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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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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Remote sensing of earth terrain

A systematic approach for the identification of terrain media such as vegetation canopy, forest, and snow covered fields is developed using the optimum polarimetric classifier. The covariance matrices for the various terrain covers are computed from the theoretical models of random medium by evaluating the full polarimetric scattering matrix elements. The optimal classification scheme makes use of a quadratic distance measure and is applied to classify a vegetation canopy consisting of both trees and grass. Experimentally measured data are used to validate the classification scheme. Theoretical probability of classification error using the full polarimetric matrix are compared with classification based on single features including the phase difference between the VV and HH polarization returns. It is shown that the full polarimetric results are optimal and provide better classification performance than single feature measurements. A systematic approach is presented for obtaining the optimal polarimetric matched filter which produces maximum contrast between two scattering classes, each represented by its respective covariance matrix.

Kong, J. A.↗
NASA NTRS1972

Prediction of directional reflectance of a corn field under stress

A vegetative canopy model concept is developed and used to calculate the directional spectral reflectance of a corn field under stress. The problem has been idealized by assuming that the canopy is represented in several layers of uniform but randomly distributed biological components; horizontal and vertical projection of leaves, for example, replaces the actual leaf. An accumulative horizontal projection leads to a quantitative horizontal leaf area index while accumulated vertical projections provide the vertical leaf index area for each layer. The spectral properties of the projections are obtained from the spectral properties of the biological components. These techniques together with soil reflectance data provide a physical description for the vegetative canopy and adequately interprete multispectral scanning data.

Suits, G. H.↗
NASA NTRS1981

Microwave response of vegetation

The radar backscatter behavior is discussed as a function of the vegetation geometrical and electrical properties. Experimental data covering the 1-18 GHz region are used to model the vegetation canopy as a water cloud, evaluate the attenuation of the canopy, and generate a vegetation clutter model describing the statistical distribution of vegetation backscatter under a wide range of environmental conditions. The use of radar in conjunction with optical sensors for crop identification is then discussed. Analysis of studies conducted to date indicates that the observation angle should be in the 50-70 deg range (from nadir) and the frequency should be higher than 8 GHz.

Ulaby, F. T.↗
NASA NTRS1983

Remote sensing of agricultural crops and soils

Research in the correlative and noncorrelative approaches to image registration and the spectral estimation of corn canopy phytomass and water content is reported. Scene radiation research results discussed include: corn and soybean LANDSAT MSS classification performance as a function of scene characteristics; estimating crop development stages from MSS data; the interception of photosynthetically active radiation in corn and soybean canopies; costs of measuring leaf area index of corn; LANDSAT spectral inputs to crop models including the use of the greenness index to assess crop stress and the evaluation of MSS data for estimating corn and soybean development stages; field research experiment design data acquisition and preprocessing; and Sun-view angles studies of corn and soybean canopies in support of vegetation canopy reflection modeling.

Bauer, M. E.↗
NASA NTRS2017

Hyperspectral Radiative Transfer Modeling to Explore the Combined Retrieval of Biophysical Parameters and Canopy Fluorescence from FLEX - Sentinel-3 Tandem Mission Multi-Sensor Data

The FLuorescence EXplorer (FLEX) satellite mission, selected as ESA's 8th Earth Explorer, has been designed forthe measurement of sun-induced fluorescence (F) spectra emitted by plants. This will be accomplished through amulti-sensor approach by placing it in a common orbit in tandem with the Sentinel-3 (S3) mission, which willhave two optical sensors on board, OLCI (Ocean and Land Colour Instrument) and SLSTR (Sea and Land SurfaceTemperature Radiometer) to complement FLEX. These S3 instruments will be used in combination with theimaging spectrometers on board FLEX to provide data useful for atmospheric correction of FLEX data. However,a fully synergetic approach, i.e. by exploiting the spectral and directional information from all tandem missioninstruments together, is an attractive alternative which is explored in this paper. By employing all combined topof-atmosphere (TOA) spectral radiance data, one can (i) characterize the relevant optical properties of the atmosphere,(ii) retrieve biophysical canopy properties including the associated reflectance anisotropy, and (iii)retrieve a more accurate and consistent canopy F.Regarding retrieval methods, Fraunhofer Line Depth (FLD) and Spectral Fitting (SF) are well-known techniquesapplied to hyperspectral data. Both methods depend on a high spectral resolution and assume aLambertian (isotropic) canopy reflectance. However, most vegetation canopies are non-Lambertian. This impliesthat, in particular when ignoring the anisotropic surface reflection, substantial retrieval errors can occur due tothe interaction between atmospheric absorption bands and surface reflectance anisotropy. In this paper, a novelmethod based on spectral radiative transfer (RT) modeling is proposed, in which coupled RT models are used tosimulate TOA radiance spectra. These are then matched with ‘measured' spectra in order to retrieve surfacefluorescence, along with a suite of biophysical parameters, by model inversion through optimization. By applyingcoupled RT models of the soil-leaf-canopy and the surface-atmosphere systems, TOA radiance spectra canbe simulated for all optical sensors of this tandem mission. In this way, complex effects due to surface reflectanceanisotropy and the spectral sampling by the various instruments, which are difficult to compensate for in the endproducts, are properly taken into account by their incorporation in the forward modeling. Next, by model inversionof TOA radiance data via optimization, the most accurate F retrievals can be achieved in a consistentmanner, along with important canopy level biophysical parameters that may help interpret the F spectrum, suchas chlorophyll content and leaf area index (LAI). The potential of this approach has been explored in a numericalexperiment, and the results are presented in this paper. We find that, with the assumed well-characterized andplausible FLEX/S3 instrument performances, the simultaneous retrieval of biophysical canopy parameters and Fspectra would be possible with a remarkable accuracy, provided the correct atmospheric characterization isavailable.

Verhoef, Wouter↗
NASA NTRS1994

The reflection for dense plant canopies from the one-angle radiative transfer equation

An essential component of remote sensing of vegetation canopies from satellites is fundamental understanding. Since passive remote is driven by photons, the modeling of photon interactions with vegetation is a basic building block in that understanding. Several such photon transport models have been developed during the past two decades and continue to be developed. Different approaches have been followed including monte carlo, radiosity methods, geometric shadowing, and radiative transfer. In general, each approach has application for canopies with specific attributes. This presentation concerns the application of radiative transfer to dense vegetation canopies in which the soil does not participate. The approach taken here is novel in that a consistent theory for photon transport for non-rotationally invariant leaf scattering is developed in a canopy with a general leaf angle distribution (LAD). The theory is limited to the one-angle approximation (azimuthally averaged radiance) and is based on Chandrasekhar's analytical theory. While such a model is admittedly only approximate, it does fulfill a unique function in our search for understanding. In particular, the model is simple in its construct yet contains the essential features of canopy architecture that are mainly responsible for observed responses. Thus, this model will not only be a predictive tool but also an educational one. The mathematical setting is the radiative transfer equation in a dense (semiinfinite) canopy. The leaf scattering phase function is assumed to be Lambertian with different reflectance and transmittance. In addition, abaxial and adaxial differentiation is allowed which effectively destroys optical reciprocity. The analytical solution for the canopy BRDF is obtained by manipulation of the integral transport equation (a la Chandrasekhar) for a general LAD. With discretization of the. leaf angle, the resulting set of integral equations are solved iteratively including an acceleration procedure when the single scatter albedo is near one (in the NIR). Results will be compared to the LARS soybean canopy radiances as well as to broadleaf results from a recent Ames experiment.

Ganapol, B. D.↗
NASA NTRS2008

Stochastic Transport Theory for Investigating the Three-Dimensional Canopy Structure from Space Measurements

Radiation reflected from vegetation canopies exhibits high spatial variation. Satellite-borne sensors measure the mean intensities emanating from heterogeneous vegetated pixels. The theory of radiative transfer in stochastic media provides the most logical linkage between satellite observations and the three-dimensional canopy structure through a closed system of simple equations which contains the mean intensity and higher statistical moments directly as its unknowns. Although this theory has been a highly active research field in recent years, its potential for satellite remote sensing of vegetated surfaces has not been fully realized because of the lack of models of a canopy pair-correlation function that the stochastic radiative transfer equations require. The pair correlation function is defined as the probability of finding simultaneously phytoelements at two points. This paper presents analytical and Monte Carlo generated pair correlation functions. Theoretical and numerical analyses show that the spatial correlation between phytoelements is primarily responsible for the effects of the three-dimensional canopy structure on canopy reflective and absorptive properties. The pair correlation function, therefore, is the most natural and physically meaningful measure of the canopy structure over a wide range of scales. The stochastic radiative transfer equations naturally admit this measure and thus provide a powerful means to investigate the three-dimensional canopy structure from space. Canopy reflectances predicted by the stochastic equations are assessed by comparisons with the PARABOLA measurements from coniferous and broadleaf forest stands in the BOREAS Southern Study Areas. The pair correlation functions are derived from data on tree structural parameters collected during field campaigns conducted at these sites. The simulated canopy reflectances compare well with the PARABOLA data.

Huang, Dong↗
NASA NTRS1981

Effect of sun and sensor geometry, canopy structure and density, and atmospheric condition on the spectral response of vegetation, with particular emphasis on across-track pointing

A computer modeling and simulation study carried out to assess the effects of various sun and sensor geometries and atmospheric conditions on the directional reflected radiance of several vegetated targets is described. Spectral responses at two wavelengths, 0.68 micron and 0.80 micron, are simulated at nine sensor zenith angles, five sensor azimuths, and nine solar zenith angles for six vegetation canopies under three atmspheric conditions. The six canopies comprise two different geometries of grass canopies at low, medium, and high leaf density. The results suggest that off-nadir viewing effects are more pronounced in the red than in the IR. However, the use of such transformations as the normalized difference index is found to reduce much of the variability seen in the bands. The magnitude of off-nadir viewing effects is found to be a function of canopy geometry.

Schnetzler, C. C.↗
NASA NTRS1975

Signature extension for sun angle, volume 1

The author has identified the following significant results. Within a restricted zenith sun angle range of 35 - 50 degrees, it was empirically observed that canopy reflectance is mainly Lambertian. Reflectance changes with crop stage were simple shifts in scale in the sun angle range. It was noted that sun angle variations depend on canopy characteristics. Effects of the vegetative canopy were most pronounced at the larger solar zenith angles (20 %). The linear sun angle correction coefficients demonstrate a dependency on both crop stage (15-20 %) and crop type (10-20 %). The use of canopy reflectance modeling allowed for the generation of a simulated data set over an extremely broad envelope of sun angles.

Smith, J. A.↗
NASA NTRS1983

Radar remote sensing for crop classification and canopy condition assessment: Ground-data documentation

A vegetation and soil-moisture experiment was conducted in order to examine the microwave emission and backscattering from vegetation canopies and soils. The data-acquisition methodology used in conjunction with the mobile radar scatterometer (MRS) systems is described and associated ground-truth data are documented. Test fields were located in the Kansas River floodplain north of Lawrence, Kansas. Ten fields each of wheat, corn, and soybeans were monitored over the greater part of their growing seasons. The tabulated data summarize measurements made by the sensor systems and represent target characteristics. Target parameters describing the vegetation and soil characteristics include plant moisture, density, height, and growth stage, as well as soil moisture and soil-bulk density. Complete listings of pertinent crop-canopy and soil measurements are given.

Ulaby, F. T.↗
NASA NTRS1975

Yield prediction by analysis of multispectral scanner data

A preliminary model describing the growth and grain yield of wheat was developed. The modeled growth characteristics of the wheat crop were used to compute wheat canopy reflectance using a model of vegetation canopy reflectance. The modeled reflectance characteristics were compared with the corresponding growth characteristics and grain yield in order to infer their relationships. It appears that periodic wheat canopy reflectance characteristics potentially derivable from earth satellites will be useful in forecasting wheat grain yield.

Colwell, J. E.↗
NASA NTRS1986

Patterns of vegetation in the Owens Valley, California

Spectral characteristics of semi-arid shrub communities were examined using Airborne Imaging Spectrometer (AIS) data collected in the tree mode on 23 May 1985. Mesic sites with relatively high vegetation density and distinct zonation patterns exhibited greater spectral signature variations than sites with more xeric shrub communities. Spectral signature patterns were not directly related to vegetation density or physiognomy, although spatial maps derived from an 8-channel maximum likelihood classification were supported by photo-interpreted surface features. In AIS data, the principal detected effect of shrub vegetation on the alluvial fans is to lower reflectance across the spectrum. These results are similar to those reported during a period of minimal physiological activity in autumn, indicating that shadows cast by vegetation canopies are an important element of soil-vegetation interaction under conditions of relatively low canopy cover.

Ustin, S. L.↗
NASA NTRS2020

SMAP Detects Soil Moisture under Temperate Forest Canopies

Soil moisture dynamics in the presence of dense vegetation canopies are determinants of ecosystem function and biogeochemical cycles, but the capability of existing spaceborne sensors to support reliable and useful estimates is not known. New results from a recently initiated field experiment in the northeast United States show that the NASA SMAP (Soil Moisture Active Passive) satellite is capable of retrieving soil moisture under temperate forest canopies. We present an analysis demonstrating that a parameterized emission model with the SMAP morning overpass brightness temperature resulted in a RMSD (root mean square difference) range of 0.047-0.057 m(exp 3)/m(exp 3) and a Pearson correlation range of 0.75-0.85 depending on the experiment location and the SMAP polarization. The inversion approach included a minimal amount of ancillary data. This result demonstrates unequivocally that spaceborne L-band radiometry is sensitive to soil moisture under temperate forest canopies, which has been uncertain because of lack of representative reference data.

Andreas Colliander↗
NASA NTRS1990

Modeling of interactions between biosphere and atmosphere on the global scale

Simulations of weather and climate with general circulation models show that the circulation and rainfall are sensitive to the transfers of radiation, sensible heat, water vapor, and momentum across the atmosphere land surface interface. Because, in nature, these transfers depend in large measure on the morphological and physiological characteristics of the surface vegetation, an interactive biosphere is needed for GCM's. The simple model of the biosphere (SiB) that the authors have constructed is based on the recognized difference between ground cover vegetation (grasses and other herbaceous plants) and canopy vegetation (trees and shrubs), where the latter act like elevated blocks of porous material which efficiently extract momentum from the air that flows through them; by a large number of multiple reflections enhance the absorption of the incident solar radiation; when the canopy is wet, act like well ventilated psychrometers which extract sensible heat from the air and produce a negative Bowen ratio; and, in all of these ways, behave differently from ground cover vegetation. The complete set of governing equations of SiB, whereby the various allowable combinations of trees, ground covers, and bare ground, in interaction with the atmosphere, determine all of the vegetation dependent transfers at the land surface, have been presented and described.

Baer, Ferdinand↗
NASA NTRS2021

Scaling photosynthetic function and CO2 dynamics from leaf to canopy level for maize – dataset combining diurnal and seasonal measurements of vegetation fluorescence, reflectance and vegetation indices with canopy gross ecosystem productivity

Recent advances in leaf fluorescence measurements and canopy proximal remote sensing currently enable the non-destructive collection of rich diurnal and seasonal time series, which are required for monitoring vegetation function at the temporal and spatial scales relevant to the natural dynamics of photosynthesis. Remote sensing assessments of vegetation function have traditionally used actively excited foliar chlorophyll fluorescence measurements, canopy optical reflectance data and vegetation indices (VIs), and only recently passive solar induced chlorophyll fluorescence (SIF) measurements. In general, reflectance data are more sensitive to the seasonal variations in canopy chlorophyll content and foliar biomass, while fluorescence observations more closely relate to the dynamic changes in plant photosynthetic function. With this dataset we link leaf level actively excited chlorophyll fluorescence, canopy proximal reflectance and SIF, with eddy covariance measurements of gross ecosystem productivity (GEP). The dataset was collected during the 2017 growing season on maize, using three automated systems (i.e., Monitoring Pulse-Amplitude-Modulation fluorimeter, Moni-PAM; Fluorescence Box, FloX; and from eddy covariance tower). The data were quality checked, filtered and collated to a common 30 minutes timestep. We derived vegetation indices related to canopy functioning (e.g., Photochemical Reflectance Index, PRI; Normalized Difference Vegetation Index, NDVI; Chlorophyll Red-edge, Clre) to investigate how SIF and VIs can be coupled for monitoring vegetation photosynthesis. The raw datasets and the filtered and collated data are provided to enable new processing and analyses.

Petya Campbell↗
NASA NTRS1993

Retrieval of Surface Directional Reflectance and Hemispherical Albedo Using Multi-angle Measurements, I. Ground Level Observations

Knowledge of the directional reflectance properties of natural surfaces such as soils and vegetation canopies is essential for classification studies and canopy model inversions. Atmospheric correction schemes, using various levels of approximation, are described to retrieve surface bidirectional reflectance factors (BRFs) and directional-hemispherical reflectances (albedos) from multi-angle radiance measurements taken at ground level.

factors (BRFs) radiometric calibration sun-view an↗
NASA NTRS1992

The application of the principles of invariance to the radiative transfer equation in plant canopies

Solutions of the radiative transfer equation describing photon interactions with vegetation canopies are important in remote sensing since they provide the canopy reflectance distribution required in the interpretation of satellite acquired information. The general one-dimensional two-angle transport problem for a finite copy of arbitrary leaf angle distribution is considered. Analytical solutions are obtained in terms of generalized Chandrasekhar's X- and Y-functions by invoking the principles of invariance. A critical step in the formulation involves the decomposition of the integral of the scattering phase function into a product of known functions of the incident and scattered photon directions. Several simplified cases previously considered in the literature are derived from the generalized solution. Various symmetries obeyed by the scattering operator and reciprocity relations are formally proved.

Ganapol, B. D.↗
NASA NTRS2018

Compensation of Oxygen Transmittance Effects for Proximal Sensing Retrieval of Canopy-Leaving Sun-Induced Chlorophyll Fluorescence

Estimates of Sun-Induced vegetation chlorophyll Fluorescence (SIF) using remote sensing techniques are commonly determined by exploiting solar and/or telluric absorption features. When SIF is retrieved in the strong oxygen (O2) absorption features, atmospheric effects must always be compensated. Whereas correction of atmospheric effects is a standard airborne or satellite data processing step, there is no consensus regarding whether it is required for SIF proximal-sensing measurements nor what is the best strategy to be followed. Thus, by using simulated data, this work provides a comprehensive analysis about how atmospheric effects impact SIF estimations on proximal sensing, regarding: (1) the sensor height above the vegetated canopy; (2) the SIF retrieval technique used, e.g., Fraunhofer Line Discriminator (FLD) family or Spectral Fitting Methods (SFM); and (3) the instrument's spectral resolution. We demonstrate that for proximal-sensing scenarios compensating for atmospheric effects by simply introducing the O2 transmittance function into the FLD or SFM formulations improves SIF estimations. However, these simplistic corrections still lead to inaccurate SIF estimations due to the multiplication of spectrally convolved atmospheric transfer functions with absorption features. Consequently, a more rigorous oxygen compensation strategy is proposed and assessed by following a classic airborne atmospheric correction scheme adapted to proximal sensing. This approach allows compensating for the O2 absorption effects and, at the same time, convolving the high spectral resolution data according to the corresponding Instrumental Spectral Response Function (ISRF) through the use of an atmospheric radiative transfer model. Finally, due to the key role of O2 absorption on the evaluated proximal-sensing SIF retrieval strategies, its dependency on surface pressure (p) and air temperature (T) was also assessed. we combined simulated spectral data with p and T measurements obtained for a one-year period in the Hyytiala Forestry Field Station in Finland. Of importance hereby is that seasonal dynamics in terms of T and p, if not appropriately considered as part of the retrieval strategy, can result in erroneous SIF seasonal trends that mimic those of known dynamics for temperature-dependent physiological responses of vegetation.

"sun–induced chlorophyll fluorescence (SIF); pro↗