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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Amazon Forests Maintain Consistent Canopy Structure and Greenness During the Dry Season

The seasonality of sunlight and rainfall regulates net primary production in tropical forests. Previous studies have suggested that light is more limiting than water for tropical forest productivity, consistent with greening of Amazon forests during the dry season in satellite data.We evaluated four potential mechanisms for the seasonal green-up phenomenon, including increases in leaf area or leaf reflectance, using a sophisticated radiative transfer model and independent satellite observations from lidar and optical sensors. Here we show that the apparent green up of Amazon forests in optical remote sensing data resulted from seasonal changes in near-infrared reflectance, an artefact of variations in sun-sensor geometry. Correcting this bidirectional reflectance effect eliminated seasonal changes in surface reflectance, consistent with independent lidar observations and model simulations with unchanging canopy properties. The stability of Amazon forest structure and reflectance over seasonal timescales challenges the paradigm of light-limited net primary production in Amazon forests and enhanced forest growth during drought conditions. Correcting optical remote sensing data for artefacts of sun-sensor geometry is essential to isolate the response of global vegetation to seasonal and interannual climate variability.

dry season↗
NASA NTRS1986

Comparison of leaf and canopy reflectance of subarctic forests

Near-surface and aerial reflectance of foliage and canopies of subarctic forests were measured in central Alaska near Fairbanks. Bi-directional and hemispherical radiometric data were recorded over wavelengths ranging from 0.285 to 2.8 microns with emphasis on Landsat TM (Thematic Mapper) bands. Comparison of near-surface and aerial data indicates that the canopy of some species such as black spruce and aspen have reflectance values similar to their respective foliage. Other species such as birch have large differences. Canopy structure and understory vegetation appear to be the primary factors that control whether the reflectance of canopy and foliage are similar or different. The results suggest that radiation reflected from the canopy of some forest species will be close to laboratory measurements of foliage after atmospheric corrections.

Dean, K. G.↗
NASA NTRS2018

El Nino Drought Increased Canopy Turnover in Amazon Forests

Amazon droughts, including the 2015-2016 El Ni~no, may reduce forest net primary productivityand increase canopy tree mortality, thereby altering both the short- and the longtermnet forest carbon balance. Given the broad extent of drought impacts, inventory plots oreddy flux towers may not capture regional variability in forest response to drought. We used multi-temporal airborne Lidar data and field measurements of coarse woodydebris to estimate patterns of canopy turnover and associated carbon losses in intact and fragmentedforests in the central Brazilian Amazon between 2013-2014 and 2014-2016. Average annualized canopy turnover rates increased by 65% during the drought period inboth intact and fragmented forests. The average size and height of turnover events was similarfor both time intervals, in contrast to expectations that the 2015-2016 El Ni~no droughtwould disproportionally affect large trees. Lidar biomass relationships between canopyturnover and field measurements of coarse woody debris were modest (R2 0.3), given similarcoarse woody debris production and Lidar-derived changes in canopy volume from singletree and multiple branch fall events. Our findings suggest that El Ni~no conditions accelerated canopy turnover in central Amazonforests, increasing coarse woody debris production by 62% to 1.22 Mg C ha1(exp) yr1(exp) indrought years.

ecosystem models↗
NASA NTRS1995

Studies of microwave scattering and canopy architecture for boreal forests

This is an annual report on the project titled 'Study of Microwave Scattering and Canopy Architecture for Boreal Forests.' The objectives of our work are to study the interaction of microwave signals with vegetation components and to determine the radar's ability to provide accurate estimates of biophysical parameters such as biomass. Our research is aimed at refining the current microwave models and using these improvements to facilitate more accurate interpretations of SAR (synthetic aperture radar) imagery.

Lockhart, G. Lance↗
NASA NTRS1995

Dynamics and pattern of a managed coniferous forest landscape in Oregon

We examined the process of fragmentation in a managed forest landscape by comparing rates and patterns of disturbance (primarily clear-cutting) and regrowth between 1972 and 1988 using Landsat imagery. A 2589-km(exp 2) managed forest landscape in western Oregon was classified into two forest types, closed-canopy conifer forest (CF) (typically, greater than 60% conifer cover) and other forest and nonforest types (OT) (typically, less than 40 yr old or deciduous forest). The percentage of CF declined from 71 to 58% between 1972 and 1988. Declines were greatest on private land, least in wilderness, and intermediate in public nonwilderness. High elevations (greater than 914 m) maintained a greater percentage of CF than lower elevations (less than 914 m). The percentage of the area at the edge of the two cover types increased on all ownerships and in both elevational zones, whereas the amount of interior habitat (defined as CF at least 100 m from OT) decreased on all ownerships and elevational zones. By 1988 public lands contained approximately 45% interior habitat while private lands had 12% interior habitat. Mean interior patch area declined from 160 to 62 ha. The annual rate of disturbance (primarily clear-cutting) for the entire area including the wilderness was 1.19%, which corresponds to a cutting rotation of 84 yr. The forest landscape was not in a steady state or regulated condition which is not projected to occur for at least 40 yr under current forest plans. Variability in cutting rates within ownerships was higher on private land than on nonreserve public land. However, despite the use of dispersed cutting patterns on public land, spatial patterns of cutting and remnant forest patches were nonuniform across the entire public ownership. Large remaining patches (less than 5000 ha) of contiguous interior forest were restricted to public lands designated for uses other than timber production such as wilderness areas and research natural areas.

Spies, Thomas A.↗
NASA NTRS1983

A correlation analysis of percent canopy closure versus TMS spectral response for selected forest sites in the San Juan National Forest, Colorado

The correlation of canopy closure with the signal response of individual thematic mapper simulator (TMS) bands for selected forest sites in the San Juan National Forest, Colorado was investigated. Ground truth consisted of a photointerpreted determination of percent canopy closure of 0 to 100 percent for 32 sites. The sites selected were situated on plateaus at an elevation of approximately 3 km with slope or = 10 percent. The predominant tree species were ponderosa pine and aspen. The mean TMS response per band per site was calculated from data acquired by aircraft during mid-September, 1981. A correlation analysis of TMS response vs. canopy closure resulted in the following correlation coefficients for bands 1 through 7, respectively: -0.757, -0.663, -0.666, -0.088, -0.797, -0.763. Two model regressions were applied to the TMS data set to create a map of predicted percent forest canopy closure for the study area. Results indicated percent predictive accuracies of 71, 74, and 57 for percent canopy closure classes of 0-25, 25-75, and 75-100, respectively.

Butera, M. K.↗
NASA NTRS1995

Determining coniferous forest cover and forest fragmentation with NOAA-9 advanced very high resolution radiometer data

NOAA-9 satellite data from the Advanced Very High Resolution Radiometer (AVHRR) were used in conjunction with Landsat Multispectral Scanner (MSS) data to determine the proportion of closed canopy conifer forest cover in the Cascade Range of Oregon. A closed canopy conifer map, as determined from the MSS, was registered with AVHRR pixels. Regression was used to relate closed canopy conifer forest cover to AVHRR spectral data. A two-variable (band) regression model accounted for more variance in conifer cover than the Normalized Difference Vegetation Index (NDVI). The spectral signatures of various conifer successional stages were also examined. A map of Oregon was produced showing the proportion of closed canopy conifer cover for each AVHRR pixel. The AVHRR was responsive to both the percentage of closed canopy conifer cover and the successional stage in these temperate coniferous forests in this experiment.

Ripple, William J.↗
NASA NTRS2016

Morton et al. Reply

Multiple mechanisms could lead to up-regulation of dry-season photosynthesis in Amazon forests, including canopy phenology and illumination geometry. We specifically tested two mechanisms for phenology-driven changes in Amazon forests during dry-season months, and the combined evidence from passive optical and lidar satellite data was incompatible with large net changes in canopy leaf area or leaf reflectance suggested by previous studies. We therefore hypothesized that seasonal changes in the fraction of sunlit and shaded canopies, one aspect of bidirectional reflectance effects in Moderate Resolution Imaging Spectroradiometer (MODIS) data, could alter light availability for dry-season photosynthesis and the photosynthetic capacity of Amazon forests without large net changes in canopy composition. Subsequent work supports the hypothesis that seasonal changes in illumination geometry and diffuse light regulate light saturation in Amazon forests. These studies clarify the physical mechanisms that govern light availability in Amazon forests from seasonal variability in direct and diffuse illumination. Previously, in the debate over light limitation of Amazon forest productivity, seasonal changes in the distribution of light within complex Amazon forest canopies were confounded with dry-season increases in total incoming photosynthetically active radiation. In the accompanying Comment, Saleska et al. do not fully account for this confounding effect of forest structure on photosynthetic capacity.

Morton, Douglas C.↗
NASA NTRS2019

Long-Term Impacts of Selective Logging on Amazon Forest Dynamics from Multi-Temporal Airborne LiDAR

Forest degradation is common in tropical landscapes, but estimates of the extent and duration of degradation impacts are highly uncertain. In particular, selective logging is a form of forest degradation that alters canopy structure and function, with persistent ecological impacts following forest harvest. In this study, we employed airborne laser scanning in 2012 and 2014 to estimate three-dimensional changes in the forest canopy and understory structure and aboveground biomass following reduced-impact selective logging in a site in Eastern Amazon. Also, we developed a binary classification model to distinguish intact versus logged forests. We found that canopy gap frequency was significantly higher in logged versus intact forests even after 8 years (the time span of our study). In contrast, the understory of logged areas could not be distinguished from the understory of intact forests after 6–7 years of logging activities. Measuring new gap formation between LiDAR acquisitions in 2012 and 2014, we showed rates 2 to 7 times higher in logged areas compared to intact forests. New gaps were spatially clumped with 76 to 89% of new gaps within 5 m of prior logging damage. The biomass dynamics in areas logged between the two LiDAR acquisitions was clearly detected with an average estimated loss of -4.14 +/- 0.76 MgC/hay. In areas recovering from logging prior to the first acquisition, we estimated biomass gains close to zero. Together, our findings unravel the magnitude and duration of delayed impacts of selective logging in forest structural attributes, confirm the high potential of airborne LiDAR multitemporal data to characterize forest degradation in the tropics, and present a novel approach to forest classification using LiDAR data.

Pinage, Ekena Rangel↗
NASA NTRS1994

Studies of microwave scattering and canopy architecture for boreal forests

Our primary objectives during the last year have been to develop a helicopter-borne radar system for measuring microwave backscatter from vegetation and to use this system to study the characteristics of backscatter from the boreal forest. Our research is aimed at refining the current microwave models and using these improvements for more accurate interpretation of SAR data. SAR data are very useful for monitoring the boreal forest region because of the microwave signal's ability to penetrate clouds and to see at night. Meeting these objectives involves several stages of development. The first stage is the design and implementation of a frequency-modulated continuous-wave (FM-CW) radar system with the capability of measuring backscatter at three frequencies and four polarizations at each frequency. These requirements necessitate a twelve-channel radar system. Using three frequencies is advantageous because it allows us to look at different parts of the canopy. For instance, the lower frequency signal penetrates deeper into the canopy and allows us to see the ground while the high frequency signal is scattered more by the leaves and needles and typically does not penetrate to the floor of the forest. We designed the radar starting with the antenna system. We then developed the intermediate frequency (IF) and radio frequency (RF) sections of the radar. Also, the need to collect data from twelve channels during each flight line presented a complex data acquisition problem that we solved by using a high-speed data acquisition board. After construction, the radar was tested at the lab. We performed extensive testing of the IF and RF systems of the radar during this time. Once we were satisfied with the operation of the radar it was shipped to Canada for use in the second intensive field campaign (IFC-2) from July 16 - August 8, 1994. During IFC-2, we collected backscatter data over the experimental sites in the southern study area (SSA). Additionally, we used a ground-based step-frequency radar to measure the reflection coefficient of the forest floor at the old jack pine (OJP) and young jack pine (YJP) sites. The ground-based radar data have been processed and a frew examples are included in this report. we are currently processing the helicopter-borne radar data.

Lockhart, G. Lance↗
NASA NTRS1999

Geoscience Applications of Airborne and Spaceborne Lidar Altimetry

Recent advances in lidar altimetry technology have enabled new methods to describe the vertical structure of the Earth's surface with great accuracy. Application of these methods in several geoscience disciplines will be described. Airborne characterization of vegetation canopy structure will be illustrated, including a validation of lidar-derived Canopy Height Profiles for closed-canopy, broadleaf forests. Airborne detection of tectonic landforms beneath dense canopy will also be illustrated, with an application mapping active fault traces in the Puget Lowland of Washington state for earthquake hazard assessment purposes. Application of data from the first and second flights of the Shuttle Laser Altimeter will also be discussed in an assessment of global digital elevation model accuracy and error characteristics. Two upcoming space flight missions will be described, the Vegetation Canopy Lidar (VCL) and the Ice, Cloud and Land Elevation Mission (ICESat), which will provide comprehensive lidar altimeter observations of the Earth's topography and vegetation cover.

Harding David J.↗
NASA NTRS2024

Southern Indiana Ecological Conservation: Assessing Canopy Cover Dynamics and Forest Type Groupings in Southern Indiana to Inform Restoration Activities

As human influence continues to negatively impact natural habitats, timely assessment of ecosystem changes and restoration is critical to protect forest health and biodiversity. In our study, we focused on oak-hickory forests in southern Indiana. Oak-hickory forests were the dominant ecosystem dynamic in present-day Indiana for centuries until European colonization, which brought about fire suppression and, eventually, fire exclusion. Anthropogenic fire exclusion in this fire-adapted habitat led to the encroachment of mesic species, such as beech and maple trees. This process, commonly referred to as mesophication, was the focus of our study. Our team performed a feasibility study in using NASA Earth observations to support our end-user partners, Let the Sun Shine In and the US Forest Service, Hoosier National Forest, in their selection of oak-hickory restoration sites. To aid in our analysis of the forest dynamics of southern Indiana, our team used Landsat 5, 8, and 9 imageries, along with other ancillary datasets to create maps to illustrate areas that would most benefit from partners’ forest restoration and management practices. By constructing a Green Vegetation Fraction change map across our 39-year study period (1984-2023) to visualize the change in forest cover and creating a restoration suitability assessment map to reveal sites that met requirements for oak-hickory growth, we provided our partners with suitable site selection for restorative management and found that 3.3% of our entire study area and 4.4% of the Hoosier National Forest were deemed suitable. Our feasibility study benefits southern Indiana restoration by aiding our partners in efficiently selecting sites for prescribed burning, forest thinning, and other restoration management practices.

restoration↗
NASA NTRS2024

Extending the Utility of Space-Borne Snow Water Equivalent Observations Over Vegetated Areas With Data Assimilation

Snow is a vital component of the earth system, yet no snow-focused satellite remote sensing platform currently exists. In this study, we investigate how synthetic observations of snow water equivalent (SWE) representative of a synthetic aperture radar remote sensing platform could improve spatiotemporal estimates of snowpack. We use a fraternal twin observing system simulation experiment, specifically investigating how much snow simulated using widely used models and forcing data could be improved by assimilating synthetic observations of SWE. We focus this study across a 24° x 37° domain in the western USA and Canada, simulating snow at 250 m resolution and hourly time steps in water year 2019. We perform two data assimilation experiments, including (1) a simulation excluding synthetic observations in forests where canopies obstruct remote sensing retrievals and (2) a simulation inferring snow distribution in forested grid cells using synthetic observations from nearby canopy-free grid cells. Results found that, relative to a nature run, or assumed true simulation of snow evolution, assimilating synthetic SWE observations improved average SWE biases at maximum snowpack timing in shrub, grass, crop, bare-ground, and wetland land cover types from 14 %, to within 1 %. However, forested grid cells contained a disproportionate amount of SWE volume. In forests, SWE mean absolute errors at the time of maximum snow volume were 111 mm and average SWE biases were on the order of 150 %. Here the data assimilation approach that estimated forest SWE using observations from the nearest canopy-free grid cells substantially improved these SWE biases (18 %) and the SWE mean absolute error (27 mm). Simulations employing data assimilation also improved estimates of the temporal evolution of both SWE and runoff, even in spring snowmelt periods when melting snow and high snow liquid water content prevented synthetic SWE retrievals. In fact, in the Upper Colorado River region, melt-season SWE biases were improved from 63 % to within 1 %, and the Nash–Sutcliffe efficiency of runoff improved from −2.59 to 0.22. These results demonstrate the value of data assimilation and a snow-focused globally relevant remote sensing platform for improving the characterization of SWE and associated water availability.

Justin Pflug↗
DOE OSTI2023

Mapping foliar photosynthetic capacity in sub-tropical and tropical forests with UAS-based imaging spectroscopy: Scaling from leaf to canopy

Accurate understanding of the variability in foliar physiological traits across landscapes is critical to improve parameterization and evaluation of terrestrial biosphere models (TBMs) that seek to represent the response of terrestrial ecosystems to a changing climate. Numerous studies suggest imaging spectroscopy can characterize foliar biochemical and morphological traits at the canopy scale, but there is only limited evidence for retrieving canopy photosynthetic capacity (e.g., maximum carboxylation rate, V c,max and maximum electron transport rate, J max ). Moreover, the effect of canopy structure within forest communities on scaling up spectra-trait relationships from leaf to canopy level is not well known. To advance the spectra-trait approach and enable the estimation of key traits using remote sensing, we collected imaging spectroscopy data from an Unoccupied Aerial System (UAS) platform over two forest sites in China (a subtropical forest in Mt. Dinghu and a tropical rainforest in Xishuangbanna). At these sites, we also collected ground measurements of leaf spectra and traits, including biochemical (leaf nitrogen, phosphorus, chlorophyll, and water content), morphological (leaf mass per area, LMA) and physiological (V c,max25 and J max25 ) traits (n=135 tree-crowns from 42 species across two sites). Using a partial least-squares regression (PLSR) approach, we built and tested spectra-trait models with repeated cross-validation. The spectral models developed with leaf spectra were directly transferred to canopy spectra to evaluate the effect of canopy structure. Here we further applied canopy spectral models to map these traits at individual tree-crown scale. The results demonstrate that (1) UAS-based canopy spectra can be used to estimate V c,max (R 2 =0.55, nRMSE=11.79%), Jmax (R 2 =0.54, nRMSE=12.34%), and five additional foliar traits (R 2 =0.38-0.60, nRMSE=10.11-13.56%) at the tree-crown scale with demonstrated generalizability across two sites; (2) canopy structure strongly affects the spectratrait relationships from leaf to canopy level, but the effects vary considerably across foliar traits and cannot be well captured by the 4SAIL canopy radiative transfer model. UAS-based imaging spectroscopy maps large variability in all foliar traits (including physiological traits) with spatially explicit information, reproducing the field-observed inter- and intra-specific variations. These results demonstrate the capability of using UAS-based imaging spectroscopy for characterizing the variability of foliar physiological traits at individual tree-crown scale over forest landscapes and highlight the similar generalizability but different biophysical mechanisms underlying spectra-trait relationships at leaf and canopy levels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

AmeriFlux FLUXNET-1F US-MtB Mt Bigelow

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-MtB Mt Bigelow. This is the FLUXNET version of the carbon flux data for the site US-MtB Mt Bigelow produced by applying the standard ONEFlux (1F) software. Site Description - Western slope of Mt. Bigelow; 29 km NE of Tucson, AZ, USA; Mixed evergreen conifer forest; Average canopy height = 10 m; Summer monsoon; 30-m tower installed in 2002; Secondary forest re-established in the 1930s

Barron-Gafford, Greg [University of Arizona]↗
NASA NTRS2011

Applications of the BIOPHYS Algorithm for Physically-Based Retrieval of Biophysical, Structural and Forest Disturbance Information

Canopy reflectance model inversion using look-up table approaches provides powerful and flexible options for deriving improved forest biophysical structural information (BSI) compared with traditional statistical empirical methods. The BIOPHYS algorithm is an improved, physically-based inversion approach for deriving BSI for independent use and validation and for monitoring, inventory and quantifying forest disturbance as well as input to ecosystem, climate and carbon models. Based on the multiple-forward mode (MFM) inversion approach, BIOPHYS results were summarized from different studies (Minnesota/NASA COVER; Virginia/LEDAPS; Saskatchewan/BOREAS), sensors (airborne MMR; Landsat; MODIS) and models (GeoSail; GOMS). Applications output included forest density, height, crown dimension, branch and green leaf area, canopy cover, disturbance estimates based on multi-temporal chronosequences, and structural change following recovery from forest fires over the last century. Good correspondences with validation field data were obtained. Integrated analyses of multiple solar and view angle imagery further improved retrievals compared with single pass data. Quantifying ecosystem dynamics such as the area and percent of forest disturbance, early regrowth and succession provide essential inputs to process-driven models of carbon flux. BIOPHYS is well suited for large-area, multi-temporal applications involving multiple image sets and mosaics for assessing vegetation disturbance and quantifying biophysical structural dynamics and change. It is also suitable for integration with forest inventory, monitoring, updating, and other programs.

Peddle, Derek R.↗