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All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Contribution of Near Real Time MODIS-Based Forest Disturbance Detection Products to a National Forest Threat Early Warning System

This presentation discusses an effort to compute and post weekly MODIS forest change products for the conterminous US (CONUS), as part of national forest threat early warning system (EWS) known as the U.S. Forest Change Assessment Viewer (FCAV). The US Forest Service, NASA, USGS, and ORNL are working collaboratively to contribute weekly change products to this EWS. Large acreages of the nation's forests are being disturbed by a growing multitude of biotic and abiotic threats that can act either singularly or in combination. When common at regional scales, such disturbances can pose hazards and threats to floral and faunal bio-diversity, ecosystem sustainability, ecosystem services, and human settlements across the conterminous US. Regionally evident forest disturbances range from ephemeral periodic canopy defoliation to stand replacement mortality events due to insects, disease, fire, hurricanes, tornadoes, ice, hail, and drought. Mandated by the Healthy Forest Restoration Act of 2003, this forest threat EWS has been actively developed since 2006 and on-line since 2010. This FCAV system employs 250-meter MODIS NDVI-based forest change products as a key element of the system, providing regional and CONUS scale products in near real time every 8 days. Each forest change product in FCAV is based on current versus historical 24 day composite NDVI data gridded at 231.66 meter resolution. Current NDVI is derived from USGS eMODIS expedited products. MOD13 NDVI is used for constructing historical baselines. CONUS change products are computed for all forests as % change in the current versus historical NDVI. Change products are computed according to previous year, previous 3 years and previous 8 year historical baselines. The use of multiple baselines enables disturbance anomaly phenology to be more fully assessed. CONUS forest change products are posted each week on the FCAV, a web mapping service maintained by the National Environmental Modeling and Analysis Center. The FCAV EWS has been used to aid multiple Federal and State agency forest management activities, including aerial disturbance detection surveys, as well as rapid response preliminary assessments of timber loss due to tornadoes, regional drought studies, and fire damage assessments. The FCAV allows end-users to assess the context of apparent forest vegetation change with respect to ancillary data, such as land cover, topography, hydrology, climate variables, and administrative boundaries. Such change products are being evaluated through case studies involving comparison with higher spatial resolution satellite, aerial, and field data. The presentation will include multiple examples in which regionally evident forest disturbances were successfully detected and monitored with the MODIS-based change products, as part of the FCAV. FCAV's MODIS forest change products enable end-users (e.g., resource managers) to monitor forest hazards at regional scales throughout the year and across the nation.

Spruce, Joseph P.↗
NASA NTRS1974

New England reservoir management: Land use/vegetation mapping in reservoir management (Merrimack River Basin)

The author has identified the following significant results. It is evident from this comparison that for land use/vegetation mapping the S190B Skylab photography compares favorably with the RB-57 photography and is much superior to the ERTS-1 and Skylab 190A imagery. For most purposes the 12.5 meter resolution of the S190B imagery is sufficient to permit extraction of the information required for rapid land use and vegetation surveys necessary in the management of reservoir or watershed. The ERTS-1 and S190A data products are not considered adequate for this purpose, although they are useful for rapid regional surveys at the level 1 category of the land use/vegetation classification system.

Cooper, S.↗
NASA NTRS1991

The Geologic Remote Sensing Field Experiment (GRSFE): The first geology multisensor airborne campaign

The primary objective of the Geologic Remote Sensing Field Experiment (GRSFE) is to acquire relevant data for geological sites that can be used to test models for extraction of surface property information from remote sensing data for earth, Mars and Venus in support of the Earth Observing System (EOS), Mars Observer, and Magellan, respectively. Over forty scientists from eight universities and three NASA centers are participating in GRSFE which is co-sponsored by the NASA Planetary Geology and Geophysics Program and the NASA Geology Program. Highlights of the airborne campaign included the first simultaneous acquisition of Airborne Visible and Infrared Imaging Spectrometer (AVRIS) and Thermal Infrared Multispectral Scanner (TIMS) data on September 29, 1989, and acquisition of Advanced Solid-State Array Spectroradiometer (ASAS), Polarimetric Synthetic Aperture Radar (AIRSAR), and Airborne Terrain Laser Altimeter System (ATLAS) data all within three months of each other. The sites covered were Lunar Crater Volcanic Field and Fish Lake Valley in Nevada; and Cima Volcanic Field, Death Valley, and Ubehebe Crater in California. Coincident field measurements included meteorological and atmospheric measurements, visible/near-infrared and thermal spectra, and characterization of geology and vegetation cover. The GRSFE airborne and field data will be reduced to a suite of standard products and submitted, along with appropriate documentation, to the Planetary Data System (PDS) and the Pilot Land Data System (PLDS). These data will be used for a variety of investigations including paleoclimatic studies in the arid southwestern United States, and analysis of Magellan data. GRSFE data will also be used to support Mars Observer Laser Altimeter (MOLA) and Mars Rover Sample Return (MRSR) simulation studies.

Evans, Diane L.↗
NASA NTRS2002

Using Support Vector Machines to Automatically Extract Open Water Signatures from POLDER Multi-Angle Data Over Boreal Regions

This study used Support Vector Machines to classify multiangle POLDER data. Boreal wetland ecosystems cover an estimated 90 x 10(exp 6) ha, about 36% of global wetlands, and are a major source of trace gases emissions to the atmosphere. Four to 20 percent of the global emission of methane to the atmosphere comes from wetlands north of 4 degrees N latitude. Large uncertainties in emissions exist because of large spatial and temporal variation in the production and consumption of methane. Accurate knowledge of the areal extent of open water and inundated vegetation is critical to estimating magnitudes of trace gas emissions. Improvements in land cover mapping have been sought using physical-modeling approaches, neural networks, and active microwave, examples that demonstrate the difficulties of separating open water, inundated vegetation and dry upland vegetation. Here we examine the feasibility of using a support vector machine to classify POLDER data representing open water, inundated vegetation and dry upland vegetation.

Pierce, J.↗
NASA NTRS2013

The GLAS Standard Data Products Specification-Level 1, Version 9

The Geoscience Laser Altimeter System (GLAS) is the primary instrument for the ICESat (Ice, Cloud and Land Elevation Satellite) laser altimetry mission. ICESat was the benchmark Earth Observing System (EOS) mission for measuring ice sheet mass balance, cloud and aerosol heights, as well as land topography and vegetation characteristics. From 2003 to 2009, the ICESat mission provided multi-year elevation data needed to determine ice sheet mass balance as well as cloud property information, especially for stratospheric clouds common over polar areas. It also provided topography and vegetation data around the globe, in addition to the polar-specific coverage over the Greenland and Antarctic ice sheets.This document defines the Level-1 GLAS standard data products. This document addresses the data flow, interfaces, record and data formats associated with the GLAS Level 1 standard data products. GLAS Level 1 standard data products are composed of Level 1A and Level 1B data products. The term standard data products refers to those EOS instrument data that are routinely generated for public distribution. The National Snow and Ice Data Center (NSDIC) distribute these products. Each data product has a unique Product Identification code assigned by the Senior Project Scientist. GLAS Level 1A and Level 1B Data Products are composed from those Level 0 data that have been reformatted or transformed to corrected and calibrated data in physical units at the full instrument rate and resolution.

Lee, Jeffrey E.↗
NASA NTRS1974

Remote sensing in Iowa agriculture: Identification and classification of Iowa's crops, soils and forestry resources using ERTS-1 and complimentary underflight imagery

The author has identified the following significant results. Springtime ERTS-1 imagery covering pre-selected test sites in Iowa showed considerable detail with respect to broad soil and land use patterns. Additional imagery has been incorporated into a state mosaic. The mosaic was used as a base for soil association lines transferred from an existing map. The regions of greatest contrast are between the Clarion-Nicollet-Webster soil association area and adjacent areas. Landscape characteristics in this area result in land use patterns with a high percentage of pasture, hay, and timber. The soil association areas of the state that have patterns interpreted to be associated with intensive row crop production are: Moody, Galva-Primghar-Sac, Clarion-Nicollet-Webter, Tama-Muscatine, Dinsdale-Tama, Cresco-Lourdes, Clyde, Kenyon-Floyd-Clyde, and the Luton-Onawa-Salix area on the Missouri River floodplain. Forestland estimates have been attained for an area in central Iowa using wintertime ERTS-1 imagery. Visual analysis of multispectral, temporal imagery indicates that temporal analysis for cropland identification and acreage analyses procedures may be a very useful tool. Combinations of wintertime, springtime, and summertime ERTS-1 imagery separate most vegetation types. Timing can be critical depending upon crop development and harvesting times because of the dynamic nature of agricultural production.

Mahlstede, J. P.↗
NASA NTRS2016

Benefit of Modeling the Observation Error in a Data Assimilation Framework Using Vegetation Information Obtained From Passive Based Microwave Data

A primary operational goal of the United States Department of Agriculture (USDA) is to improve foreign market access for U.S. agricultural products. A large fraction of this crop condition assessment is based on satellite imagery and ground data analysis. The baseline soil moisture estimates that are currently used for this analysis are based on output from the modified Palmer two-layer soil moisture model, updated to assimilate near-real time observations derived from the Soil Moisture Ocean Salinity (SMOS) satellite. The current data assimilation system is based on a 1-D Ensemble Kalman Filter approach, where the observation error is modeled as a function of vegetation density. This allows for offsetting errors in the soil moisture retrievals. The observation error is currently adjusted using Normalized Difference Vegetation Index (NDVI) climatology. In this paper we explore the possibility of utilizing microwave-based vegetation optical depth instead.

Vegetation↗
NASA NTRS1977

Distinguishing vegetation from soil background information

In aircraft and satellite multispectral scanner data, soil background signals are superimposed on or intermingled with information about vegetation. A procedure which accounts for soil background would, therefore, make a considerable contribution to an operational use of Landsat and other spectral data for monitoring the productivity of range, forest, and crop lands. A description is presented of an investigation which was conducted to obtain information for the development of such a procedure. The investigation included a study of the soil reflectance that supplies the background signal of vegetated surfaces. Landsat data as recorded on computer compatible tapes were used in the study. The results of the investigation are discussed, taking into account a study reported by Kauth and Thomas (1976). Attention is given to the determination of Kauth's plane of soils, sun angle effects, vegetation index modeling, and the evaluation of vegetation indexes. Graphs are presented which show the results obtained with a gray mapping technique. The technique makes it possible to display plant, soil, water, and cloud conditions for any Landsat overpass.

Richardson, A. J.↗
NASA NTRS2022

Process-Oriented Analysis of Dominant Sources of Uncertainty in the Land Carbon Sink

The observed global net land carbon sink is captured by current land models. All models agree that atmospheric CO 2 and nitrogen deposition driven gains in carbon stocks are partially offset by climate and land-use and land-cover change (LULCC) losses. However, there is a lack of consensus in the partitioning of the sink between vegetation and soil, where models do not even agree on the direction of change in carbon stocks over the past 60 years. This uncertainty is driven by plant productivity, allocation, and turnover response to atmospheric CO 2 (and to a smaller extent to LULCC), and the response of soil to LULCC (and to a lesser extent climate). Overall, differences in turnover explain ~70% of model spread in both vegetation and soil carbon changes. Further analysis of internal plant and soil (individual pools) cycling is needed to reduce uncertainty in the controlling processes behind the global land carbon sink.

Attribution↗
NASA NTRSDate not supplied

Quantitative Assessment of the HLS Surface Reflectance Consistency

The Harmonized Landsat and Sentinel-2 (HLS) project produces compatible surface reflectance (SR) from observations acquired by Landsat-8/9 OLI and Sentinel-2A/2B MSI. The HLS harmonization procedures include atmosphere correction, cloud masking, view angle normalization, and bandpass adjustment. The objective of this study is to quantitatively assess the reflectance consistency between Landsat and Sentinel-2 within the Version 2 HLS data. We collected 545 pairs of same-day Landsat/Sentinel-2 images across the globe to represent a wide range of vegetation types and climate regimes. The mean absolute difference (MAD) in reflectance between Landat and Sentinel-2 was calculated as a consistency indicator for each harmonization step. The MAD generally increased after the atmosphere correction, and then greatly decreased after the BRDF and bandpass adjustments, to smaller than the top-of-atmosphere MAD values. The MAD ranged from 0.0048 to 0.0093 for the six common spectral bands (blue, green, red, NIR, SWIR1, and SWIR2) in the final products, only slightly greater than the difference between Landsat and Sentinel-2 calibrations.. An evaluation on a few commonly used vegetation indices also showed good agreement between Landsat and Sentinel-2 reflectance. All these evaluations demonstrate that the HLS project produces a consistent SR dataset from Landsat-OLI and Sentinel-MSI, which will be a valuable resource for a wide range of remote sensing applications.

Qiang Zhou↗
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 NTRS2013

The GLAS Standard Data Products Specification-Data Dictionary, Version 1.0

The Geoscience Laser Altimeter System (GLAS) is the primary instrument for the ICESat (Ice, Cloud and Land Elevation Satellite) laser altimetry mission. ICESat was the benchmark Earth Observing System (EOS) mission for measuring ice sheet mass balance, cloud and aerosol heights, as well as land topography and vegetation characteristics. From 2003 to 2009, the ICESat mission provided multi-year elevation data needed to determine ice sheet mass balance as well as cloud property information, especially for stratospheric clouds common over polar areas. It also provided topography and vegetation data around the globe, in addition to the polar-specific coverage over the Greenland and Antarctic ice sheets.This document contains the data dictionary for the GLAS standard data products. It details the parameters present on GLAS standard data products. Each parameter is defined with a short name, a long name, units on product, type of variable, a long description and products that contain it. The term standard data products refers to those EOS instrument data that are routinely generated for public distribution. These products are distributed by the National Snow and Ice Data Center (NSDIC).

Lee, Jeffrey E.↗
NASA NTRS1977

Generalized vegetation map of north Merrit Island based on a simplified multispectral analysis

A simplified system for classification of multispectral data was used for making a generalized map of ground features of North Merritt Island. Subclassification of vegetation within broad categories yielded promising results which led to a completely automatic method and to the production of satisfactory detailed maps. Changes in an area north of Happy Hammocks are evidently related to water relations of the soil and are not associated with the last winter freeze-damage which affected mainly the mangrove species, likely to reestablish themselves by natural processes. A supplementary investigation involving reflectance studies in the laboratory has shown that the reflectance by detached citrus leaves, of wavelengths lying between 400 microns and 700 microns, showed some variation over a period of seven days during which the leaves were kept in a laboratory atmosphere.

Poonai, P.↗
NASA NTRS1993

Specularly modified vegetation indices to estimate photosynthetic activity

The hypothesis tested was that some part of the ecosystem-dependent variability of vegetation indices was attributable to the effects of light specularly reflected by leaves. 'Minus specular' indices were defined excluding effects of specular light which contains no cellular pigment information. Results, both empirical and theoretical, show that the 'minus specular' indices, when compared to the traditional vegetation indices, potentially provide better estimates of the photosynthetic activity within a canopy - and therefore canopy primary production - specifically as a function of sun and view angles.

Rondeaux, G.↗
NASA NTRS2007

All Source Solution Decision Support Products Created for Stennis Space Center in Response to Hurricane Katrina

In the aftermath of Hurricane Katrina and in response to the needs of SSC (Stennis Space Center), NASA required the generation of decision support products with a broad range of geospatial inputs. Applying a systems engineering approach, the NASA ARTPO (Applied Research and Technology Project Office) at SSC evaluated the Center's requirements and source data quality. ARTPO identified data and information products that had the potential to meet decision-making requirements; included were remotely sensed data ranging from high-spatial-resolution aerial images through high-temporal-resolution MODIS (Moderate Resolution Imaging Spectroradiometer) products. Geospatial products, such as FEMA's (Federal Emergency Management Agency's) Advisory Base Flood Elevations, were also relevant. Where possible, ARTPO applied SSC calibration/validation expertise to both clarify the quality of various data source options and to validate that the inputs that were finally chosen met SSC requirements. ARTPO integrated various information sources into multiple decision support products, including two maps: Hurricane Katrina Inundation Effects at Stennis Space Center (highlighting surge risk posture) and Vegetation Change In and Around Stennis Space Center: Katrina and Beyond (highlighting fire risk posture).

Ross, Kenton W.↗
NASA NTRS2007

Satellite Boreal Measurements over Alaska and Canada During June-July 2004: Simultaneous Measurements of Upper Tropospheric CO, C2H6, HCN, CH3Cl, CH4, C2H2, CH2OH, HCOOH, OCS, and SF6 Mixing Ratios

Simultaneous ACE (Atmospheric Chemistry Experiment) upper tropospheric CO, C2H6, HCN, CH3Cl, CH4 , C2H2 , CH30H, HCOOH, and OCS measurements show plumes up to 185 ppbv (10 (exp -9) per unit volume) for CO, 1.36 ppbv for C2H6, 755 pptv (10(exp -12) per unit volume) for HCN, 1.12 ppbv for CH3C1, 1.82 ppmv, (10(exp -6) per unit volume) for CH4, 0.178 ppbv for C2H2, 3.89 ppbv for CH30H, 0.843 ppbv for HCOOH, and 0.48 ppbv for OCS in western Canada and Alaska at 50 deg N-68 deg N latitude between 29 June and 23 July 2004. Enhancement ratios and emission factors for HCOOH, CH30H, HCN, C2H6, and OCS relative to CO at 250-350 hPa are inferred from measurements of young plumes compared with lower mixing ratios assumed to represent background conditions based on a CO emission factor derived from boreal measurements. Results are generally consistent with the limited data reported for various vegetative types and emission phases measured in extratropical forests including boreal forests. The low correlation between fire product emission mixing ratios and the S176 mixing ratio is consistent with no significant SF6 emissions from the biomass fires.

Rinsland, Curtis P.↗
NASA NTRS1986

Discrimination of natural and cultivated vegetation using Thematic Mapper spectral data

The availability of high quality spectral data from the current suite of earth observation satellite systems offers significant improvements in the ability to survey and monitor food and fiber production on both a local and global basis. Current research results indicate that Landsat TM data when used in either digital or analog formats achieve higher land-cover classification accuracies than MSS data using either comparable or improved spectral bands and spatial resolution. A review of these quantitative results is presented for both natural and cultivated vegetation.

Degloria, Stephen D.↗
NASA NTRS2011

NASA SPoRT Initialization Datasets for Local Model Runs in the Environmental Modeling System

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed several products for its National Weather Service (NWS) partners that can be used to initialize local model runs within the Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). These real-time datasets consist of surface-based information updated at least once per day, and produced in a composite or gridded product that is easily incorporated into the WRF EMS. The primary goal for making these NASA datasets available to the WRF EMS community is to provide timely and high-quality information at a spatial resolution comparable to that used in the local model configurations (i.e., convection-allowing scales). The current suite of SPoRT products supported in the WRF EMS include a Sea Surface Temperature (SST) composite, a Great Lakes sea-ice extent, a Greenness Vegetation Fraction (GVF) composite, and Land Information System (LIS) gridded output. The SPoRT SST composite is a blend of primarily the Moderate Resolution Imaging Spectroradiometer (MODIS) infrared and Advanced Microwave Scanning Radiometer for Earth Observing System data for non-precipitation coverage over the oceans at 2-km resolution. The composite includes a special lake surface temperature analysis over the Great Lakes using contributions from the Remote Sensing Systems temperature data. The Great Lakes Environmental Research Laboratory Ice Percentage product is used to create a sea-ice mask in the SPoRT SST composite. The sea-ice mask is produced daily (in-season) at 1.8-km resolution and identifies ice percentage from 0 100% in 10% increments, with values above 90% flagged as ice.

Case, Jonathan L.↗