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NASA NTRS2010

Resilience of Alaska's Boreal Forest to Climatic Change

This paper assesses the resilience of Alaska s boreal forest system to rapid climatic change. Recent warming is associated with reduced growth of dominant tree species, plant disease and insect outbreaks, warming and thawing of permafrost, drying of lakes, increased wildfire extent, increased postfire recruitment of deciduous trees, and reduced safety of hunters traveling on river ice. These changes have modified key structural features, feedbacks, and interactions in the boreal forest, including reduced effects of upland permafrost on regional hydrology, expansion of boreal forest into tundra, and amplification of climate warming because of reduced albedo (shorter winter season) and carbon release from wildfires. Other temperature-sensitive processes for which no trends have been detected include composition of plant and microbial communities, long-term landscape-scale change in carbon stocks, stream discharge, mammalian population dynamics, and river access and subsistence opportunities for rural indigenous communities. Projections of continued warming suggest that Alaska s boreal forest will undergo significant functional and structural changes within the next few decades that are unprecedented in the last 6000 years. The impact of these social ecological changes will depend in part on the extent of landscape reorganization between uplands and lowlands and on policies regulating subsistence opportunities for rural communities.

Chapin, F. S., III↗

NASA NTRS2005

Effects of artificial defoliation of pines on the structure and physiology of the soil fungal community of a mixed pine-spruce forest

Loss of photosynthetic area can affect soil microbial communities by altering the availability of fixed carbon. We used denaturing gradient gel electrophoresis (DGGE) and Biolog filamentous-fungus plates to determine the effects of artificial defoliation of pines in a mixed pine-spruce forest on the composition of the fungal community in a forest soil. As measured by DGGE, two fungal species were affected significantly by the defoliation of pines (P < 0.001); the frequency of members of the ectomycorrhizal fungus genus Cenococcum decreased significantly, while the frequency of organisms of an unidentified soil fungus increased. The decrease in the amount of Cenococcum organisms may have occurred because of the formation of extensive hyphal networks by species of this genus, which require more of the carbon fixed by their host, or because this fungus is dependent upon quantitative differences in spruce root exudates. The defoliation of pines did not affect the overall composition of the soil fungal community or fungal-species richness (number of species per core). Biolog filamentous-fungus plate assays indicated a significant increase (P < 0.001) in the number of carbon substrates utilized by the soil fungi and the rate at which these substrates were used, which could indicate an increase in fungal-species richness. Thus, either small changes in the soil fungal community give rise to significant increases in physiological capabilities or PCR bias limits the reliability of the DGGE results. These data indicate that combined genetic and physiological assessments of the soil fungal community are needed to accurately assess the effect of disturbance on indigenous microbial systems.

Pinus/growth & development/physiology↗

NASA NTRS2010

Mapping Successional Stages in a Wet Tropical Forest Using Landsat ETM+ and Forest Inventory Data

In this study, we test whether an existing classification technique based on the integration of Landsat ETM+ and forest inventory data enables detailed characterization of successional stages in a wet tropical forest site. The specific objectives were: (1) to map forest age classes across the La Selva Biological Station in Costa Rica; and (2) to quantify uncertainties in the proposed approach in relation to field data and existing vegetation maps. Although significant relationships between vegetation height entropy (a surrogate for forest age) and ETM+ data were detected, the classification scheme tested in this study was not suitable for characterizing spatial variation in age at La Selva, as evidenced by the error matrix and the low Kappa coefficient (12.9%). Factors affecting the performance of the classification at this particular study site include the smooth transition in vegetation structure between intermediate and advanced successional stages, and the low sensitivity of NDVI to variations in vertical structure at high biomass levels.

forest structure↗

NASA NTRS2026

Benchmarking Bayesian Optimization Frameworks and Acquisition Strategies for Materials Discovery and Autonomous Laboratories

Bayesian optimization (BO) can accelerate materials discovery by guiding expensive experiments toward the most promising processing conditions. We systematically compare five BO surrogate and framework combinations (Gaussian processes in Ax, Gaussian processes and Monte-Carlo neural networks in BayBE, random forests in Lolopy, and tree-structured Parzen (TPE) estimators in Hyperopt) on three benchmarks that mimic common materials design tasks (a discrete solid-electrolyte composition space, a hybrid discrete/continuous laminate-composite design problem solved with micromechanics modeling, and the continuous Ishigami analytic function which is a standard optimization benchmark). Each BO surrogate is paired with posterior mean, probability of improvement, and expected improvement acquisition functions and run for 100 trials from randomized initial samples with uniform random search providing a control. Across five random seeds per setting, BayBE’s Gaussian-process surrogate with expected improvement consistently reached ≥95 % of the known optimum in the fewest evaluations, while Lolopy’s random forest matched or exceeded GP performance on purely categorical or mixed spaces at a higher computational cost. Posterior mean alone often stagnated at local optima, underscoring the need for exploration, whereas probability and expected improvement balanced exploration and exploitation leading to better optimization in fewer trials. Execution times ranged from milliseconds for TPE to minutes for neural-network and random-forest surrogates. These results establish baseline expectations for BO in automated materials laboratories and highlight expected improvement with Gaussian processes as a reliable first choice, with random forests offering a strong alternative when categorical variables dominate. The benchmark suite and code are released to facilitate future surrogate, acquisition, and constraint-handling research in data-driven materials optimization.

Bayesian optimization↗

NASA NTRS1986

Multiple incidence angle SIR-B experiment over Argentina Mapping of forest units

Multiple incidence angle SIR-B data of the Cordon la Grasa region of the Chubut Province of Argentina are used to discriminate various forest types by their relative brightness versus incidence angle signatures. The region consists of several species of Nothofagas which change in canopy structure with elevation, slope, and exposure. In general, the factors that appear to impact the radar response most are canopy structure, density, and ground cover (presence or absence of dead trunks and branches in particular). The results of this work indicate that (1) different forest species, and structures of a single species, may be discriminated using multiple incidence angle radar imagery and (2) it is essential to consider the variation in backscatter due to incidence angle when analyzing the comparing data collected at varying frequencies and polarizations.

Cimino, J.↗

NASA NTRS1999

The Laser Vegetation Imaging Sensor (LVIS): A Medium-Altitude, Digitization-Only, Airborne Laser Altimeter for Mapping Vegetation and Topography

The Laser Vegetation Imaging Sensor (LVIS) is an airborne, scanning laser altimeter designed and developed at NASA's Goddard Space Flight Center. LVIS operates at altitudes up to 10 km above ground, and is capable of producing a data swath up to 1000 m wide nominally with 25 m wide footprints. The entire time history of the outgoing and return pulses is digitized, allowing unambiguous determination of range and return pulse structure. Combined with aircraft position and attitude knowledge, this instrument produces topographic maps with decimeter accuracy and vertical height and structure measurements of vegetation. The laser transmitter is a diode-pumped Nd:YAG oscillator producing 1064 nm, 10 nsec, 5 mJ pulses at repetition rates up to 500 Hz. LVIS has recently demonstrated its ability to determine topography (including sub-canopy) and vegetation height and structure on flight missions to various forested regions in the U.S. and Central America. The LVIS system is the airborne simulator for the Vegetation Canopy Lidar (VCL) mission (a NASA Earth remote sensing satellite due for launch in 2000), providing simulated data sets and a platform for instrument proof-of-concept studies. The topography maps and return waveforms produced by LVIS provide Earth scientists with a unique data set allowing studies of topography, hydrology, and vegetation with unmatched accuracy and coverage.

Blair, J. Bryan↗

NASA NTRS2021

Cutting out the Middleman: Calibrating and Validating a Dynamic Vegetation Model (ED2-PROSPECT5) Using Remotely Sensed Surface Reflectance

Canopy radiative transfer is the primary mechanism by which models relate vegetation composition and state to the surface energy balance, which is important to light- and temperature-sensitive plant processes as well as understanding land–atmosphere feedbacks. In addition, certain parameters (e.g., specific leaf area, SLA) that have an outsized influence on vegetation model behavior can be constrained by observations of shortwave reflectance, thus reducing model predictive uncertainty. Importantly, calibrating against radiative transfer outputs allows models to directly use remote sensing reflectance products without relying on highly derived products (such as MODIS leaf area index) whose assumptions may be incompatible with the target vegetation model and whose uncertainties are usually not well quantified. Here, we created the EDR model by coupling the two-stream representation of canopy radiative transfer in the Ecosystem Demography model version 2 (ED2) with a leaf radiative transfer model (PROSPECT-5) and a simple soil reflectance model to predict full-range, high-spectral-resolution surface reflectance that is dependent on the underlying ED2 model state. We then calibrated this model against estimates of hemispherical reflectance (corrected for directional effects) from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and survey data from 54 temperate forest plots in the northeastern United States. The calibration significantly reduced uncertainty in model parameters related to leaf biochemistry and morphology and canopy structure for five plant functional types. Using a single common set of parameters across all sites, the calibrated model was able to accurately reproduce surface reflectance for sites with highly varied forest composition and structure. However, the calibrated model's predictions of leaf area index (LAI) were less robust, capturing only 46 % of the variability in the observations. Comparing the ED2 radiative transfer model with another two-stream soil–leaf–canopy radiative transfer model commonly used in remote sensing studies (PRO4SAIL) illustrated structural errors in the ED2 representation of direct radiation backscatter that resulted in systematic underestimation of reflectance. In addition, we also highlight that, to directly compare with a two-stream radiative transfer model like EDR, we had to perform an additional processing step to convert the directional reflectance estimates of AVIRIS to hemispherical reflectance (also known as “albedo”). In future work, we recommend that vegetation models add the capability to predict directional reflectance, to allow them to more directly assimilate a wide range of airborne and satellite reflectance products. We ultimately conclude that despite these challenges, using dynamic vegetation models to predict surface reflectance is a promising avenue for model calibration and validation using remote sensing data.

Alexey N Shiklomanov↗

NASA NTRS2010

Complex Spatial Structure in a Population of Didymopanax pittieri, A Tree of Wind-Exposed Lower Montane Rain Forest

Didymopanax pittieri is a common shade-intolerant tree colonizing treefall gaps in the elfin forests on windswept ridgecrests in the lower montane rain forests of the Cordillera de Tilarain, Costa Rica. All D. pittieri taller than > 0.5 m in a 5.2-ha elfin forested portion of a gridded study watershed in the Monteverde Cloud Forest Preserve were located, mapped, and measured. This local population of D. pittieri is spatially inhomogeneous, in that density increases with increasing wind exposure; D. pittieri are more abundant near ridge crests than lower on windward slopes. The important and ubiquitous phenomenon of spatial inhomogeneity in population density is addressed and corrected for in spatial analyses by the application of the inhomogeneous version of Ripley's K. The spatial patterns of four size classes of D. pittieri (<5 cm dbh, 5-10 cm dbh, 10-20 cm dbh, and> 20 cm dbh) were investigated. Within the large-scale trend in density driven by wind exposure, D. pittieri saplings are clumped at the scale of treefall gaps and at the scale of patches of aggregated gaps. D. pittieri 5-10 cm dbh are randomly distributed, apparently due to competitive thinning of sapling clumps during the early stages of gap-phase regeneration. D. pittieri larger than 10 cm dbh are overdispersed at a scale larger than that of patches of gaps. Natural disturbance can influence the distribution of shade intolerant tree populations at several different spatial scales, and can have discordant effects at different life history stages.

Lawton, Robert M.↗

NASA NTRS1993

Turbulent heat transfer from a sparsely vegetated surface - Two-component representation

The conventional calculation of heat fluxes from a vegetated surface involving the coefficient of turbulent heat transfer which increases logarithmically with surface roughness, is inappropriate such highly structured surfaces as desert scrub or open forest. An approach is developed here for computing sensible heat flux from sparsely vegetated surfaces, where the absorption of insolation and the transfer of absorbed heat to the atmosphere are calculated separately for the plants and for the soil. This approach is applied to a desert-scrub surface in the northern Sinai, for which the turbulent transfer coefficient of sensible heat flux from the plants is much larger than that from the soil below, as shown by an analysis of plant, soil, and air temperatures. The plant density is expressed as the sum of products (plant-height) x (plant-diameter) of plants per unit horizontal surface area. The solar heat absorbed by the plants is assumed to be transferred immediately to the airflow. The effective turbulent transfer coefficient k(g-eff) for sensible heat from the desert-scrub/soil surface computed under this assumption increases sharply with increasing solar zenith angle, as the plants absorb a greater fraction of the incoming irradiation. The surface absorptivity (the coalbedo) also increases sharply with increasing solar zenith angle, and thus the sensible heat flux from such complex surfaces is a much broader function of time of day than when computed under constant k(g-eff) and constant albedo assumptions.

Otterman, J.↗

NASA NTRS1990

High performance pipelined multiplier with fast carry-save adder

A high-performance pipelined multiplier is described. Its high performance results from the fast carry-save adder basic cell which has a simple structure and is suitable for the Gate Forest semi-custom environment. The carry-save adder computes the sum and carry within two gate delay. Results show that the proposed adder can operate at 200 MHz for a 2-micron CMOS process; better performance is expected in a Gate Forest realization.

Wu, Angus↗

NASA NTRS1996

The HI Environment of Nearby Lyman-alpha Absorbers

We present the results of a VLA and WSRT search for H I emission from the vicinity of seven nearby clouds, which were observed in Ly-alpha absorption with HST toward Mrk 335, Mrk 501, and PKS 2155-304. Around the absorbers, we searched a volume of 4O' x 40' x 1000 km/s; for one of the absorbers we probed a velocity range of only 600 km/s. The H I mass sensitivity (5 sigma) very close to the lines of sight varies from 5 x 10(exp 6) solar mass at best to 5 x 10(exp 8) solar mass at worst. We detected H I emission in the vicinity of four out of seven absorbers. The closest galaxy we find to the absorbers is a small dwarf galaxy at a projected distance of 68 h(exp -1) kpc from the sight line toward Mrk 335. This optically uncataloged galaxy has the same velocity (V = 1970 km/s) as one of the absorbers, is fainter than the SMC, and has an H I mass of only 4 x 10(exp 7) solar mass. We found a somewhat more luminous galaxy at exactly the velocity (V = 5100 km/s) of one of the absorbers toward PKS 2155-304 at a projected distance of 230 h(exp -1) kpc from the sight line. Two other, stronger absorbers toward PKS 2155-304 at V approx. 17,000 km/s appear to be associated with a loose group of three bright spiral galaxies, at projected distances of 300 to 600 h(exp -1) kpc. These results support the conclusions emerging from optical searches that most nearby Ly-alpha forest clouds trace the large-scale structures outlined by the optically luminous galaxies, although this is still based on small-number statistics. We do not find any evidence from the H I distribution or kinematics that there is a physical association between an absorber and its closest galaxy. While the absorbing clouds are at the systemic velocity of the galaxies, the H I extent of the galaxies is fairly typical, and at least an order of magnitude smaller than the projected distance to the sight line at which the absorbers are seen. On the other hand, we also do not find evidence against such a connection. In total, we detected H I emission from five galaxies, of which two were previously uncataloged and one did not have a known redshift. No H I emission was detected from the vicinity of the two absorbers, which are located in a void and a region of very low galaxy density; but the limits are somewhat less stringent than for the other sight lines. These results are similar to what has been found in optically unbiased H I surveys. Thus, presence of Ly-alpha absorbers does not significantly alter the H I detection rate in their environment.

VanGorkom, J. H.↗

NASA NTRS2011

Canopy Spectral Invariants. Part 1: A New Concept in Remote Sensing of Vegetation

The concept of canopy spectral invariants expresses the observation that simple algebraic combinations of leaf and canopy spectral reflectance become wavelength independent and determine two canopy structure specific variables the recollision and escape probabilities. These variables specify an accurate relationship between the spectral response of a vegetation canopy to incident solar radiation at the leaf and the canopy scale. They are sensitive to important structural features of the canopy such as forest cover, tree density, leaf area index, crown geometry, forest type and stand age. This paper presents the mathematical basis of the concept which is linked to eigenvalues and eigenvectors of the three-dimensional radiative transfer equation.

Knyazikhin, Yuri↗

NASA NTRS2020

Mapping tree canopy cover and canopy height with L-band SAR using LiDAR data and Random Forests

Light detection and ranging (LiDAR) data can provide direct measurements of vegetation structures but are limited by the sparse spatial coverage. Polarimetric synthetic aperture radar (SAR) can perform large-scale high-resolution mapping without weather constraints but the information about vegetation and ground subsurface are mixed in the backscatter data. In this paper, we adopted the Random Forests algorithm to train an upscaling function using tree canopy cover (TCC) and canopy height model (CHM) derived from Goddard’s LiDAR, Hyperspectral and Thermal Imager (G-LiHT) data. The regression model is then applied to the L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data acquired during the 2017 Arctic-Boreal Vulnerability Experiment (ABoVE) airborne campaign to map the TCC and CHM over the Delta Junction area in interior Alaska.

Moghaddam, Mahta↗

NASA NTRS2021

Estimating Bare Earth in Sparse Boreal Forests With WorldView Stereo Imagery

Circumboreal forests are currently experiencing rapid climate warming which is altering their structure, productivity, and status as a carbon sink. Very-high resolution (VHR, <2 m) stereo derived digital surface models are available to monitor these forests, but, a similar resolution digital terrain model (DTM) is required to extract information about tree height, which is often used to estimate carbon content. To our knowledge, no openly available VHR DTM currently exists. To address this need, we developed approaches to extract DTMs by filtering VHR stereo point clouds (PCs) in sparse canopies of Alaska. Our evaluation consisted of two stereo processing methods with three PC search radii, at six different tree canopy cover (TCC) intervals. We found VHR DTMs were robust for estimating bare ground at TCC intervals less than 40% with vertical errors <1.6 m using airborne small footprint light detection and ranging (LiDAR) as reference.

Christopher S R Neigh↗

NASA NTRS2021

Estimating Bare Earth in Sparse Boreal Forests With WorldView Stereo Imagery

Christopher S. R. Neigh↗

NASA NTRS1975

Agriculture, forestry, range, and soils, chapter 2, part C

The feasibility of using microwave systems in agriculture, forestry, range, and soil moisture measurements was studied. Theory and preliminary results show the feasibility of measuring moisture status in the soil. For vegetational resources, crop identification for inventory and for yield and production estimates is most feasible. Apart from moisture- and water-related phenomena, microwave systems are also used to record structural and spatial data related to crops and forests.

Source record↗

NASA NTRS1987

Atmospheric surface and boundary layers of the Amazon Basin

Three phases of work were performed: design of and preparation for the Amazon Boundary Layer Experiment (ABLE 2-A); execution of the ABLE 2-A field program; and analysis of the ABLE 2-A data. Three areas of experiment design were dealt with: surface based meteorological measurements; aircraft missions; and project meteorological support. The primary goal was to obtain a good description of the structure of the atmosphere immediately above the rain forest canopy (top of canopy to a few thousand meters), to describe this region during the growing daytime phase of the boundary layer; and to examine the nighttime stratified state. A secondary objective was to examine the role that deep convective storms play in the vertical transport of heat, water vapor, and other trace gases. While significant progress was made, much of the analysis remains to be done.

Garstang, Michael↗

NASA NTRS1999

Mapping Vegetation Structure in Kakadu National Park: An AIRSAR and GIS Application in Conservation

Airborne Synthetic Aperture Radar (AIRSAR) data were used to map vegetation structure in Kakadu National Park Australia as part of the PACRIM project. SAR data were co-registered with Landsat TM, aerial photos, and map data in a geographic information system for a small test area consisting of mangrove, floodplain grasslands, lowland tropical evergreen forest and upland mixed deciduous and evergreen tropical forest near the South Alligator River. Landsat (Thematic Mapper) TM very clearly showed the floristic composition and burn scars from the previous years fires and the AIRSAR data provided a profile of vegetation structure. Extensive field data on vegetation species composition and structure were collected across a series of transects in cooperation with a survey of avifauna in an effort to link the habitat edge structure with bird species responses. A test site was found that contained two types of habitat edges: 1) A structure specific edge - characterized by the appearance of a very strong structural change in the forest canopy occurring in the absence of a substantial turnover in floristics. 2) Floristic edge - a sharp transition in vegetation genetic composition with a mixed set of structural changes. Specific polarization combinations were selected that were highly correlated to a set of desired structural parameters found in the field data. Classification routines were employed to group radar pixels into 3 structural classes based on: the Surface Area to Volume ratio (SA/V) of the stems, the SA/V of the branches, and the leaf area index of the canopy. Separate canopy structure maps were then entered into the GIS and bird responses were observed relative to the classes and their boundaries. Follow-on work will consist of extending this approach to neighboring areas, generating structure maps, predicting bird responses across the edges, and make accuracy assessments.

Imhoff, Marc L.↗