Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Biomass characterization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Climatology of Aerosol Optical Properties in Southern Africa

A thorough regionally dependent understanding of optical properties of aerosols and their spatial and temporal distribution is required before we can accurately evaluate aerosol effects in the climate system. Long term measurements of aerosol optical depth, Angstrom exponent and retrieved single scattering albedo and size distribution, were analyzed and compiled into an aerosol optical properties climatology for southern Africa. Monitoring of aerosol parameters have been made by the AERONET program since the middle of the last decade in southern Africa. This valuable information provided an opportunity for understanding how aerosols of different types influence the regional radiation budget. Two long term sites, Mongu in Zambia and Skukuza in South Africa formed the core sources of data in this study. Results show that seasonal variation of aerosol optical thicknesses at 500 nm in southern Africa are characterized by low seasonal multi-month mean values (0.11 to 0.17) from December to May, medium values (0.20 to 0.27) between June and August, and high to very high values (0.30 to 0.46) during September to November. The spatial distribution of aerosol loadings shows that the north has high magnitudes than the south in the biomass burning season and the opposite in none biomass burning season. From the present aerosol data, no long term discernable trends are observable in aerosol concentrations in this region. This study also reveals that biomass burning aerosols contribute the bulk of the aerosol loading in August-October. Therefore if biomass burning could be controlled, southern Africa will experience a significant reduction in total atmospheric aerosol loading. In addition to that, aerosol volume size distribution is characterized by low concentrations in the non biomass burning period and well balanced particle size contributions of both coarse and fine modes. In contrast high concentrations are characteristic of biomass burning period, combined with significant dominance of fine mode particles.

Queface, Antonio J.↗
NASA NTRS2011

L Band Brightness Temperature Observations Over a Corn Canopy During the Entire Growth Cycle

During a field campaign covering the 2002 corn growing season, a dual polarized tower mounted L-band (1.4 GHz) radiometer (LRAD) provided brightness temperature (T(sub B)) measurements at preset intervals, incidence and azimuth angles. These radiometer measurements were supported by an extensive characterization of land surface variables including soil moisture, soil temperature, vegetation biomass, and surface roughness. During the period from May 22, 2002 to August 30, 2002 a range of vegetation water content (W) of 0.0 to 4.3 kg/square m, ten days of radiometer and ground measurements were available. Using this data set, the effects of corn vegetation on surface emissions are investigated by means of a semi-empirical radiative transfer model. Additionally, the impact of roughness on the surface emission is quantified using T(sub B) measurements over bare soil conditions. Subsequently, the estimated roughness parameters, ground measurements and horizontally (H)-polarized T(sub B) are employed to invert the H-polarized transmissivity (gamma-h) for the monitored corn growing season.

Joseph, Alicia T.↗
NASA NTRS2014

The Effect of Growth Environment and Salinity on Lipid Production and Composition of Salicornia virginica

Finding a viable and sustainable source of renewable energy is a global task. Biofuels as a renewable energy source can potentially be a viable option for sustaining long-term energy needs. Biodiesel from halophytes shows great promise due to their ability to serve not only as a fuel source, but a food source as well. Halophytes are one of the few biomass plant species that can tolerate a wide range of saline conditions. We investigate the feasibility of using the halophyte, Salicornia virginica as a biofuel source by conducting a series of experiments utilizing various growth and salinity conditions. The goal is to determine if the saline content of Salicornia virginica in our indoor growth vs outdoor growth conditions has an influence on lipid recovery and total biomass composition. We focused on using standard lipid extraction protocols and characterization methods to evaluate twelve Salicornia virginica samples under six saline values ranging from freshwater to seawater and two growth conditions. The overall goal is to develop an optimal lipid extraction protocol for Salicornia virginica and potentially apply this protocol to halophytes in general.

Bomani, Bilal Mark McDowell↗
NASA NTRS2015

Characterization of Aerosol Episodes in the Greater Mediterranean Sea Area from Satellite Observations (2000-2007)

An algorithm able to identify and characterize episodes of different aerosol types above sea surfaces of the greater Mediterranean basin (GMB), including the Black Sea and the Atlantic Ocean off the coasts of Iberia and northwest Africa, is presented in this study. Based on this algorithm, five types of intense (strong and extreme) aerosol episodes in the GMB are identified and characterized using daily aerosol optical properties from satellite measurements, namely MODIS-Terra, Earth Probe (EP)-TOMS and OMIAura. These aerosol episodes are: (i) biomass-burning/urban-industrial (BU), (ii) desert dust (DD), (iii) dust/sea-salt (DSS), (iv) mixed (MX) and (v) undetermined (UN). The identification and characterization is made with our algorithm using a variety of aerosol properties, namely aerosol optical depth (AOD), Angstrom exponent (a), fine fraction (FF), effective radius (reff) and Aerosol Index (AI). During the study period (2000e2007), the most frequent aerosol episodes are DD, observed primarily in the western and central Mediterranean Sea, and off the northern African coasts, 7 times/year for strong episodes and 4 times/year for extreme ones, on average. The DD episodes yield 40% of all types of strong aerosol episodes in the study region, while they account for 71.5% of all extreme episodes. The frequency of occurrence of strong episodes exhibits specific geographical patterns, for example the BU are mostly observed along the coasts of southern Europe and off the Atlantic coasts of Portugal, the MX episodes off the Spanish Mediterranean coast and over the Adriatic and northern Aegean Sea, while the DSS ones over the western and central Mediterranean Sea. On the other hand, the extreme episodes for all but DD aerosol display more patchy spatial patterns. The strong episodes exhibit AOD at 550 nm as high as 1.6 in the southernmost parts of central and eastern Mediterranean Sea, which rise up to 5 for the extreme, mainly DD and DSS, episodes. Although more than 90% of all aerosol episodes last 1 day, there are few cases, mainly extreme DD episodes, which last up to 4 days. Independently of their type, the Mediterranean aerosol episodes occur more frequently in spring (strong and extreme episodes) and summer (strong episodes) and most rarely during winter. A significant year by year variability of Mediterranean aerosol episodes has been identified, more in terms of their frequency than intensity. An analysis of 5-day back trajectories for the most extreme episodes provides confidence on the obtained results of the algorithm, based on the revealed origin and track of air masses causing the episodes. The 25 and 6% of all strong and extreme episodes, respectively, are MX, thus highlighting the co-existence of different aerosol types in the greater Mediterranean. The intensity of both MX and DSS episodes exhibits similar patterns to those of DD strong ones, indicating that desert dust is a determinant factor for the intensity of aerosol episodes in the Mediterranean, including DSS and MX episodes.

Atmospheric Chemistry↗
NASA NTRS1996

Volatile organic compounds detected in the atmosphere of NASA's Biomass Production Chamber

Atmospheres of enclosed environments in which 20 m2 stands of wheat, potato, and lettuce were grown were characterized and quantified by gas chromatography-mass spectrometry. A large number (in excess of 90) of volatile organic compounds (VOCs) were identified in the chambers. Twenty eight VOC's were assumed to be of biogenic origin for these were not found in the chamber atmosphere when air samples were analyzed in the absence of plants. Some of the compounds found were unique to a single crop. For example, only 35% of the biogenic compounds detected in the wheat atmosphere were unique to wheat, while 36% were unique to potato and 26% were unique to lettuce. The number of compounds detected in the wheat (20 compounds) atmosphere was greater than that of potato (11) and lettuce (15) and concentration levels of biogenic and non-biogenic VOC's were similar.

NASA Discipline Number 61-20↗
NASA NTRS2016

Lidar-Based Estimates of Above-Ground Biomass in the Continental US and Mexico Using Ground, Airborne, and Satellite Observations

Existing national forest inventory plots, an airborne lidar scanning (ALS) system, and a space profiling lidar system (ICESat-GLAS) are used to generate circa 2005 estimates of total aboveground dry biomass (AGB) in forest strata, by state, in the continental United States (CONUS) and Mexico. The airborne lidar is used to link ground observations of AGB to space lidar measurements. Two sets of models are generated, the first relating ground estimates of AGB to airborne laser scanning (ALS) measurements and the second set relating ALS estimates of AGB (generated using the first model set) to GLAS measurements. GLAS then, is used as a sampling tool within a hybrid estimation framework to generate stratum-, state-, and national-level AGB estimates. A two-phase variance estimator is employed to quantify GLAS sampling variability and, additively, ALS-GLAS model variability in this current, three-phase (ground-ALS-space lidar) study. The model variance component characterizes the variability of the regression coefficients used to predict ALS-based estimates of biomass as a function of GLAS measurements. Three different types of predictive models are considered in CONUS to determine which produced biomass totals closest to ground-based national forest inventory estimates - (1) linear (LIN), (2) linear-no-intercept (LNI), and (3) log-linear. For CONUS at the national level, the GLAS LNI model estimate (23.95 +/- 0.45 Gt AGB), agreed most closely with the US national forest inventory ground estimate, 24.17 +/- 0.06 Gt, i.e., within 1%. The national biomass total based on linear ground-ALS and ALS-GLAS models (25.87 +/- 0.49 Gt) overestimated the national ground-based estimate by 7.5%. The comparable log-linear model result (63.29 +/-1.36 Gt) overestimated ground results by 261%. All three national biomass GLAS estimates, LIN, LNI, and log-linear, are based on 241,718 pulses collected on 230 orbits. The US national forest inventory (ground) estimates are based on 119,414 ground plots. At the US state level, the average absolute value of the deviation of LNI GLAS estimates from the comparable ground estimate of total biomass was 18.8% (range: Oregon,−40.8% to North Dakota, 128.6%). Log-linear models produced gross overestimates in the continental US, i.e., N2.6x, and the use of this model to predict regional biomass using GLAS data in temperate, western hemisphere forests is not appropriate. The best model form, LNI, is used to produce biomass estimates in Mexico. The average biomass density in Mexican forests is 53.10 +/- 0.88 t/ha, and the total biomass for the country, given a total forest area of 688,096 sq km, is 3.65 +/- 0.06 Gt. In Mexico, our GLAS biomass total underestimated a 2005 FAO estimate (4.152 Gt) by 12% and overestimated a 2007/8 radar study's figure (3.06 Gt) by 19%.

Hybrid 3-Phase sampling↗
NASA NTRS1992

A regional estimate of convective transport of CO from biomass burning

A regional-scale estimate of the fraction of biomass burning emissions that are transported to the free troposphere by deep convection is presented. The focus is on CO and the study region is a part of Brazil that underwent intensive deforestation in the 1980s. The method of calculation is stepwise, scaling up from a prototype convective event, the dynamics of which are well-characterized, to the vertical mass flux of carbon monoxide over the region. Given uncertainties in CO emissions from biomass burning and the representativeness of the prototype event, it is estimated that 10-40 percent of CO emissions from the burning region may be rapidly transported to the free troposphere over the burning region. These relatively fresh emissions will produce O3 efficiently in the free troposphere where O3 has a longer lifetime than in the boundary layer.

Pickering, Kenneth E.↗
NASA NTRS2003

Trace Gas Measurements in Nascent, Aged and Cloud-processed Smoke from Africa Savanna Fires by Airborne Fourier Transform Infrared Spectroscopy (AFTIR)

We measured stable and reactive trace gases with an airborne Fourier transform infrared spectrometer (AFTIR) on the University of Washington Convair-580 research aircraft in August/September 2000 during the SAFARI 2000 dry season campaign in Southern Africa. The measurements included vertical profiles of C02, CO, H20, and CH4 up to 5.5 km on six occasions above instrumented ground sites and below the TERRA satellite and ER-2 high-flying research aircraft. We also measured the trace gas emissions from 10 African savanna fires. Five of these fires featured extensive ground-based fuel characterization, and two were in the humid savanna ecosystem that accounts for most African biomass burning. The major constituents we detected in nascent CH3OOH, HCHO, CH30H, HCN, NH3, HCOOH, and C2H2. These are the first quantitative measurements of the initial emissions of oxygenated volatile organic compounds (OVOC), NH3, and HCN from African savanna fires. On average, we measured 5.3 g/kg of OVOC and 3.6 g/kg of hydrocarbons (including CH4) in the initial emissions from the fires. Thus, the OVOC will have profound, largely unexplored effects on tropical tropospheric chemistry. The HCN emission factor was only weakly dependent on fire type; the average value (0.53 g/kg) is about 20 times that of a previous recommendation. HCN may be useful as a tracer for savanna fires. Delta O3/Delta CO and Delta CH3COO/Delta CO increased to as much as 9% in <1 h of photochemical processing downwind of fires. Direct measurements showed that cloud processing of smoke greatly reduced CH30H, NH3, CH3COOH, SO2, and NO2 levels, but significantly increased HCHO and NO.

Yokelson, Robert J.↗
NASA NTRS2013

Source Attributions of Pollution to the Western Arctic During the NASA ARCTAS Field Campaign

We use the NASA GEOS-5 transport model with tagged tracers to investigate the contributions of different regional sources of CO and black carbon (BC) to their concentrations in the Western Arctic (i.e., 50-90 deg N and 190- 320 deg E) in spring and summer 2008. The model is evaluated by comparing the results with airborne measurements of CO and BC from the NASA Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field campaigns to demonstrate the strengths and limitations of our simulations. We also examine the reliability of tagged CO tracers in characterizing air mass origins using the measured fossil fuel tracer of dichloromethane and the biomass burning tracer of acetonitrile. Our tagged CO simulations suggest that most of the enhanced CO concentrations (above background level from CH4 production) observed during April originate from Asian anthropogenic emissions. Boreal biomass burning emissions and Asian anthropogenic emissions are of similar importance in July domain wise, although the biomass burning CO fraction is much larger in the area of the ARCTAS field experiments. The fraction of CO from Asian anthropogenic emissions is larger in spring than in summer. European sources make up no more than 10% of CO levels in the campaign domain during either period. Comparisons of CO concentrations along the flight tracks with regional averages from GEOS-5 show that the alongtrack measurements are representative of the concentrations within the large domain of the Western Arctic in April but not in July.

Black Carbon↗
NASA NTRS2021

Spectral Derivatives of Optical Depth for Partitioning Aerosol Type and Loading

Quantifying aerosol compositions (e.g., type, loading) from remotely sensed measurements by spaceborne, suborbital and ground-based platforms is a challenging task. In this study, the first and second-order spectral derivatives of aerosol optical depth (AOD) with respect to wavelength are explored to determine the partitions of the major components of aerosols based on the spectral dependence of their particle optical size and complex refractive index. With theoretical simulations from the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) model, AOD spectral derivatives are characterized for collective models of aerosol types, such as mineral dust (DS) particles, biomass-burning (BB) aerosols and anthropogenic pollutants (AP), as well as stretching out to the mixtures among them. Based on the intrinsic values from normalized spectral derivatives, referenced as the Normalized Derivative Aerosol Index (NDAI), a unique pattern is clearly exhibited for bounding the major aerosol components; in turn, fractions of the total AOD (fAOD) for major aerosol components can be extracted. The subtlety of this NDAI method is examined by using measurements of typical aerosol cases identified carefully by the ground-based Aerosol Robotic Network (AERONET) sun–sky spectroradiometer. The results may be highly practicable for quantifying fAOD among mixed-type aerosols by means of the normalized AOD spectral derivatives.

aerosol partition↗
NASA NTRS2022

Identifying Chemical Aerosol Signatures Using Optical Suborbital Observations: How Much Can Optical Properties Tell us about Aerosol Composition?

Improvements in air quality and Earth’s climate predictions require improvements of the aerosol speciation in chemical transport models, using observational constraints. Aerosol speciation (e.g., organic aerosols, black carbon, sulfate, nitrate, ammonium, dust or sea salt) is typically determined using in situ instrumentation. Continuous, routine surface network aerosol composition measurements are not uniformly widespread over the globe. Satellites, on the other hand, can provide a maximum coverage of the horizontal and vertical atmosphere but observe aerosol optical properties (and not aerosol speciation) based on remote sensing instrumentation. Combinations of satellite-derived aerosol optical properties can inform on air mass aerosol types (AMTs e.g., clean marine, dust, polluted continental). However, these AMTs are subjectively defined, might often be misclassified and are hard to relate to the critical parameters that need to be refined in models. In this paper, we derive AMTs that are more directly related to sources and hence to speciation. They are defined, characterized, and derived using simultaneous in situ gas-phase, chemical and optical instruments on the same aircraft during the Study of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS, US, summer of 2013). First, we prescribe well-informed AMTs that display distinct aerosol chemical and optical signatures to act as a training AMT dataset. These in situ observations reduce the errors and ambiguities in the selection of the AMT training dataset. We also investigate the relative skill of various combinations of aerosol optical properties to define AMTs and how much these optical properties can capture dominant aerosol speciation. We find distinct optical signatures for biomass burning (from agricultural or wildfires), biogenic and dust-influence AMTs. Useful aerosol optical properties to characterize these signatures are the extinction angstrom exponent (EAE), the single scattering albedo, the difference of single scattering albedo in two wavelengths, the absorption coefficient, the absorption angstrom exponent (AAE), and the real part of the refractive index (RRI). We find that all four AMTs studied when prescribed using mostly airborne in situ gas measurements, can be successfully extracted from at least three combinations of airborne in situ aerosol optical properties (e.g., EAE, AAE and RRI) over the US during SEAC4RS. However, we find that the optically based classifications for BB from agricultural fires and polluted dust include a large percentage of misclassifications that limit the usefulness of results relating to those classes. The technique and results presented in this study are suitable to develop a representative, robust and diverse source-based AMT database. This database could then be used for widespread retrievals of AMTs using existing and future remote sensing suborbital instruments/networks. Ultimately, it has the potential to provide a much broader observational aerosol data set to evaluate chemical transport and air quality models than is currently available by direct in situ measurements. This study illustrates how essential it is to explore existing airborne datasets to bridge chemical and optical signatures of different AMTs, before the implementation of future spaceborne missions (e.g., the next generation of Earth Observing System (EOS) satellites addressing Aerosol, Cloud, Convection and Precipitation (ACCP) designated observables).

Meloe S F Kacenelenbogen↗
NASA NTRS2012

Lidar Remote Sensing of Forests: New Instruments and Modeling Capabilities

Lidar instruments provide scientists with the unique opportunity to characterize the 3D structure of forest ecosystems. This information allows us to estimate properties such as wood volume, biomass density, stocking density, canopy cover, and leaf area. Structural information also can be used as drivers for photosynthesis and ecosystem demography models to predict forest growth and carbon sequestration. All lidars use time-in-flight measurements to compute accurate ranging measurements; however, there is a wide range of instruments and data types that are currently available, and instrument technology continues to advance at a rapid pace. This seminar will present new technologies that are in use and under development at NASA for airborne and space-based missions. Opportunities for instrument and data fusion will also be discussed, as Dr. Cook is the PI for G-LiHT, Goddard's LiDAR, Hyperspectral, and Thermal airborne imager. Lastly, this talk will introduce radiative transfer models that can simulate interactions between laser light and forest canopies. Developing modeling capabilities is important for providing continuity between observations made with different lidars, and to assist the design of new instruments. Dr. Bruce Cook is a research scientist in NASA's Biospheric Sciences Laboratory at Goddard Space Flight Center, and has more than 25 years of experience conducting research on ecosystem processes, soil biogeochemistry, and exchange of carbon, water vapor and energy between the terrestrial biosphere and atmosphere. His research interests include the combined use of lidar, hyperspectral, and thermal data for characterizing ecosystem form and function. He is Deputy Project Scientist for the Landsat Data Continuity Mission (LDCM); Project Manager for NASA s Carbon Monitoring System (CMS) pilot project for local-scale forest biomass; and PI of Goddard's LiDAR, Hyperspectral, and Thermal (G-LiHT) airborne imager.

Cook, Bruce D.↗
NASA NTRS2003

Use of MODIS-Derived Fire Radiative Energy to Estimate Smoke Aerosol Emissions over Different Ecosystems

Biomass burning is the main source of smoke aerosols and certain trace gases in the atmosphere. However, estimates of the rates of biomass consumption and emission of aerosols and trace gases from fires have not attained adequate reliability thus far. Traditional methods for deriving emission rates employ the use of emission factors e(sub x), (in g of species x per kg of biomass burned), which are difficult to measure from satellites. In this era of environmental monitoring from space, fire characterization was not a major consideration in the design of the early satellite-borne remote sensing instruments, such as AVHRR. Therefore, although they are able to provide fire location information, they were not adequately sensitive to variations in fire strength or size, because their thermal bands used for fire detection saturated at the lower end of fire radiative temperature range. As such, hitherto, satellite-based emission estimates employ proxy techniques using satellite derived fire pixel counts (which do not express the fire strength or rate of biomass consumption) or burned areas (which can only be obtained after the fire is over). The MODIS sensor, recently launched into orbit aboard EOS Terra (1999) and Aqua (2002) satellites, have a much higher saturation level and can, not only detect the fire locations 4 times daily, but also measures the at-satellite fire radiative energy (which is a measure of the fire strength) based on its 4 micron channel temperature. Also, MODIS measures the optical thickness of smoke and other aerosols. Preliminary analysis shows appreciable correlation between the MODIS-derived rates of emission of fire radiative energy and smoke over different regions across the globe. These relationships hold great promise for deriving emission coefficients, which can be used for estimating smoke aerosol emissions from MODIS active fire products. This procedure has the potential to provide more accurate emission estimates in near real-time, providing opportunities for various disaster management applications such as alerts, evacuation and, smoke dispersion forecasting.

Ichoku, Charles↗
NASA NTRS2020

Spectral Range Within Global aCDOM(440) Algorithms for Oceanic, Coastal, and Inland Waters with Application to Airborne Measurements

The optically active component of dissolved organic material in aquatic ecosystems, or colored dissolved organic matter (CDOM), is represented by the coefficient of absorption due to the dissolved aquatic constituents at 440 nm, aCDOM(440). Remote sensing of aCDOM(440) enables characterization of ecosystem processes and aids in retrieval of chlorophyll a, a proxy for phytoplankton biomass. Spectrally adjacent band-ratio domains, e.g., blue to green, have previously been applied for remote sensing of aCDOM(440) in coastal and oceanic waters with similar results compared to more complex semi-analytical algorithms. Estimation of aCDOM(440) from ratios of the most spectrally separated ocean color wavebands (end members), e.g., ultraviolet (UV) to near-infrared (NIR), termed end-member analysis (EMA), has previously been shown to increase the accuracy of global aCDOM(440) retrievals from in-water observations of diffuse attenuation and to enable a unified algorithmic perspective without requiring regional adjustment of internal bio-optical parameters. EMA of above-water observations is evaluated herein, with a focus on coastal and inland waters in which increasing optical complexity and likelihood of bottom reflectance challenge the oceanic algorithms developed for deep and optically simple (case-1) waters. Analysis herein of three independent, in situ, bio-optical datasets indicates significant correlation between aCDOM(440) and end-member band ratios (next-generation 320 and 780 nm or legacy 412 and 670 nm ratios) with a coefficient of determination, R2, of 0.87 (log-scale) or higher based on a dataset spanning the dynamic range of global, conservative water bodies. For applicable wavelengths, EMA algorithms are shown to agree with case-1 relationships and to produce consistent log-scale uncertainties across more than three orders of magnitude in aCDOM(440) values (0.001–2.305 m􀀀1). EMA using UV and NIR wavelengths (320 and 780 nm) is applied to low-altitude airborne observations and satisfies 25% uncertainty based on unbiased percent differences (UPDs) within each of three dissimilar match-up sites ranging in aCDOM(440) from 0.02–0.57 m􀀀1. Results demonstrate that EMA is a useful and robust approach for the remote sensing of aCDOM(440) in coastal and inland waters, which are generally shallower, contain more optically complex environments, and span a greater range in aCDOM(440) than oceanic waters.

CDOM↗
NASA NTRS2012

Characterizing 3D Vegetation Structure from Space: Mission Requirements

Human and natural forces are rapidly modifying the global distribution and structure of terrestrial ecosystems on which all of life depends, altering the global carbon cycle, affecting our climate now and for the foreseeable future, causing steep reductions in species diversity, and endangering Earth s sustainability. To understand changes and trends in terrestrial ecosystems and their functioning as carbon sources and sinks, and to characterize the impact of their changes on climate, habitat and biodiversity, new space assets are urgently needed to produce high spatial resolution global maps of the three-dimensional (3D) structure of vegetation, its biomass above ground, the carbon stored within and the implications for atmospheric green house gas concentrations and climate. These needs were articulated in a 2007 National Research Council (NRC) report (NRC, 2007) recommending a new satellite mission, DESDynI, carrying an L-band Polarized Synthetic Aperture Radar (Pol-SAR) and a multi-beam lidar (Light RAnging And Detection) operating at 1064 nm. The objectives of this paper are to articulate the importance of these new, multi-year, 3D vegetation structure and biomass measurements, to briefly review the feasibility of radar and lidar remote sensing technology to meet these requirements, to define the data products and measurement requirements, and to consider implications of mission durations. The paper addresses these objectives by synthesizing research results and other input from a broad community of terrestrial ecology, carbon cycle, and remote sensing scientists and working groups. We conclude that: (1) current global biomass and 3-D vegetation structure information is unsuitable for both science and management and policy. The only existing global datasets of biomass are approximations based on combining land cover type and representative carbon values, instead of measurements of actual biomass. Current measurement attempts based on radar and multispectral data have low explanatory power outside low biomass areas. There is no current capability for repeatable disturbance and regrowth estimates. (2) The science and policy needs for information on vegetation 3D structure can be successfully addressed by a mission capable of producing (i) a first global inventory of forest biomass with a spatial resolution 1km or finer and unprecedented accuracy (ii) annual global disturbance maps at a spatial resolution of 1 ha with subsequent biomass accumulation rates at resolutions of 1km or finer, and (iii) transects of vertical and horizontal forest structure with 30 m along-transect measurements globally at 25 m spatial resolution, essential for habitat characterization. We also show from the literature that lidar profile samples together with wall-to53 wall L-band quad-pol-SAR imagery and ecosystem dynamics models can work together to satisfy these vegetation 3D structure and biomass measurement requirements. Finally we argue that the technology readiness levels of combined pol-SAR and lidar instruments are adequate for space flight. Remaining to be worked out, are the particulars of a lidar/pol-SAR mission design that is feasible and at a minimum satisfies the information and measurement requirement articulated herein.

Hall, Forrest G.↗
NASA NTRS2001

Association of American Geographers, Remote Sensing Specialty Group Special Issue of Geocarto International

This special issue continues the precedence of the Association of American Geographers (AAG), Remote Sensing Specialty Group (RSSG) for publishing selected articles in Geocarto International as a by-product from the AAG annual meeting. As editors, we issued earlier this year, a solicitation for papers to be published in a special issue of Geocarto International that were presented in RSSG-sponsored sessions at the 2001 AAG annual meeting held in New York City on February 27-March 3. Although not an absolute requisite for publication, the vast majority of the papers in this special issue were presented at this year's AAG meeting in New York. Other articles in this issue that were not part of a paper or poster session at the 2001 AAG meeting are authored by RSSG members. Under the auspices of the RSSG, this special Geocarto International issue provides even more compelling evidence of the inextricable linkage between remote sensing and geography. The papers in this special issue fall into four general themes: 1) Urban Analysis and Techniques for Urban Analysis; 2) Land Use/Land Cover Analysis; 3) Fire Modeling Assessment; and 4) Techniques. The first four papers herein are concerned with the use of remote sensing for analysis of urban areas, and with use or development of techniques to better characterize urban areas using remote sensing data. As the lead paper in this grouping, Rashed et al., examine the usage of spectral mixture analysis (SMA) for analyzing satellite imagery of urban areas as opposed to more 'standard' methods of classification. Here SMA has been applied to IRS-1C satellite multispectral imagery to extract measures that better describe the 'anatomy' of the greater Cairo, Egypt region. Following this paper, Weng and Lo describe how Landsat TM data have been used to monitor land cover types and to estimate biomass parameters within an urban environment. The research reported in this paper applies an integrated GIS (Geographic Information System) approach for detecting urban growth and assessing its impact on biomass in the Zhujiang Delta, China. The remaining two papers in this first grouping deal with improved techniques for characterizing and analyzing urban areas using remote sensing data. Myint examines the use of texture analysis to better classify urban features. Here wavelet analysis has been employed to assist in deriving a more robust classification of the urban environment from high spatial resolution, multispectral aircraft data. Mesev provides insight on how through the modification of the standard maximum likelihood image analysis technique, population census data can be used enhance the overall robustness of urban image classification through the modification of the standard maximum likelihood image analysis technique.

Allen, Thomas R.↗
NASA NTRS2012

Modified Light Use Efficiency Model for Assessment of Carbon Sequestration in Grasslands of Kazakhstan: Combining Ground Biomass Data and Remote-sensing

A modified light use efficiency (LUE) model was tested in the grasslands of central Kazakhstan in terms of its ability to characterize spatial patterns and interannual dynamics of net primary production (NPP) at a regional scale. In this model, the LUE of the grassland biome (εn) was simulated from ground-based NPP measurements, absorbed photosynthetically active radiation (APAR) and meteorological observations using a new empirical approach. Using coarse-resolution satellite data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), monthly NPP was calculated from 1998 to 2008 over a large grassland region in Kazakhstan. The modelling results were verified against scaled up plot-level observations of grassland biomass and another available NPP data set derived from a field study in a similar grassland biome. The results indicated the reliability of productivity estimates produced by the model for regional monitoring of grassland NPP. The method for simulation of εn suggested in this study can be used in grassland regions where no carbon flux measurements are accessible.

Kazakhstan↗
NASA NTRS1999

Interannual Variabilities in Tropical Tropospheric Ozone

This paper presents the first detailed characterization of interannual variability in tropical tropospheric column ozone (TCO) to delineate the relative importance of biomass burning and large-scale transport. TCO time series are derived from 20 years (1979-1998) of total ozone mapping spectrometer (TOMS) data using the convective cloud differential (CCD) method. Our study identifies three regions in the tropics with distinctly different characteristics related to interannual variability. These three regions are the eastern Pacific, Atlantic, and western Pacific. The Atlantic region indicates a quasi-biennial oscillation (QBO) in TCO which is out of phase with the QBO in stratospheric ozone. This is consistent with the photochemical control of this region by ozone-producing precursors. The observed pattern however does not seem to be related to interannual variability in ozone precursors related to biomass burning. Instead it appears to be a manifestation of the UV modulation of upper tropospheric chemistry on a QBO time scale caused by stratospheric ozone. During El Nino events there is anomalously low TCO in the eastern Pacific and high values in the western Pacific, indicating the effects of convectively-driven transport. The observed increase of 10-20 DU in TCO in the Indonesian region in the western Pacific during the recent 1997-1998 El Nino was associated with large-scale fires which may have contributed 5-10 DU of the total increase.

Ziemke, Jerry R.↗