images of similar spatial resolution. It appears that the multipolarization images discriminate variation in tree density, but no evidence was found for discrimination between evergreen and deciduous forest types.

Ford, J. P.↗
NASA NTRS1994

Seasonal Patterns and Remote Spectral Estimation of Canopy Chemistry Across the Oregon Transect

We examined seasonal changes in canopy chemical concentrations and content in conifer forests growing along a climate gradient in western Oregon, as part of the Oregon Transect Ecosystem Research (OTTER) study. The chemical variables were related to seasonal patterns of growth and production. Statistical comparisons of chemical variables with data collected from two different airborne remote-sensing platforms were also carried out. Total nitrogen (N) concentrations in foliage varied significantly both seasonally and among sites; when expressed as content in the forest canopy, nitrogen varied to a much greater extent and was significantly related to aboveground net primary production (r = 0.99). Chlorophyll and free amino acid concentrations varied more strongly than did total N and may have reflected changes in physiological demands for N. Large variations in starch concentrations were measured from pre- to post-budbreak in all conifer sites. Examination of remote-sensing data from two different airborne instruments suggests the potential for remote measurement of some canopy chemicals. Multivariate analysis of high-resolution spectral data in the near infrared region indicated significant correlations between spectral signals and N concentration and canopy N content; the correlation with canopy N content was stronger and was probably associated in part with water absorption features of the forest canopy. The spectral bands that were significantly correlated with lignin concentration and content were similar to bands selected in the other laboratory and airborne studies; starch concentrations were not significantly related to spectral reflectance data. Strong relationships between the spectral position of specific reflectance features in the visible region and chlorophyll were also found.

Matson, Pamela↗
DOE OSTI2020

Leaf traits and canopy structure together explain canopy functional diversity: an airborne remote sensing approach

Plant functional diversity is strongly connected to photosynthetic carbon assimilation in terrestrial ecosystems. However, many of the plant functional traits that regulate photosynthetic capacity, including foliar nitrogen concentration and leaf mass per area, vary significantly between and within plant functional types and vertically through forest canopies, resulting in considerable landscape-scale heterogeneity in three dimensions. Hyperspectral imagery has been used extensively to quantify functional traits across a range of ecosystems but is generally limited to providing information for top-of-canopy leaves only. On the other hand, lidar data can be used to retrieve the vertical structure of forest canopies. Because these data are rarely collected at the same time, there are unanswered questions about the effect of forest structure on the 3-D spatial patterns of functional traits across ecosystems. In the United States, the National Ecological Observatory Network's Airborne Observation Platform (NEON AOP) provides an opportunity to address this structure-function relationship by collecting lidar and hyperspectral data together across a variety of ecoregions. With a fusion of hyperspectral and lidar data from the NEON AOP and field-collected foliar trait data, we assessed the impacts of forest structure on spatial patterns of N. In addition, we examine the influence of abiotic gradients and management regimes on top of canopy %N and total canopy N (i.e. the total amount of N (g/m 2 ) within a forest canopy) at a NEON site consisting of a mosaic of open longleaf pine and dense broadleaf deciduous forests. Here, our resulting maps suggest that in contrast with top-of-canopy values, total canopy N variation is dampened across this landscape resulting in relatively homogeneous spatial patterns. At the same time, we found that leaf functional diversity and canopy structural diversity showed distinct dendritic patterns related to the spatial distribution of plant functional types.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1986

Lithologic mapping in a forested region using remotely sensed data

Forest canopies over different sedimentary lithologies of valleys and ridges are composed of different dominant species and have significantly different reflectance and emittance. In a botanical survey of eighty-seven forest sites, sedimentary lithologies were found to differ in the species which dominate the forest canopy. Sandstone sites had abundant chestnut oak (Quercus prinus), black oak (Q. velutina), and northern red oak (Q. rubra). On shale sites chestnut oak, white oak (Q. alba), northern red oak and red pine (Pinus resinosa) were dominant. Limestone sites had a variable species composition with the most common species, northern red oak, white oak, and black locust (Robinia pseudocacia) accounting for only 30 percent of the total trees. Thematic Mapper Simulator (TMS) data obtained during the growing season were analyzed to determine if sandstones, shales, and limestones could be distinguished on the basis of forest-canopy reflectance. The observations compared in the analysis were means of the eight TMS bands for 10 x 10-pixel test sites selected from areas with complete canopy closure. In August imagery the three lithologies were separable based on differences in TMS band 3 (630-690 nm) and band 8 (10.4-12.5 microns).

Masuoka, E.↗
NASA NTRS2017

Patterns of Canopy and Surface Layer Consumption in a Boreal Forest Fire from Repeat Airborne Lidar

Fire in the boreal region is the dominant agent of forest disturbance with direct impacts on ecosystem structure, carbon cycling, and global climate. Global and biome-scale impacts are mediated by burn severity, measured as loss of forest canopy and consumption of the soil organic layer. To date, knowledge of the spatial variability in burn severity has been limited by sparse field sampling and moderate resolution satellite data. Here, we used pre- and post-fire airborne lidar data to directly estimate changes in canopy vertical structure and surface elevation for a 2005 boreal forest fire on Alaskas Kenai Peninsula. We found that both canopy and surface losses were strongly linked to pre-fire species composition and exhibited important fine-scale spatial variability at sub-30m resolution. The fractional reduction in canopy volume ranged from 0.61 in lowland black spruce stands to 0.27 in mixed white spruce and broad leaf forest. Residual structure largely reflects standing dead trees, highlighting the influence of pre-fire forest structure on delayed carbon losses from above ground biomass, post-fire albedo, and variability in understory light environments. Median loss of surface elevation was highest in lowland black spruce stands (0.18 m) but much lower in mixed stands (0.02 m), consistent with differences in pre-fire organic layer accumulation. Spatially continuous depth-of-burn estimates from repeat lidar measurements provide novel information to constrain carbon emissions from the surface organic layer and may inform related research on post-fire successional trajectories. Spectral measures of burn severity from Landsat were correlated with canopy (r = 0.76) and surface (r = -0.71) removal in black spruce stands but captured less of the spatial variability in fire effects for mixed stands (canopy r = 0.56, surface r = -0.26), underscoring the difficulty in capturing fire effects in heterogeneous boreal forest landscapes using proxy measures of burn severity from Landsat.

Alonzo, Michael↗
NASA NTRS1976

A canopy-related stratification of a southern pine forest using LANDSAT digital data

An investigation was undertaken to determine if a consistent stratification of a Southern pine forest could be obtained by using LANDSAT multispectral scanner data to assess crown closure. Winter and summer LANDSAT scenes of the North Carolina coastal region were analyzed individually and then registered and merged to take advantage of temporal changes in the forest canopy. Three levels of pine crown closure were accurately delineated. The applicability of this stratification as supplemental input to a forest inventory system is also discussed.

Williams, D. L.↗
NASA NTRS1976

A canopy-related stratification of a Southern pine forest using Landsat digital data

An investigation was undertaken to determine if a consistent stratification of a Southern pine forest could be obtained by using Landsat multispectral scanner data to assess crown closure. Winter and summer Landsat scenes of the North Carolina coastal region were analyzed individually and then registered and merged to take advantage of temporal changes in the forest canopy. Three levels of pine crown closure were accurately delineated. The applicability of this stratification as supplemental input to a forest inventory system is also discussed.

Williams, D. L.↗
NASA NTRS1990

Field testing of thermal canopy models in a spruce-fir forest

Recent advances in remote sensing technology allow the use of the thermal infrared region to gain information about vegetative surfaces. Extending existing models to account for thermal radiance transfers within rough forest canopies is of paramount importance. This is so since all processes of interest in the physical climate system and biogeochemical cycles are thermally mediated. Model validation experiments were conducted at a well established boreal forest; northern hardwood forest ecotone research site located in central Maine. Data was collected to allow spatial and temporal validation of thermal models. Emphasis was placed primarily upon enhancing submodels of stomatal behavior, and secondarily upon enhancing boundary layer resistance submodels and accounting for thermal storage in soil and vegetation.

Source record↗
NASA NTRS1995

Pseudo-wavelet analysis of turbulence patterns in three vegetation layers

Ramp patterns in scalar traces such as temperature are the signature of coherent structures. A pseudo-wavelet analysis technique was developed in which ideal saw-tooth patterns of varying size were used as basis functions and fitted to temperature and velocity data. Data recorded from three very different vegetation stands were examined in this study. It was found that the most probable structure duration for the forest canopy was in the range 35-40 s, for the orchard canopy it was 20-25 s and for the maize it was 15-20 s. When expressed in non-dimensional form, the structure duration probability distribution for the maize canopy was about a decade larger than for the forest canopy, with the orchard canopy intermediate. The mean eddy duration versus wind shear relation falls on a narrow band for all three canopies, indicating that wind shear at the canopy top is the determining factor for the scale of the coherent eddies. The inverse of duration and intermittency of coherent structures exhibits a tendency of independence from wind shear at higher wind shear values. Coherent structures transport heat in a more efficient way than do smaller scale, less coherent motions. In all the canopies, the heat flux fractions associated with coherent structures are at least 10% higher than the corresponding time fraction.

Qiu, Jie↗
NASA NTRS1990

Measurements of soil and canopy exchange rates in the Amazon rain forest using Rn-222

Measurements were taken of the emission of Rn-222 from Amazon forest rocks and soils and used as a tracer of ventilation of the forest canopy layer at night. It was determined that the greatest resistance to transfer of trace gases from the soil to the atmosphere lies in the soil air space. Profiles of Rn-222 and CO2 showed steepest concentration gradients in the layer between 0 and 3 m above soil surface. Aerodynamic resistances calculated for this layer from Rn-222 and CO2 varied from 1.6 to 18 s/cm, with greater resistance during the afternoon than at night. The resistance to exchange with air from the entire 41 m layer below the canopy averaged 4.8 s/cm during 13 nights of CO2 profiles. The calculated average time to flush the layer below 41 m is 5.5 hr, and it is concluded that this indicates that significant exchange occurs despite nocturnal stratification.

Trumbore, S. E.↗
DOE OSTI2025

Benchmarking Near-Surface Winds in the HRRR Analyses Using Multisource Observations over Complex Terrain in the Southeastern United States

Wind energy plays a crucial role in sustainable power generation, yet its full potential in the southeast United States (SEUS) remains underexplored. This study advances wind resource assessment in the SEUS using existing regional modeling and multisource observations. We find that terrain complexity, influenced by orography and forest canopy, significantly impacts the accuracy of modeled wind speed. While the High-Resolution Rapid Refresh (HRRR) model effectively simulates wind profiles over flat, nonforested terrain, larger errors are produced above forest canopies, and particularly for those stands in hilly and mountainous terrain where there are no observations aloft that could be used by HRRR’s data assimilation software. Seasonal variations, e.g., changes in the leaf area index, further complicate the relationship between terrain complexity and simulation errors. Here, our findings emphasize the critical need for comprehensive wind profile measurements, extending from below the canopy to height above the canopy and through the lower planetary boundary layer, to fully quantify model performance over and near forests, and for improving wind resource assessment, planning, and management. This study provides valuable insights not only for further model development but also for future field campaign deployment with the goal of further improving our understanding of wind resources in the region.

Complex terrain↗
NASA NTRS1987

Estimating key forest ecosystem parameters through remote sensing

Forest canopy chemistry and biomass indicators of ecosystem photosynthesis and decomposition processes are presently studied in view of Airborne Imaging Spectrometer data, which generated spectra from averaged 3 x 3 pixel areas for each of 20 sites for mutual qualitative comparison. Vegetation spectra were strongly differentiated from other cover types by an apparent absorption feature at 1500-1700 nm. Preliminary work with stepwise regression suggests that lignin may play a role in canopy reflectance, and that there is potential for remote detection of forest canopy lignin.

Wessman, Carol A.↗
NASA NTRS1985

Characterizing terrestrial ecosystems and productivity from remote sensing data

Predictive relationships were studied between the leaf area index (LAI) of temperate coniferous forests and the canopy of reflective properties as sensed by satellites. Also, the relationship was examined between this sensible variable, LAI, and functional properties such as net primary productivity (NPP) and nitrogen mineralization. Leaf surface area is a locus of many important material and energy exchanges. If LAI can be reasonably estimated from remote sensing measurements, then it could be used with models to predict evapotranspiration, radiation interception, precipitation interception, and other ecosystem processes over large areas. Nineteen mature closed canopy forest stands were measured for leaf area index distributed along a temperature moisture gradient across Oregon. The LAI varies from 15.4 to 0.6. Infrared radiation is strongly scattered by leaves so that it penetrates deeply and its reflectance is proportional to LAI. Red radiation is strongly absorbed by chlorophyll and its reflectance is inversely related to LAI, becoming asymptotic at LAI values of about 3. The ratio of infrared to red radiation compensates for irradiance variations across this transect.

Peterson, David L.↗
NASA NTRS1990

Application of the Semivariogram Textural Classifier (STC) to SIR-B data of Borneo

This paper presents the results of an application of the semivariogram textural classifier to SIR-B data. Ford and Casey (1988) performed a visual interpretation of a SIR-B image of a tropical rain forest in Borneo in which they recognized and mapped three units of forest canopy (coastal lowland forest, tidal forest and swamp) and two units of open areas (clearcut and wetland). In this study the same image is classified using the STC in an attempt to emulate their interpretation.

Miranda, F. P.↗
NASA NTRS2012

Contribution of National near Real Time MODIS Forest Maximum Percentage NDVI Change Products to the U.S. ForWarn System

This presentation reviews the development, integration, and testing of Near Real Time (NRT) MODIS forest % maximum NDVI change products resident to the USDA Forest Service (USFS) ForWarn System. ForWarn is an Early Warning System (EWS) tool for detection and tracking of regionally evident forest change, which includes the U.S. Forest Change Assessment Viewer (FCAV) (a publically available on-line geospatial data viewer for visualizing and assessing the context of this apparent forest change). NASA Stennis Space Center (SSC) is working collaboratively with the USFS, ORNL, and USGS to contribute MODIS forest change products to ForWarn. These change products compare current NDVI derived from expedited eMODIS data, to historical NDVI products derived from MODIS MOD13 data. A new suite of forest change products are computed every 8 days and posted to the ForWarn system; this includes three different forest change products computed using three different historical baselines: 1) previous year; 2) previous three years; and 3) all previous years in the MODIS record going back to 2000. The change product inputs are maximum value NDVI that are composited across a 24 day interval and refreshed every 8 days so that resulting images for the conterminous U.S. are predominantly cloud-free yet still retain temporally relevant fresh information on changes in forest canopy greenness. These forest change products are computed at the native nominal resolution of the input reflectance bands at 231.66 meters, which equates to approx 5.4 hectares or 13.3 acres per pixel. The Time Series Product Tool, a MATLAB-based software package developed at NASA SSC, is used to temporally process, fuse, reduce noise, interpolate data voids, and re-aggregate the historical NDVI into 24 day composites, and then custom MATLAB scripts are used to temporally process the eMODIS NDVIs so that they are in synch with the historical NDVI products. Prior to posting, an in-house snow mask classification product is computed for the current compositing period and integrated into the change images to account for snow related NDVI drops. The supplemental snow classification product was needed because other available QA cloud/snow mask typically underestimates snow cover. MODIS true and false color composites were also computed from eMODIS reflectance data and the true color RGBs are also posted on ForWarn?s FCAV; this data is used for assessing apparent occasional quality issues on the change products due to residual unmasked cloud cover. New forest change products are posted with typical latencies of 1-2 days after the last input eMODIS data collection date for a given 24 day compositing period.

Spruce, Joseph P.↗
NASA NTRS1993

Leaf Areas And Spectral Properties Of Slash Pine

NASA technical memorandum describes experiments to test feasibility of estimating seasonal leaf areas of forest canopies from spectral radiances measured by remote instruments. Accurate estimates of seasonal leaf areas of forests necessary for studies of seasonal exchanges of energy between forest canopies and atmosphere. Potential use of remote sensing in estimating seasonal changes in leaf area index (LAI).

Curran, Paul J.↗