Engineering topics

Hall, Forrest G.

Publications and source records attributed to Hall, Forrest G..

At least 19 records

NASA NTRS2012

Remote Sensing of Tropical Ecosystems: Atmospheric Correction and Cloud Masking Matter

Tropical rainforests are significant contributors to the global cycles of energy, water and carbon. As a result, monitoring of the vegetation status over regions such as Amazonia has been a long standing interest of Earth scientists trying to determine the effect of climate change and anthropogenic disturbance on the tropical ecosystems and its feedback on the Earth's climate. Satellite-based remote sensing is the only practical approach for observing the vegetation dynamics of regions like the Amazon over useful spatial and temporal scales, but recent years have seen much controversy over satellite-derived vegetation states in Amazônia, with studies predicting opposite feedbacks depending on data processing technique and interpretation. Recent results suggest that some of this uncertainty could stem from a lack of quality in atmospheric correction and cloud screening. In this paper, we assess these uncertainties by comparing the current standard surface reflectance products (MYD09, MYD09GA) and derived composites (MYD09A1, MCD43A4 and MYD13A2 - Vegetation Index) from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to results obtained from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. MAIAC uses a new cloud screening technique, and novel aerosol retrieval and atmospheric correction procedures which are based on time-series and spatial analyses. Our results show considerable improvements of MAIAC processed surface reflectance compared to MYD09/MYD13 with noise levels reduced by a factor of up to 10. Uncertainties in the current MODIS surface reflectance product were mainly due to residual cloud and aerosol contamination which affected the Normalized Difference Vegetation Index (NDVI): During the wet season, with cloud cover ranging between 90 percent and 99 percent, conventionally processed NDVI was significantly depressed due to undetected clouds. A smaller reduction in NDVI due to increased aerosol levels was observed during the dry season, with an inverse dependence of NDVI on aerosol optical thickness (AOT). NDVI observations processed with MAIAC showed highly reproducible and stable inter-annual patterns with little or no dependence on cloud cover, and no significant dependence on AOT (p less than 0.05). In addition to a better detection of cloudy pixels, MAIAC obtained about 20-80 percent more cloud free pixels, depending on season, a considerable amount for land analysis given the very high cloud cover (75-99 percent) observed at any given time in the area. We conclude that a new generation of atmospheric correction algorithms, such as MAIAC, can help to dramatically improve vegetation estimates over tropical rain forest, ultimately leading to reduced uncertainties in satellite-derived vegetation products globally.

tropical ecosystems↗

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 NTRS2011

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

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

Peddle, Derek R.↗

NASA NTRS2004

A LEO Hyperspectral Mission Implementation for Global Carbon Cycle Observations

For both terrestrial and ocean carbon cycle science objectives, high resolution (less than l0 nm) imaging spectrometers capable of acquiring multiple regional to global scale observations per day should enable the development of new remote sensing measurements for important but as yet unobservable variables, with the overall goal of linking both terrestrial and ocean carbon cycle processes to climate variability. For terrestrial research, accurate estimates of carbon, water and energy (CWE) exchange between the terrestrial biosphere and atmosphere a needed to id- the geographical locations and temporal dynamics of carbon sources/sinks and to improve regional climate models and climate change assessments. It is an enormous challenge to estimate CWE exchange from the infrequent temporal coverage and sparse spectral information provided by most single polar-orbiting, earth-looking satellite. The available satellite observations lack a sufficient number of well-placed narrow bands from which to derive spectral indices that capture vegetation responses to stress conditions associated with down-regulation of photosynthesis. Physiological status can best be assessed with spectral indices based on continuous, narrow bands in the visible/near infrared spectra, as can seasonal and annual terrestrial productivity. For coastal and ocean constituents, narrow-band observations in the ultraviolet and visible are essential to investigate the variability, dynamics and biogeochemical cycles of the world's coastal and open ocean regions, which will in turn help in measuring ocean productivity and predicting the variability of ocean carbon uptake and its role in climate change.

Gervin, Janette C.↗

NASA NTRS2004

A GEO Hyperspectral Mission For Continental-Scale Carbon Cycle Observations

For both terrestrial and ocean carbon cycle science objectives, a hyperspectral geostationary sensor should enable the development of new remote sensing measurements for important but as yet unobservable variables, and with the overall goal of linking both terrestrial and ocean carbon cycle processes to climate variability. For terrestrial research, accurate estimates of carbon, water and energy (CWE) exchange between the terrestrial biosphere and atmosphere are needed to identify the geographical locations of carbon sources/sinks and to improve regional climate models and global climate change assessments. It is an enormous challenge to estimate CWE exchange from the infrequent temporal coverage provided by most polar-orbiting satellites, and without benefit of spectral indices that capture vegetation responses to stress conditions that down-regulate photosynthesis. Physiological status can be better assessed with spectral indices based on continuous, narrow (5 nm) bands, as can seasonal and annual terrestrial productivity. For coastal and ocean constituents, narrow-band observations in the ultraviolet and visible are essential to investigate the variability, dynamics and biogeochemical cycles of the world s coastal and open ocean regions, which will in turn help in measuring ocean productivity and predicting the variability of Ocean carbon uptake and its role in climate change scenarios. The GSFC Carbon Team has been pursuing a geostationary hyperspectral instrument, which would revolutionize our knowledge of biological processes on land, in the ocean, and along the coast by providing multiple, diurnal coverage. Preliminary studies in Goddard's Instrument Synthesis and Analysis Laboratory (ISAL) indicate that we can meet many of our science requirements: full spectral coverage (360-1000 nm); narrow bandwidths (5-10 nm); adequate ground resolution (100-200 m); and continental-scale coverage 4-6 times per day; all the while achieving a signal to noise ratio of between 500 and 1000 to 1. However, an innovative and bold focal plane design and a large mirror (1.8 meter diameter) would be required. The development of our science requirements and the results of the initial design study will be presented as well as our most recent technological developments.

Gervin, Janette C.↗

NASA NTRS2003

Estimating Terrestrial Carbon Exchange from Space: How Often and How Well?

Data from a new space mission measuring integrated light-use efficiency could provide a breakthrough in understanding of global carbon, water, and energy dynamics, and greatly improve the accuracy of model predictions for terrestrial carbon cycles and climate. Over the past decade, Gamon and others have shown that changes in photo-protective pigments are sensitive indicators of declines in light-use efficiency of plants and plant canopies. The requirements for integrated diurnal measurements from space need to be defined, before a space mission can be formulated successfully using this concept. We used towerbased CO 2 flux data as idealized proxies for remote measurements, examining their sampling properties. Thousands of half-hourly CO 2 flux measurements are needed before their average begins to converge on an average annual net CO 2 exchange. Estimates of daily integrated fluxes (i.e., diurnal curves) are more statistically efficient, especially if the spacing between measured days is quasiregular, rather than random. Using a few measurements per day one can distinguish among days with different net CO 2 exchanges. Fluxes sampled between mid-morning to mid-afternoon are more diagnostic than early morning or late afternoon measurements. Similar results (correlation >0.935) were obtained using 2 measurements per day with high accuracy ([:plusmn:]5%), 3 measurements per day with medium accuracy ([:plusmn:] 10%), or 5 measurements per day at lower accuracy ([:plusmn:]20%). An observatory in a geosynchronous or near-geosynchronous orbit could provide appropriate observations, as could a multi-satellite constellation in polar orbits, but there is a potential trade-off between the required number of observations per day and quality of each observation.

Knox, Robert G.↗

NASA NTRS2000

BOREAS TGB-7 Rainwater Herbicide and Organochlorine Concentration Data

The BOREAS TGB-7 team measured the concentration and flux of several agricultural pesticides in air and rainwater samples in order to determine the associated yearly deposition rates. This data set contains information on the rainwater concentration of seven herbicides [2,4- dichlorophenoxyacidic_acid (2,4-D), bromoxynil, dicamb, 2-methyl-4-chlorophenoxyacetic acid (MCPA), triallate, trifluralin, and diclop-methyl] known to appear in the atmosphere of the Canadian prairies. Also, the concentration of three herbicides (atrazine, alachlor, and metolachlor), two groups of insecticides (lindane and breakdown products and dichloro-diphenyl-trichloroethane (DDT) and breakdown products), and several polychlorinated biphenyls commonly used in the central United States was measured. All of these chemicals are reported, in the literature, to be transported in the atmosphere. Many have been reported to occur in boreal and arctic food chains. The sampling was carried out from 16-Jun to 13-Aug-1993 and 04-May to 20-Jul-1994 at the BOREAS site in the Prince Albert National Park (Waskesiu). The data are stored in tabular ASCII files.

Waite, Don↗

NASA NTRS2000

BOREAS TGB-7 Dry Deposition Herbicide and Organochlorine Flux Data

The BOREAS TGB-7 team measured the concentration and flux of several agricultural pesticides in air, rainwater, and dry deposition samples in order to determine the associated yearly deposition rates. This data set contains information on the dry deposition flux of seven herbicides [2,4- dichlorophenoxyacidic_acid (2,4-D), bromoxynil, dicamb, 2-methyl-4-chlorophenoxyacetic acid (MCPA), triallate, trifluralin, and diclop-methyl] known to appear in the atmosphere of the Canadian prairies. Also, the concentration of three herbicides (atrazine, alachlor, and metolachlor), two groups of insecticides (lindane and breakdown products and dichloro-diphenyl-trichloroethane (DDT) and breakdown products), and several polychlorinated biphenyls commonly used in the central United States was measured. All of these chemicals are reported, in the literature, to be transported in the atmosphere. Many have been reported to occur in boreal and arctic food chains. The sampling was carried out from 16-Jun to 13-Aug-1993 and 04-May to 20-Jul-1994 at the BOREAS site in the Prince Albert National Park (Waskesiu). The data are stored in tabular ASCII files.

Waite, Don↗

NASA NTRS2000

BOREAS TF-9 SSA-OBS Tower Flux, Meteorological, and Soil Temperature Data

The BOREAS TF-9 team collected energy, carbon dioxide, and water vapor flux data at the BOREAS SSA-OBS site during the growing season of 1994 and most of the year for 1996. From the winter of 1995 to 1996, soil temperature data were also collected and provided. The data are available in tabular ASCII files.

Hall, Forrest G.↗

NASA NTRS2000

BOREAS TF-9 SSA-OBS Branch Level Flux Data

The BOREAS TF-9 team collected data that describe carbon dioxide and water vapor fluxes from foliage at the BOREAS SSA-OBS site from 07-April through 23-November-1996. The data are available in tabular ASCII files.

Rayment, Mark B.↗

NASA NTRS2000

BOREAS TGB-8 Monoterpene Concentration Data over the SSA-OBS

The BOREAS TGB-8 team collected data to investigate the controls over NMHC fluxes from boreal forest tree species. This data set contains measurements of monoterpene concentrations in collected foliar gas emissions and foliar samples. The data were collected at the OJP and OBS tower flux sites in the SSA and were the locus for the monoterpene emission measurements. These areas contained mature stands of jack pine and black spruce and were the focal sites in the BOREAS program for studies of biosphere/atmosphere exchange from these two habitat types. The OBS site is situated in a black spruce/sphagnum bog with the largest trees 155 years old and 10-15 m tall. The OJP site is in a jack pine forest, 80 to 120 years old, which lies on a sandy bench of glacial outwash with the largest tree standing 15 m tall. Temporally, the data cover the period of 24-May-1994 to 19-Sep-1994. The data are stored in tabular ASCII files.

Hall, Forrest G.↗

NASA NTRS2000

BOREAS TGB-5 Dissolved Organic Carbon Data from NSA Beaver Ponds

The BOReal Ecosystem-Atmosphere Study Trace Gas Biogeochemistry (BOREAS TGB-5) team collected several data sets related to carbon and trace gas fluxes and concentrations in the Northern Study Area (NSA). This data set contains concentrations of dissolved organic and inorganic carbon species from water samples collected at various NSA sites. In particular, this set covers the NSA Tower Beaver Pond Site and the NSA Gillam Road Beaver Pond Site, including data from all visits to open water sampling locations during the BOREAS field campaigns from April to September 1994. The data are provided in tabular ASCII files.

Bourbonniere, Rick↗

NASA NTRS2000

BOREAS TGB-3 CH4 and CO2 Chamber Flux Data over NSA Upland Sites

The BOReal Ecosystem-Atmosphere Study Trace Gas Biogeochemistry (BOREAS TGB-3) team collected methane and carbon dioxide (CH4, CO2) chamber flux measurements at the Northern Study Area (NSA) Fen, Old Black Spruce (OBS), Young Jack Pine (YJP), and auxiliary sites along Gillam Road and the 1989 burn site. Gas samples were extracted from chambers and analyzed at the NSA lab facility approximately every 7 days during May to September 1994 and June to October 1996. The data are provided in tabular ASCII files.

Savage, Kathleen↗

NASA NTRS2000

BOREAS TGB-3 Plant Species Composition Data over the NSA Fen

The BOReal Ecosystem-Atmosphere Study Trace Gas Biogeochemistry (BOREAS TGB-3) team collected several data sets that contributed to understanding the measured trace gas fluxes over sites in the Northern Study Area (NSA). This data set contains information about the composition of plant species that were within the collars used to measure Net Ecosystem Exchange of CO2 (NEE). The species composition was identified to understand the differences in NEE among the various plant communities in the NSA fen. The data were collected in July of 1994 and 1996. The data are contained in comma-delimited, ASCII files.

Bubier, Jill L.↗

NASA NTRS2000

BOREAS TGB-12 Isotropic Carbon Dioxide Data over the NSA

The BOREAS TGB-12 team made measurements of soil carbon inventories, carbon concentration in soil gases, and rates of soil respiration at several sites to estimate the rates of carbon accumulation and turnover in each of the major vegetation types. This data set contains information on the carbon isotopic content of carbon dioxide sampled from soils in the NSA-OBS, NSA-YJP, and NSA-OJP sites. Data were collected from 14-Nov-1993 to 10-Oct-1996. The data are stored in tabular ASCII files.

Trumbore, Susan↗

NASA NTRS2000

BOREAS TGB-10 Oxidant Flux Data over the SSA

The BOREAS TGB-10 team collected several trace gas data sets in its efforts to determine the role of biogenic hydrocarbon emissions with respect to boreal forest carbon cycles. This oxidant data set contains measured peroxide (H2O2 and total organic peroxides (ROOH)) and ozone concentrations as well as H2O2 and ROOH deposition velocities. These data were obtained at the SSA-OJP site during the summer of 1994. Measurements were made from May to September 1994. The data are stored in tabular ASCII files. Some important results were: (1) Ozone concentrations were consistently low, 20-30 ppb, during the summer of 1994. (2) Peroxide concentrations showed a seasonal variation with highest concentrations occurring in July (IFC-2). (3) Midday H2O2 levels averaged around 1.4 ppb during IFC-2 and 0.4 - 0.5 ppb during IFC's 1 and 3. (4) Midday organic peroxide concentrations were lower, averaging 0.8 ppb during IFC-2, and 0.4 - 0.5 ppb during IFC's 1 and 3. (5) The rough pine forest canopy serves as a significant sink for H2O2. (6) Midday H2O2 deposition velocities averaged 4 - 7 cm/s. (7) Organic peroxide deposition velocities (measured as total ROOH) were approximately 40% as large as those of H2O2.

Hall, Forrest G.↗

NASA NTRS2000

BOREAS TGB-10 Oxidant Concentration Data over the SSA

The BOREAS TGB-10 team collected several trace gas data sets in its efforts to determine the role of biogenic hydrocarbon emissions with respect to boreal forest carbon cycles. This data set contains measured peroxide (H2O2 and total organic peroxides (ROOH)) and ozone concentrations as well as H2O2 and ROOH deposition velocities. These data were obtained at the SSA-OJP site from May to September 1994. The data are stored in tabular ASCII files. Some important results were: (1) Ozone concentrations were consistently low, 20-30 ppb, during the summer of 1994. (2) Peroxide concentrations showed a seasonal variation with highest concentrations occurring in July (IFC-2). (3) Midday H2O2 levels averaged around 1.4 ppb during IFC-2 and 0.4 - 0.5 ppb during IFC's 1 and 3. (4) Midday organic peroxide concentrations were lower, averaging 0.8 ppb during IFC-2, and 0.4 - 0.5 ppb during IFC's 1 and 3. (5) The rough pine forest canopy serves as a significant sink for H2O2. (6) Midday H2O2 deposition velocities averaged 4 - 7 cm/s. (7) Organic peroxide deposition velocities (measured as total ROOH) were approximately 40% as large as those of H2O2.

Hall, Forrest G.↗

NASA NTRS2000

BOREAS TGB-8 Photosynthetic Rate Data over the SSA-OBS and the SSA-OJP

The BOREAS TGB-8 team collected data to investigate the controls over NMHC fluxes from boreal forest tree species. This data set includes measurements of photosynthetic rates at mature jack pine and black spruce sites. The data were collected at the OJP and OBS tower flux locations in the BOREAS SSA. These areas contained mature stands of jack pine and black spruce and were the focal sites in the BOREAS program for studies of biosphere/atmosphere exchange from these two habitat types. The OBS site is situated in a black spruce/sphagnum bog with the largest trees 155 years old and 10-15 m tall. The OJP site is in a jack pine forest, 80 to 120 years old, which lies on a sandy bench of glacial outwash with the largest tree standing 15 m tall. Temporally, the data cover the period of 24-May-1994 to 19-Sep-1994. The data are stored in tabular ASCII files.

Hall, Forrest G.↗