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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Temporal trends in earth-atmosphere system reflectance factor for sagebrush steppe vegetation communities

Four consecutive Landsat-5 Thematic Mapper acquisitions were used to examine trends in earth-atmosphere system reflectance factors of sagebrush steppe vegetation communities following soil moisture recharge from snow melt. Significant differences in trends between vegetation communities correspond to known differences in the initiation and duration of active vegetation growth. Information on short-term vegetation processes are a valuable supplement to estimates of total vegetation cover which can be obtained using satellite brightness images at less frequent temporal intervals.

Strong, Laurence L.↗
NASA NTRS1990

Assessment of vegetation change in a fire-altered forest landscape

This research focused on determining the degree to which differences in burn severity relate to postfire vegetative cover within a Michigan pine forest. Landsat MSS data from June 1973 and TM data from October 1982 were classified using an unsupervised approach to create prefire and postfire cover maps of the study area. Using a raster-based geographic information system (GIS), the maps were compared, and a map of vegetation change was created. An IR/red band ratio from a June 1980 Landsat scene was classified to create a map of three degres of burn severity, which was then compared with the vegetation change map using a GIS. Classification comparisons of pine and deciduous forest classes (1973 to 1982) revealed that the most change in vegetation occurred in areas subjected to the most intense burn. Two classes of regenerating forest comprised the majority of the change, while the remaining change was associated with shrub vegetation or another forest class.

Jakubauskas, Mark E.↗
NASA NTRS1989

Analysis of regional-scale vegetation dynamics of Mexico using stratified AVHRR NDVI data

Previous studies have shown that a good relationship exists between AVHRR Normalized Difference Vegetation Index (NDVI) measurements, and both regional-scale patterns of vegetation seasonality and productivity. Most of these studies used known samples of vegetation types. An alternative approach, and the objective was to examine the above relationships by analyzing one year of AVHRR NDVI data that was stratified using a small-scale vegetation map of Mexico. The results show that there is a good relationship between AVHRR NDVI measurements and regional-scale vegetation dynamics of Mexico.

Turcotte, Kevin M.↗
NASA NTRS1991

Geomorphology and reflectance patterns of vegetation-covered dunes at the Tsodilo Hills, north-west Botswana

Seasonal reflectance variations in semigrid environments provide a means of assessing vegetation health and density as well as monitoring landform processes. Multitemporal Landsat Thematic Mapper scenes with field measurements are used to map geomorphology and vegetation density in a stabilized dune environment and to measure seasonal reflectance changes for a series of ten geomorphological and vegetation units on the Kalahari-age linear dunes. Units were chosen based on differences in landform and proportion of trees, forbs and bare soil. Reflectance curves and normalized-difference vegetation indices (NDVI) show that dune crests have the strongest seasonal variability in color and brightness. The geomorphological link with reflectance and NDVI values are linked to biomass production and zoning of vegetation with slope, drainage and subtle soil differences.

Jacobberger, P. A.↗
NASA NTRS1991

Separation of vegetation and rock signatures in Thematic Mapper and polarimetric SAR images

A technique for separating classes of surface roughness and vegetation in semiarid regions using polarimetric synthetic aperture radar (SAR) and Thematic Mapper data is developed. Polarimetric SAR data may be used to separate areas with less than 10 percent vegetation cover where one suite of model inversions may be applicable for derivation of surface roughness. In more vegetated regions, visible/near-infrared data provide a mechanism for determining the relative contribution of vegetation to multiple scattering in the SAR data. Thus, the synergistic use of the two data sets provides a more complete characterization of surface units and cover. This result is critical when trying to monitor dielectric constant variations related to changes in moisture content of soil and vegetation cover in arid to semiarid regions. A strategy for automating a procedure for measurement of surface roughness is proposed.

Evans, Diane L.↗
NASA NTRS1991

Inferring vegetation characteristics using a knowledge-based system

A knowledge-based system for inferring physical and biological surface properties of vegetation using nadir and/or directional reflectance data as input is developed. A portion of this system has been developed to discriminate between user-defined vegetation classes using spectral and directional reflectance relationships. This discrimination program was used to classify targets into user-defined ground cover and plant height classes. The program learns class descriptors from samples (both positive and negative) of spectral, directional reflectance data of natural surfaces (bare soils, natural vegetation, and agricultural vegetation). The system is designed to handle any combination of directional view angles. The explicit relationships used in the class descriptions include greater-than relationships between combinations of two view angles and maximum and minimum value relationships. The class descriptions are used to classify an unknown target using the same directional views. The program was tested by learning class descriptions of various categories of percent ground cover and vegetation height.

Kimes, D. S.↗
NASA NTRS1992

Extraction of soil and vegetation parameters from high resolution bi-directional reflectance spectra

High spectral resolution reflectance spectra were collected over a semi-desert grassland at both dry and wet season periods. Spectral reflectance measurements were made from several viewing angles at both low and high solar zenith angles. A mixture model was used to separate and extract green vegetation from dry/dead vegetation and soil. The extracted vegetation signal varied greatly with view and sun angle variations such that off-nadir viewing and illuminating angles resulted in the highest vegetation loadings. These variations were normalized with cosine functions for both sun and view angle. These results offer a methodology for standardizing multi-temporal and multi-angular satellite measurements of vegetation activity.

Huete, A. R.↗
NASA NTRS1993

Radar response of vegetation: An overview

This document contains a number of viewgraphs on surface and vegetation backscattering. A classification of vegetation based on general scattering properties is presented. Radar scattering mechanisms are discussed, and backscattering and reflection coefficients for soil back scattering models are given. Radar response to vegetation is presented, with the objectives to discriminate and classify vegetation; to estimate biomass, leaf area index (LAI), and soil moisture; and to monitor changes, including deforestation and growth. Both theory and observation (laboratory, field, air SAR, and European Remote Sensing Satellite (ERS-1) observations) are used to present backscatter coefficients and other data for various vegetation types. ERS-1 results include class statistics, comparison with theory, and biomass response and seasonal variation (LAI) for deciduous and coniferous forests.

Ulaby, Fawwaz T.↗
NASA NTRS1993

Mapping and monitoring changes in vegetation communities of Jasper Ridge, CA, using spectral fractions derived from AVIRIS images

An important application of remote sensing is to map and monitor changes over large areas of the land surface. This is particularly significant with the current interest in monitoring vegetation communities. Most of traditional methods for mapping different types of plant communities are based upon statistical classification techniques (i.e., parallel piped, nearest-neighbor, etc.) applied to uncalibrated multispectral data. Classes from these techniques are typically difficult to interpret (particularly to a field ecologist/botanist). Also, classes derived for one image can be very different from those derived from another image of the same area, making interpretation of observed temporal changes nearly impossible. More recently, neural networks have been applied to classification. Neural network classification, based upon spectral matching, is weak in dealing with spectral mixtures (a condition prevalent in images of natural surfaces). Another approach to mapping vegetation communities is based on spectral mixture analysis, which can provide a consistent framework for image interpretation. Roberts et al. (1990) mapped vegetation using the band residuals from a simple mixing model (the same spectral endmembers applied to all image pixels). Sabol et al. (1992b) and Roberts et al. (1992) used different methods to apply the most appropriate spectral endmembers to each image pixel, thereby allowing mapping of vegetation based upon the the different endmember spectra. In this paper, we describe a new approach to classification of vegetation communities based upon the spectra fractions derived from spectral mixture analysis. This approach was applied to three 1992 AVIRIS images of Jasper Ridge, California to observe seasonal changes in surface composition.

Sabol, Donald E., Jr.↗
NASA NTRS1993

Relationships between evaprorative fraction and remotely sensed vegetation index and microwave brightness temperature for semiarid rangelands

Measurements of the microwave brightness temperature (TB) with the Pushbroom Microwave Radiometer (PBMR) over the Walnut Gulch Experiment Watershed were made on selected days during the MONSOON 90 field campaign. The PBMR is an L-band instrument (21-cm wavelength) that can provide estimates of near-surface soil moisture over a variety of surfaces. Aircraft observations in the visible and near-infrared wavelengths collected on selected days also were used to compute a vegetation index. Continuous micrometeorological measurements and daily soil moisture samples were obtained at eight locations during experimental period. Two sites were instrumented with time domain reflectometry probes to monitor the soil moisture profile. The fraction of available energy used for evapotranspiration was computed by taking the ratio of latent heat flux (LE) to the sum of net radiation (Rn) and soil heat flux (G). This ratio is commonly called the evaporative fraction (EF) and normally varies between 0 and 1 under daytime convective conditions with minimal advection. A wide range of environmental conditions existed during the field campaign, resulting in average EF values for the study area varying from 0.4 to 0.8 and values of TB ranging from 220 to 280 K. Comparison between measured TB and EF for the eight locations showed an inverse relationship. Other days were included in the analysis by estimating TB with the soil moisture data. Because transpiration from the vegetation is more strongly coupled to root zone soil moisture, significant scatter in this relationship existed at high values of TB or dry near-surface soil moisture conditions. The variation in EF under dry near-surface soil moisture conditions was correlated to the amount of vegetation cover estimated with a remotely sensed vegetation index. These findings indicate that information obtained from optical and microwave data can be used for quantifying the energy balance of semiarid areas. The microwave data can indicate when soil evaporation is significantly contributing to EF, while the optical data is helpful for quantifying the spatial variation in EF due to the distribution of vegetation cover.

Kustas, W. P.↗
NASA NTRS1995

Thermal remote sensing of surface soil water content with partial vegetation cover for incorporation into climate models

This study outlines a method for the estimation of regional patterns of surface moisture availability (M(sub 0)) and fractional vegetation (Fr) in the presence of spatially variable vegetation cover. The method requires relating variations in satellite-derived (NOAA, Advanced Very High Resolution Radiometer (AVHRR)) surface radiant temperature to a vegetation index (computed from satellite visible and near-infrared data) while coupling this association to an inverse modeling scheme. More than merely furnishing surface soil moisture values, the method constitues a new conceptual and practical approach for combining thermal infrared and vegetation index measurements for incorporating the derived values of M(sub 0) into hydrologic and atmospheric prediction models. Application of the technique is demonstrated for a region in and around the city of Newcastle upon Tyne situated in the northeast of England. A regional estimate of M(sub 0) is derived and is probabbly good for fractional vegetation cover up to 80% before errors in the estimated soil water content become unacceptably large. Moreover, a normalization scheme is suggested from which a nomogram, `universal triangle,' is constructed and is seen to fit the observed data well. The universal triangle also simplifies the inclusion of remotely derived M(sub 0) in hydrology and meteorological models and is perhaps a practicable step toward integrating derived data from satellite measurements in weather forecasting.

Gillies, Robert R.↗
NASA NTRS1996

The Application of Remote Sensing Data to GIS Studies of Land Use, Land Cover, and Vegetation Mapping in the State of Hawaii

A land cover-vegetation map with a base classification system for remote sensing use in a tropical island environment was produced of the island of Hawaii for the State of Hawaii to evaluate whether or not useful land cover information can be derived from Landsat TM data. In addition, an island-wide change detection mosaic combining a previously created 1977 MSS land classification with the TM-based classification was produced. In order to reach the goal of transferring remote sensing technology to State of Hawaii personnel, a pilot project was conducted while training State of Hawaii personnel in remote sensing technology and classification systems. Spectral characteristics of young island land cover types were compared to determine if there are differences in vegetation types on lava, vegetation types on soils, and barren lava from soils, and if they can be detected remotely, based on differences in pigments detecting plant physiognomic type, health, stress at senescence, heat, moisture level, and biomass. Geographic information systems (GIS) and global positioning systems (GPS) were used to assist in image rectification and classification. GIS was also used to produce large-format color output maps. An interactive GIS program was written to provide on-line access to scanned photos taken at field sites. The pilot project found Landsat TM to be a credible source of land cover information for geologically young islands, and TM data bands are effective in detecting spectral characteristics of different land cover types through remote sensing. Large agriculture field patterns were resolved and mapped successfully from wildland vegetation, but small agriculture field patterns were not. Additional processing was required to work with the four TM scenes from two separate orbits which span three years, including El Nino and drought dates. Results of the project emphasized the need for further land cover and land use processing and research. Change in vegetation composition was noted in the change detection image.

Hogan, Christine A.↗
NASA NTRS1999

Vegetation Interaction Enhances Interdecadal Climate Variability in the Sahel

The role of naturally varying vegetation in influencing the climate variability in the Sahel is explored in a coupled atmosphere-land-vegetation model. The Sahel rainfall variability is influenced by sea surface temperature (SST) variations in the oceans. Land-surface feedback is found to increase this variability both on interannual and interdecadal time scales. Interactive vegetation enhances the interdecadal variation significantly, but can reduce year to year variability due to a phase lag introduced by the relatively slow vegetation adjustment time. Variations in vegetation accompany the changes in rainfall, in particular, the multi-decadal drying trend from the 1950s to the 80s.

Zeng, Ning↗
NASA NTRS1994

Extraction of Dry Leaf Spectral Features from Reflectance Spectra of Green Vegetation

Reflectance spectra of green vegetation in the 1.4-2.5 micrometer region are dominated by liquid water absorptions. In this article, we describe the analysis of a set of reflectance spectra of green vegetation, dry vegetation, and liquid water measured in a laboratory using a nonlinear least squares spectral matching technique. We conclude that both the liquid water and the dry materials contribute to the reflectance spectra of green vegetation in the 1.0-2.5 micrometer region. Our matching of data acquired with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over two vegetated areas in Oregon Transect with a pure water spectrum also shows a residual absorption feature near 1.72 micrometers.

Gao, Bo-Cai↗
NASA NTRS2006

Meeting Report: Long Term Monitoring of Global Vegetation using Moderate Resolution Satellites

The international community has long recognized the need to coordinate observations of Earth from space. In 1984, this situation provided the impetus for creating the Committee on Earth Observation Satellites (CEOS), an international coordinating mechanism charged with coordinating international civil spaceborne missions designed to observe and study planet Earth. Within CEOS, its Working Group on Calibration and Validation (WGCV) is tasked with coordinating satellite-based global observations of vegetation. Currently, several international organizations are focusing on the requirements for Earth observation from space to address key science questions and societal benefits related to our terrestrial environment. The Global Vegetation Workshop, sponsored by the WGCV and held in Missoula, Montana, 7-10 August, 2006, was organized to establish a framework to understand the inter-relationships among multiple, global vegetation products and identify opportunities for: 1) Increasing knowledge through combined products, 2) Realizing efficiency by avoiding redundancy, and 3) Developing near- and long-term plans to avoid gaps in our understanding of critical global vegetation information. The Global Vegetation Workshop brought together 135 researchers from 25 states and 14 countries to advance these themes and formulate recommendations for CEOS members and the Global Earth Observation System of Systems (GEOSS). The eighteen oral presentations and most of the 74 posters presented at the meeting can be downloaded from the meeting website (www.ntsg.umt.edu/VEGMTG/). Meeting attendees were given a copy of the July 2006 IEEE Transactions on Geoscience and Remote Sensing Special Issue on Global Land Product Validation, coordinated by the CEOS Working Group on Calibration and Validation (WGCV). This issue contains 29 articles focusing on validation products from several of the sensors discussed during the workshop.

Morisette, Jeffrey↗
NASA NTRS2007

North American Vegetation Dynamics Observed with Multi-Resolution Satellite Data

North American vegetation has been discovered to be a net carbon sink, with atypical behavior of drawing down more carbon from the atmosphere during the past century. It has been suggested that the Northern Hemisphere will respond favorably to climate warming by enhancing productivity and reducing the impact of fossil fuel emissions into the atmosphere. Many investigations are currently underway to understand and identify mechanisms of storage so they might be actively managed to offset carbon emissions which have detrimental consequences to the functioning of ecosystems and human well being. This paper used a time series of satellite data from multiple sensors at multiple resolutions over the past thlrty years to identify and understand mechanisms of change to vegetation productivity throughout North America. We found that humans had a marked impact to vegetation growth in half of the six selected study regions which cover greater than two million km2. We found climatic influences of increasing temperatures, and longer growing seasons with reduced snow cover in the northern regions of North America with forest fire recovery in the Northern coniferous forests of Canada. The Mid-latitudes had more direct land cover changes induced by humans coupled with climatic influences such as severe drought and altered production strategies of rain-fed agriculture in the upper Midwest, expansion of irrigated agriculture in the lower Midwest, and insect outbreaks followed by subsequent logging in the upper Northeast. Vegetation growth over long time periods (20+ years) in North America appears to be associated with long term climate change but most of the marked changes appear to be associated with climate variability on decadal and shorter time scales along with direct human land cover conversions. Our results document regional land cover land use change and climatic influences that have altered continental scale vegetation dynamics in North America.

Neigh, Christopher S. R.↗
NASA NTRS2007

Advanced NASA Earth Science Mission Concept for Vegetation 3D Structure, Biomass and Disturbance

Carbon in forest canopies represents about 85% of the total carbon in the Earth's aboveground biomass (Olson et al., 1983). A major source of uncertainty in global carbon budgets derives from large errors in the current estimates of these carbon stocks (IPCC, 2001). The magnitudes and distributions of terrestrial carbon storage along with changes in sources and sinks for atmospheric C02 due to land use change remain the most significant uncertainties in Earth's carbon budget. These uncertainties severely limit accurate terrestrial carbon accounting; our ability to evaluate terrestrial carbon management schemes; and the veracity of atmospheric C02 projections in response to further fossil fuel combustion and other human activities. Measurements of vegetation three-dimensional (3D) structural characteristics over the Earth's land surface are needed to estimate biomass and carbon stocks and to quantify biomass recovery following disturbance. These measurements include vegetation height, the vertical profile of canopy elements (i.e., leaves, stems, branches), andlor the volume scattering of canopy elements. They are critical for reducing uncertainties in the global carbon budget. Disturbance by natural phenomena, such as fire or wind, as well as by human activities, such as forest harvest, and subsequent recovery, complicate the quantification of carbon storage and release. The resulting spatial and temporal heterogeneity of terrestrial biomass and carbon in vegetation make it very difficult to estimate terrestrial carbon stocks and quantify their dynamics. Vegetation height profiles and disturbance recovery patterns are also required to assess ecosystem health and characterize habitat. The three-dimensional structure of vegetation provides habitats for many species and is a control on biodiversity. Canopy height and structure influence habitat use and specialization, two fundamental processes that modify species richness and abundance across ecosystems. Accurate and consistent 3D measurements of forest structure at the landscape scale are needed for assessing impacts to animal habitats and biodiversity following disturbance.

Ranson, K. Jon↗
NASA NTRS2010

The Effect of Incident Light Polarization on Vegetation Bidirectional Reflectance Factor

The Laboratory-based Bidirectional Reflectance Factor (BRF) polarization study of vegetation is presented in this paper. The BRF was measured using a short-arc Xenon lamp/monochromator assembly producing an incoherent, tunable light source with a well-defined spectral bandpass at visible and near-infrared wavelengths of interest at 470 nm and 870 nm and coherent light source at 1.656 microns. All vegetation samples were measured using P and S linearly polarized incident light over a range of incident and scatter angles. By comparing these results, we quantitatively examine how the BRF of the samples depends on the polarization of the incident light. The differences are significant, depend strongly on the incident and scatter angles, and can be as high as 120% at 67 deg incident and 470nm. The global nature of Earth's processes requires consistent long-term calibration of all instruments involved in data retrieval. The BRF defines the reflection characteristics of Earth surface. It provides the reflectance of a target in a specific direction as a function of illumination and viewing geometry. The BRF is a function of wavelength and reflects the structural and optical properties of the surface. Various space and airborne radiometric and imaging remote sensing instruments are used in the remote sensing characterization of vegetation canopies and soils, oceans, or especially large pollution sources. The satellite data is validated through comparison with airborne, ground-based and laboratory-based data in an effort to fully understand the vegetation canopy reflectance, The Sun's light is assumed to be unpolarized at the top of the atmosphere; however it becomes polarized to some degree due to atmospheric effects by the time it reaches the vegetation canopy. Although there are numerous atmospheric correction models, laboratory data is needed for model verification and improvement.

Georgiev, Georgi T.↗