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Results for “KONZA PRAIRIE GRASSLANDS”

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.

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6 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Microwave backscattering and emission model for grass canopies

Microwave radar and radiometer measurements of grasslands indicate a substantial reduction in sensor sensitivity to soil moisture in the presence of a thatch layer. When this layer is wet it masks changes in the underlying soil, making the canopy appear warm in the case of passive sensors (radiometer) and decreasing backscatter in the active case (scatterometer). A model for a grass canopy with thatch will be presented in this paper to explain this behavior and to compare with observations. The canopy model consists of three layers: grass, thatch, and the underlying soil. The grass blades are modeled by elongated elliptical discs and the thatch is modeled as a collection of disk shaped water droplets (i.e., the dry matter is neglected). The ground is homogeneous and flat. The distorted Born approximation is used to compute the radar cross section of this three layer canopy and the emissivity is computed from the radar cross section using the Peake formulation for the passive problem. Results are computed at L-band (1.4 GHz) and C-band (4.75 GHz) using canopy parameters (i.e., plant geometry, soil moisture, plant moisture, etc.) representative of Konza Prairie grasslands. The results are compared to C-band scatterometer measurements and L-band radiometer measurements at these grasslands.

TRT-THEORETICAL↗
NASA NTRS1997

Surface Energy Heat Fluxes Using Remotely Sensed Parameters

Realistic estimates of surface energy heat fluxes are needed for the study of water and energy interactions between the land and atmosphere. The primary objective of this work is to study the estimation of surface heat energy fluxes using remote sensing derived parameters under different spatial and temporal conditions. Surface energy fluxes and remote sensing derived data from two sources were analyzed. First, we used surface heat flux, remote sensing, and ancillary data from the International Satellite Land Surface Climatology Project (ISLSCP), mapped at a 1 deg. x 1 deg. grid. Second, we used NOAA AVHRR (1 km), weather station, and ancillary data to derive estimates of surface latent and sensible heat energy fluxes over a 100 sq kilometers area for three test sites: 1) First ISLSCP Field Experiment (FIFE) grassland site, Konza Prairie, Kansas; 2) Howland, Maine Forest Ecosystem Dynamics Site; and 3) Walnut Gulch, scrubland site, surrounding Tombstone, Arizona. Satellite derived estimates of land surface temperature, surface albedo, and spectral vegetation index are used in selected models to provide estimates of surface heat fluxes. Analysis of results from the 1 deg. x 1 deg. grid for North America indicated there were similar, overall correlations between sensible and latent heat energy fluxes versus remotely sensed vegetation index and ground temperature during dry and wet year conditions. However, there were significant differences in correlations between years when stratified by land cover class. Analysis of 100 km x 100 km data (1 km resolution) indicated partitioning the areas in to primary versus secondary cover, with the secondary cover comprising less than 5% of the area, significantly improved surface heat energy flux estimates.

Toll, David L.↗
NASA NTRS1988

Advanced Solidstate Array Spectroradiometer

During the Summer of 1987, the Advanced Solidstate Array Spectroradiometer (ASAS) was installed and flown on the NASA Ames C-130 in support of the First International Field Experiment (FIFE) missions. The study site was over the grassland areas of the Konza Prairie in Kansas. The data collected with ASAS during these flights has been used to produce the first nearly simultaneous multiangular/multispectral images of selected terrestrial study sites. This data will be valuable in the study of surface bidirectional reflectance and albedo. The data will also be useful for the development of data analysis algorithms for future spaceborne instruments such as the Goddard MODIS-T and JPL's HIRIS. The flight data acquired is further analyzed.

Huegel, F. G.↗
NASA NTRS1992

Spectral bidirectional and hemispherical reflectance characteristics of selected sites in the Streletskaya steppe

Measurements of plant canopy bidirectional reflectance made by the PARABOLA (portable apparatus for rapid acquisition of bidirectional observations of the land and atmosphere) instrument in three spectral bands are analyzed for steppe grassland sites of differing productivity levels. The variation of spectral reflectance and the normalized difference vegetation index in the solar principal plane is presented. Comparisons are made with PARABOLA measurements from selected first ISLSCP field experiment (FIFE) grassland sites in the Konza prairie, Kansas. The Streletskaya steppe sites showed no strong hot spot reflectance, while this effect was present in some FIFE sites but absent in others. The hot spot effect seems to be dependent on canopy geometry and background reflectance characteristics of these sites. Spectral hemispherical reflectance was computed from the angular integration of the bidirectional measurements for the steppe sites. Total shortwave albedo was estimated from these hemispherical reflectance measurements and compared to albedo measured by pyranometers. The albedo estimates from PARABOLA were found to be approximately 12-17 percent higher than the pyranometer measurements.

Eck, Thomas F.↗
NASA NTRS1993

A comparison of spectral mixture analysis an NDVI for ascertaining ecological variables

In this study, we compare the performance of spectral mixture analysis to the Normalized Difference Vegetation Index (NDVI) in detecting change in a grassland across topographically-induced nutrient gradients and different management schemes. The Konza Prairie Research Natural Area, Kansas, is a relatively homogeneous tallgrass prairie in which change in vegetation productivity occurs with respect to topographic positions in each watershed. The area is the site of long-term studies of the influence of fire and grazing on tallgrass production and was the site of the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) from 1987 to 1989. Vegetation indices such as NDVI are commonly used with imagery collected in few (less than 10) spectral bands. However, the use of only two bands (e.g. NDVI) does not adequately account for the complex of signals making up most surface reflectance. Influences from background spectral variation and spatial heterogeneity may confound the direct relationship with biological or biophysical variables. High dimensional multispectral data allows for the application position of techniques such as derivative analysis and spectral curve fitting, thereby increasing the probability of successfully modeling the reflectance from mixed surfaces. The higher number of bands permits unmixing of a greater number of surface components, separating the vegetation signal for further analyses relevant to biological variables.

Wessman, Carol A.↗
NASA NTRS1992

The influence of grazing on surface climatological variables of tallgrass prairie

Mass and energy exchange between most grassland canopies and the atmosphere are mediated by grazing activities. Ambient temperatures can be increased or decreased by grazers. Data have been assembled from simulated grazing experiments on Konza Prairie Research Natural Area and observations on adjacent pastures grazed by cattle show significant changes in primary production, nutrient content, and bidirectional reflectance characteristics as a function of grazing intensity. The purpose of this research was to provide algorithms that would allow incorporation of grazing effects into models of energy budgets using remote sensing procedures. The approach involved: (1) linking empirical measurements of plant biomass and grazing intensities to remotely sensed canopy reflectance, and (2) using a higher resolution, mechanistic grazing model to derive plant ecophysiological parameters that influence reflectance and other surface climatological variables.

Seastedt, T. R.↗