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All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Recent Progress in Measuring and Modeling Patterns of Biomass and Soil Carbon Pools Across the Amazon Basin

Ever more detailed representations of above-ground biomass and soil carbon pools have been developed during the LBA project. Environmental controls such as regional climate, land cover history, secondary forest regrowth, and soil fertility are now being taken into account in regional inventory studies. This paper will review the evolution of measurement-extrapolation approaches, remote sensing, and simulation modeling techniques for biomass and soil carbon pools, which together help constrain regional carbon budgets and enhance in our understanding of uncertainty at the regional level.

Potter, Christopher↗
NASA NTRS2001

Tropospheric Ozone and Biomass Burning

This paper studies the significance of pyrogenic (e.g., biomass burning) emissions in the production of tropospheric ozone in the tropics associated with the forest and savanna fires in the African, South American, and Indonesian regions. Using aerosol index (Al) and tropospheric column ozone (TCO) time series from 1979 to 2000 derived from the Nimbus-7 and Earth Probe TOMS measurements, our study shows significant differences in the seasonal and spatial characteristics of pyrogenic emissions north and south of the equator in the African region and Brazil in South America. In general, they are not related to the seasonal and spatial characteristics of tropospheric ozone in these regions. In the Indonesian region, the most significant increase in TCO occurred during September and October 1997, following large-scale forest and savanna fires associated with the El Nino-induced dry season. However, the increase in TCO extended over most of the western Pacific well outside the burning region and was accompanied by a decrease in the eastern Pacific resembling a west-to-east dipole about the date-line. The net increase in TCO integrated over the tropical region between 15 deg N and 15 deg S was about 6-8 Tg (1 Tg = 10(exp 12) gm) over the mean climatological value of about 72 Tg. This increase is well within the range of interannual variability of TCO in the tropical region and does not necessarily suggest a photochemical source related to biomass burning. The interannual variability in TCO appears to be out of phase with the interannual variability of stratospheric column ozone (SCO). These variabilities seem to be manifestations of solar cycle and quasibiennial oscillations.

Chandra, Sushil↗
NASA NTRS1991

Assessment of regional biomass-soil relationships using vegetation indexes

The development of photosynthetic active biomass in different ecological conditions, as indicated by normalized difference vegetation indices (NDVIs) is compared by performing a stratified sampling (based on soil assocations) on data acquired over Indiana. Data from the NOAA-10 AVHRR were collected for the 1987 and 1988 growing seasons. An NDVI transformation was performed using the two optical bands of the sensor (0.58-0.68 microns and 0.72-1.10 microns). The NDVI is related to the amount of active photosynthetic biomass present on the ground. Samples of NDVI values over 45 fields representing eight soil associations throughout Indiana were collected to assess the effect of soil conditions and acquisition date on the spectral response of the vegetation, as shown by the NDVIs. Statistical analysis of results indicate that land-cover types (forest, forest/pasture, and crops), soil texture, and soil water-holding capacity have an important effect on vegetation biomass changes as measured by AVHRR data. Acquisition dates should be selected with condideration of the phenological stages of vegetation. Sampling of AVHRR data over extended areas should be stratified according to physiographic units rather than man-made boundaries. This will provide more homogeneous samples for statistical analysis.

Lozano-Garcia, D. Fabian↗
NASA NTRS1988

Effects of global atmospheric perturbations on forest ecosystems: Predictions of seasonal and cumulative effects

The physical effects of certain large events, such as giant impacts, explosive volcanism, or combined nuclear explosions, have the potential of inducing global catastrophes in our terrestrial environment. Such highly energetic events can inject substantial quantities of material into the atmosphere. In turn, this changes the amount of sunlight reaching the Earth's surface and modifies atmospheric temperatures to produce a wide range of global effects. One consequence is the introduction of serious stresses in both plants and animals throughout the Earth's biosphere. For example, recent studies predict that forest lands, crop lands, and range lands would suffer specific physical and biological degradations if major physical and chemical disruptions occurred in our atmosphere. Forests, which cover over 4 times 10 to the 9th power hectares (4 times 10 to the 7th power sq km) of our planet, or about 3 times the area now cultivated for crops, are critical to many processes in the biosphere. Forests contribute heavily to the production of atmospheric oxygen, supply the major volume of biomass, and provide a significant percentage of plant and animal habitats.

Tinus, R. W.↗
NASA NTRS2018

Improving Carbon Estimation of Large Tropical Trees by Linking Airborne Lidar Crown Size to Field Inventory

Quantifying tropical aboveground biomass (agb) is an outstanding challenge that requires knowledge on the 3D structure of forests. Recent studies suggest that the uncertainty in estimating agb of large trees is significantly reduced if tree height and crown size are accounted for in addition to the traditional trunk diameter and wood density. Due to the fact that field inventory techniques are not adapted to characterize the 3D forest structure, crown size metrics (e.g. height and radius) are commonly estimated as a function of trunk diameter using allometric models with limitations in explaining crown variability. Airborne lidar techniques have the potential for characterizing tree height and crown size but are not adapted to estimate trunk diameter, which is a strong predictor of agb. Here, we investigate the synergy of field inventory and airborne lidar techniques to characterize the forest structure by assessing the uncertainty introduced by the field-based allometric models in the estimation of agb at the tree-level. We focus in 1454 large individual trees (trunk diameter > 60 cm) located within the La Selva Biological Station for which we dispose of field observations (trunk diameter and wood density) and lidar derived metrics (tree height and crown radius). We show that the field-based allometric models overestimate tree height and underestimate crown radius. As a result, the allometric approach overestimates the tree-level agb in 0.8 Mg when considering the 1454 individuals and the errors can reach more than 50% of the agb of individual trees. These errors on the large trees agb highly impact on the plot-level results and then propagate to the estimation of carbon stocks at the regional and national-levels.

Clark, David↗
NASA NTRS2006

Processes Influencing Ozone Levels in Alaskan Forest Fires Plumes during Long-Range Transport over the North Atlantic

A case of long-range transport of a biomass burning plume from Alaska to Europe is analyzed using a Lagrangian approach. This plume was sampled several times in the free troposphere over North America, the North Atlantic and Europe by 3 different aircraft during the IGAC Lagrangian 2K4 experiment which was part of the ICARTT/ITOP measurement intensive in summer 2004. Measurements in the plume showed enhanced values of CO, VOCs and NOy, mainly in form of PAN. Observed O3 levels increased by 17 ppbv over 5 days. A photochemical trajectory model, CiTTyCAT, is used to examine processes responsible for the chemical evolution of the plume. The model was initialized with upwind data, and compared with downwind measurements. The influence of high aerosol loading on photolysis rates in the plume is investigated using in-situ aerosol measurements in the plume and lidar retrievals of optical depth as input into a photolysis code (Fast-J), run in the model. Significant impacts on photochemistry are found with a decrease of 18 percent in O3 production and 24 percent in O3 destruction over 5 days when including aerosols. The plume is found to be chemically active with large O3 increases attributed primarily to PAN decomposition during descent of the plume towards Europe. The predicted O3 changes are very dependent on temperature changes during transport, and also, on water vapor levels in the lower troposphere which can lead to O3 destruction. Simulation of mixing/dilution was necessary to reproduce observed pollutants level in the plume. Mixing was simulated using background concentrations from measurements in air masses in close proximity to the plume, and mixing timescales (averaging 6.25 days) were derived from CO changes. Observed and simulated O3/CO correlations in the plume are also compared in order to evaluate the photochemistry in the model. Observed slopes changed from negative to positive over 5 days. This change, which can be attributed largely to photochemistry, is well reproduced by multiple model runs even if slope values are slightly underestimated suggesting small underestimation of photochemical processes. The possible impact of this biomass burning plume on O3 levels in the Europe boundary layer is also examined by running the model for a further 5 days, and comparing with data collected at surface sites, such as Jungfraujoch, which showed small O3 increases and elevated CO levels. The model predicts significant changes in O3 over this 10 days due to photochemistry but the signal is largely lost due to the effects of dilution. However, measurement in several others BB plumes over Europe show that O3 impact of Alaskan fires can be punctually significant over Europe.

Real, E.↗
NASA NTRS2018

Quantifying Boreal Forest Structure and Composition Using UAV Structure from Motion

The vast extent and inaccessibility of boreal forest ecosystems are barriers to routine monitoring of forest structure and composition. In this research, we bridge the scale gap between intensive but sparse plot measurements and extensive remote sensing studies by collecting forest inventory variables at the plot scale using an unmanned aerial vehicle (UAV) and a structure from motion (SfM) approach. At 20 Forest Inventory and Analysis (FIA) subplots in interior Alaska, we acquired overlapping imagery and generated dense, 3D, RGB (red, green, blue) point clouds. We used these data to model forest type at the individual crown scale as well as subplot-scale tree density (TD), basal area (BA), and aboveground biomass (AGB). We achieved 85% cross-validation accuracy for five species at the crown level. Classification accuracy was maximized using three variables representing crown height, form, and color. Consistent with previous UAV-based studies, SfM point cloud data generated robust models of TD (r(sup 2) = 0.91), BA (r(sup 2) = 0.79), and AGB (r(sup 2) = 0.92), using a mix of plot- and crown-scale information. Precise estimation of TD required either segment counts or species information to differentiate black spruce from mixed white spruce plots. The accuracy of species-specific estimates of TD, BA, and AGB at the plot scale was somewhat variable, ranging from accurate estimates of black spruce TD (+/−1%) and aspen BA (−2%) to misallocation of aspen AGB (+118%) and white spruce AGB (−50%). These results convey the potential utility of SfM data for forest type discrimination in FIA plots and the remaining challenges to develop classification approaches for species-specific estimates at the plot scale that are more robust to segmentation error.

aboveground biomass↗
NASA NTRS1987

Spectrometric test of a linear array sensor

A spectroradiometer which measures spectral reflectivities and irradiance in discrete spectral channels was tested to determine the accuracy of its wavelength calibration. This sensor is a primary tool in the remote sensing investigations conducted on biomass at NASA's Goddard Space Flight Center. Measurements have been collected on crop and forest plants both in the laboratory and field with this radiometer to develop crop identification and plant stress remote sensing techniques. Wavelength calibration is essential for use in referencing the study measurements with those of other investigations and satellite remote sensor data sets. This calibration determines a wavelength vs channel address conversion which was found to have an RMS deviation of approximately half a channel, or 1.5 nm in the range from 360 to 1050 nm. A comparison of these results with those of another test showed an average difference of approximately 4 nm, sufficiently accurate for most investigative work.

Brown, Kenneth S.↗
NASA NTRS1988

The Amazon Boundary Layer Experiment (ABLE 2A) - Dry season 1985

The Amazon Boundary Layer Experiment (ABLE 2A) used data from aircraft, ground-based, and satellite platforms to characterize the chemistry and dynamics of the lower atmosphere over the Amazon Basin during the early-to-middle dry season, July and August 1985. This paper reports the conceptual framework and experimental approach used in ABLE 2A and serves as an introduction to the detailed papers which follow in this issue. The results of ABLE 2A demonstrate that isoprene, methane, carbon dioxide, nitric oxide, dimethylsulfide, and organic aerosol emissions from soils and vegetation play a major role in determining the chemical composition of the atmospheric mixed layer over undisturbed forest and wetland environments. As the dry season progresses, emissions from both local and distant biomass burning become an important source of carbon monoxide, nitric oxide and ozone in the atmosphere over the central Amazon Basin.

Harriss, R. C.↗
NASA NTRS1986

Satellite-derived leaf-area-index and vegetation maps as input to global carbon cycle models - A hierarchical approach

A hierarchical procedure for developing a leaf area index (LAI) map of deciduous boreal forests is studied. The collection of spectral reflectance data from the Boundary Waters Canoe area in Minnesota using helicopter-, high-altitude aircraft-, and Landsat-mounted spectral sensors is described. The relationship between LAI and biomass and the reflectance ratio is analyzed. The sensitivity of canopy reflectance in the visible and infrared to the LAI of the canopy for various boreal forest species is evaluated. The data reveal that Landsat data are useful for producing LAI maps of deciduous forest areas and the maps provide data which clarifies the function of vegetation in the global carbon cycle models.

Badhwar, G. D.↗
NASA NTRS2003

The Study of Biomass Emissions for Defining Radiative Forcing of Climate

Accurate quantification of the amounts of trace gases and particulate matter emitted from vegetation fires and other sources of biomass burning (agricultural waste and biofuels) on a regional and global basis is required by a number of users, including scientists studying a wide range of atmospheric processes, national governments who are required to report greenhouse gas emissions, and those interested in quantifying the sources of air pollution that affect human health at regional scales. Over the past decade, improvements in the ability to detect and map fires using a number of different satellite systems have been achieved, largely through efforts coordinated through working groups organized by the IGBP Data and Information System and Global Observation of Forest Cover (GOFC) projects. In addition, significant advances and improvement in or understanding of the emissions factors for biomass burning in different biomes has resulted through efforts by the Biomass Burning Experiment (BIBEX) organized through the International Global Atmospheric Chemistry project. A number of satellite-based fire data products have been generated, and a number of new products will shortly be available. These new data products will provide the basis for estimating emissions from biomass burning on a global basis. However, a number of issues remain concerning the availability of other data sets needed to generate these estimates. Recognizing these issues, the GOFC-Fire Satellite Validation Workshop (held in Lisbon, Portugal on 9-11 July 2001), recommended that a workshop focusing on Improving Global Estimates of Atmospheric Emissions from Biomass Burning be organized. This workshop was held from 17- 19 July 2002 on the campus of the University of Maryland, College Park, Maryland. This workshop served as the annual meeting of the GOFC/GOLD-Fire Program. The overall goals of the meeting were to review the information products generated from satellite imagery and other sources that are currently available for developing emission estimates from biomass burning, evaluate areas where improved or additional products would be beneficial, and recommend products for use by the atmospheric science community.

Penner, Joyce↗
NASA NTRS2021

Mangrove Carbon Stocks in Pongara National Park, Gabon

Mangroves are recognized for their valued ecosystem services to coastal areas, and the functional linkages between those services and ecosystem carbon stocks have been established. However, spatially explicit inventories are necessary to facilitate management and protection of mangroves, as well as providing a foundation for payment for ecosystem service programs such as REDD+. We conducted an inventory of carbon stocks in mangroves within Pongara National Park (PNP), Gabon using a stratified random sampling design based on forest canopy height derived from TanDEM-X remote sensing data. Ecosystem carbon pools, including aboveground and belowground biomass and necromass, and soil carbon to a depth of 2 m were assessed using measurements and samples from plots distributed among three canopy height classes within the park. There were two mangrove species within the inventory area in PNP, Rhizophora racemosa and R. harrisonii. R. harrisonii was predominant in the sparse, low-stature stands that dominated the west side of the park. In the east side of the park, both species occurred in tall-stature stands, with tree height often exceeding 30 m. Canopy height was an effective means to stratify the inventory area, as biomass was significantly different among the height classes. Despite those differences in aboveground biomass, the soil carbon density was not significantly different among height classes. Soils were the main component of the ecosystem carbon stock, accounting for over 84% of the total. The ecosystem carbon density ranged from 644 to 943 Mg C ha−1 among the three height classes. The ecosystem carbon stock within PNP is estimated to be 40,588 Gg C. The combination of pre-inventory information about stand conditions and their spatial distribution within the assessment area obtained from remote sensing data and a spatial decision support system were fundamental to implementing this relatively large-scale field inventory. This work exemplifies how mangrove carbon stocks can be quantified to augment national C reporting statistics, provide a baseline for projects involving monitoring, reporting and verification (i.e., MRV), and provide data on the forest composition and structure for sustainable management and conservation practices.

Carl C Trettin↗
NASA NTRS1981

State resource management and role of remote sensing

Remote sensing by satellite can provide valuable information to state officials when making decisions regarding resources management. Portions of California's investment for Prosperity program which seem likely candidates for remote sensing include: (1) surveying vegetation type, age, and density in forests and wildlife habitats; (2) controlling fires through chaparal management; (3) monitoring wetlands and measuring ocean biomass; (4) eliminating ground water overdraught; (5) locating crops in overdraught areas, assessing soil erosion and the areas of poorly drained soils and those affected by salt; (6) monitoring coastal lands and resources; (7) changes in landscapes for recreational purposes; (8) inventorying irrigated lands; (9) classifying ground cover; (10) monitoring farmland conversion; and (11) supplying data for a statewide computerized farmlands data base.

Johnson, H. D.↗
NASA NTRS1994

Effect of land use change on the carbon cycle in Amazon soils

The overall goal of this study was to provide a quantitative understanding of the cycling of carbon in the soils associated with deep-rooting Amazon forests. In particular, we wished to apply the understanding gained by answering two questions: (1) what changes will accompany the major land use change in this region, the conversion of forest to pasture? and (2) what is the role of carbon stored deeper than one meter in depth in these soils? To construct carbon budgets for pasture and forest soils we combined the following: measurements of carbon stocks in above-ground vegetation, root biomass, detritus, and soil organic matter; rates of carbon inputs to soil and detrital layers using litterfall collection and sequential coring to estimate fine root turnover; C-14 analyses of fractionated SOM and soil CO2 to estimate residence times; C-13 analyses to estimate C inputs to pasture soils from C-4 grasses; soil pCO2, volumetric water content, and radon gradients to estimate CO2 production as a function of soil depth; soil respiration to estimate total C outputs; and a model of soil C dynamics that defines SOM fractions cycling on annual, decadal, and millennial time scales.

Trumbore, Susan E.↗
NASA NTRS1993

Polarimetric radar data decomposition and interpretation

Significant efforts have been made to decompose polarimetric radar data into several simple scattering components. The components which are selected because of their physical significance can be used to classify SAR (Synthetic Aperture Radar) image data. If particular components can be related to forest parameters, inversion procedures may be developed to estimate these parameters from the scattering components. Several methods have been used to decompose an averaged Stoke's matrix or covariance matrix into three components representing odd (surface), even (double-bounce) and diffuse (volume) scatterings. With these decomposition techniques, phenomena, such as canopy-ground interactions, randomness of orientation, and size of scatters can be examined from SAR data. In this study we applied the method recently reported by van Zyl (1992) to decompose averaged backscattering covariance matrices extracted from JPL SAR images over forest stands in Maine, USA. These stands are mostly mixed stands of coniferous and deciduous trees. Biomass data have been derived from field measurements of DBH and tree density using allometric equations. The interpretation of the decompositions and relationships with measured stand biomass are presented in this paper.

Sun, Guoqing↗
NASA NTRS2018

Mangrove Canopy Height Globally Related to Precipitation and Cyclone Frequency

Mangrove wetlands are among the most productive and carbon-dense ecosystems in the world. Their structural attributes vary considerably across spatial scales, yielding large uncertainties in regional and global estimates of carbon stocks. Here, we present a global analysis of mangrove canopy height gradients and aboveground carbon stocks based on remotely sensed measurements and field data. Our study highlights that precipitation, temperature and cyclone frequency explain 74% of the global trends in maximum canopy height, with other geophysical factors influencing the observed variability at local and regional scales. We find the tallest mangrove forests in Gabon, equatorial Africa, where stands attain 62.8 m. The total global mangrove carbon stock (above- and belowground biomass, and soil) is estimated at 5.03 Pg, with a quarter of this value stored in Indonesia. Our analysis implies sensitivity of mangrove structure to climate change, and offers a baseline to monitor national and regional trends in mangrove carbon stocks.

Carbon cycle↗
NASA NTRS2003

Distributions of Trace Gases and Aerosols during the Dry Biomass Burning Season in Southern Africa

Vertical profiles in the lower troposphere of temperature, relative humidity, sulfur dioxide (SO2), ozone (O3), condensation nuclei (CN), and carbon monoxide (CO), and horizontal distributions of twenty gaseous and particulate species, are presented for five regions of southern Africa during the dry biomass burning season of 2000. The regions are the semiarid savannas of northeast South Africa and northern Botswana, the savanna-forest mosaic of coastal Mozambique, the humid savanna of southern Zambia, and the desert of western Namibia. The highest average concentrations of carbon dioxide (CO2), CO, methane (CH4), O3, black particulate carbon, and total particulate carbon were in the Botswana and Zambia sectors (388 and 392 ppmv, 369 and 453 ppbv, 1753 and 1758 ppbv, 79 and 88 ppbv, 2.6 and 5.5 micrograms /cubic meter and 13.2 and 14.3 micrograms/cubic meter). This was due to intense biomass burning in Zambia and surrounding regions. The South Africa sector had the highest average concentrations of SO2, sulfate particles, and CN (5.1 ppbv, 8.3 micrograms/cubic meter, and per 6400 cubic meter , respectively), which derived from biomass burning and electric generation plants and mining operations within this sector. Air quality in the Mozambique sector was similar to the neighboring South Africa sector. Over the arid Namibia sector there were polluted layers aloft, in which average SO2, O3, and CO mixing ratios (1.2 ppbv, 76 ppbv, and 3 10 ppbv, respectively) were similar to those measured over the other more polluted sectors. This was due to transport of biomass smoke from regions of widespread savanna burning in southern Angola. Average concentrations over all sectors of CO2 (386 +/- 8 ppmv), CO (261 +/- 81 ppbv), SO2 (2.5 +/- 1.6 ppbv), O3 (64 +/- 13 ppbv), black particulate carbon (2.3 +/- 1.9 microgram/cubic meter), organic particulate carbon (6.2 +/- 5.2 microgram/cubic meter), total particle mass (26.0 +/- 4.7 microgram/cubic meter), and potassium particles (0.4 +- 0.1 microgram/cubic meter) were comparable to those in polluted, urban air. Since the majority of the measurements in this study were obtained in locations well removed from industrial sources of pollution, the high average concentrations of pollutants reflect the effects of widespread biomass burning. On occasions, relatively thin (-0.5 km) layers of remarkably clean air were located at -3 km above mean sea level, sandwiched between heavily polluted air. The data presented here can be used for inputs to and validation of regional and global atmospheric chemical models.

Sinha, Parikhit↗
NASA NTRS2011

Historic Emissions from Deforestation and Forest Degradation in Mato Grosso, Brazil: 1. Source Data Uncertainties

Historic carbon emissions are an important foundation for proposed efforts to Reduce Emissions from Deforestation and forest Degradation and enhance forest carbon stocks through conservation and sustainable forest management (REDD+). The level of uncertainty in historic carbon emissions estimates is also critical for REDD+, since high uncertainties could limit climate benefits from mitigation actions. Here, we analyzed source data uncertainties based on the range of available deforestation, forest degradation, and forest carbon stock estimates for the Brazilian state of Mato Grosso during 1990-2008. Results: Deforestation estimates showed good agreement for multi-year trends of increasing and decreasing deforestation during the study period. However, annual deforestation rates differed by >20% in more than half of the years between 1997-2008, even for products based on similar input data. Tier 2 estimates of average forest carbon stocks varied between 99-192 Mg C/ha, with greatest differences in northwest Mato Grosso. Carbon stocks in deforested areas increased over the study period, yet this increasing trend in deforested biomass was smaller than the difference among carbon stock datasets for these areas. Conclusions: Patterns of spatial and temporal disagreement among available data products provide a roadmap for future efforts to reduce source data uncertainties for estimates of historic forest carbon emissions. Specifically, regions with large discrepancies in available estimates of both deforestation and forest carbon stocks are priority areas for evaluating and improving existing estimates. Full carbon accounting for REDD+ will also require filling data gaps, including forest degradation and secondary forest, with annual data on all forest transitions.

Morton, Douglas C.↗