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At least 271 records · Page 15

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NASA NTRS1980

A model of plant canopy polarization response

Sensors to remotely measure the linear polarization of ground scenes have been proposed for the Multispectral Resource Sampler (MRS), a satellite sensor system proposed to complement the Thematic Mapper. At present justification for a sensor on MRS to measure scene polarization is limited. This paper discusses a model for the amount of linearly polarized light reflected by the shiny leaves of such crops as wheat, corn, and sorghum. The theory demonstrates that, potentially, measurements of the linearly polarized light from a crop canopy may be used as an additional feature to discriminate between crops. Examination of the model suggests that, potentially, satellite polarization measurements may be used to monitor crop development stage, leaf water content, leaf area index, hail damage, and certain plant diseases. The model adds to the understanding of the potential information content of scene polarization measurements acquired by future satellite sensor systems such as MRS.

Vanderbilt, V. C.↗

NASA NTRS1980

A model of plant canopy polarization

A model for the amount of linearly polarized light reflected by the shiny leaves of grain crops is based on the morphological and phenological characteristics of the plant canopy and upon the Fresnel equations which describe the light reflection process at the smooth boundary separating two dielectrics. The theory used demonstrates that, potentially, measurements of the linearly polarized light from a crop canopy may be used as an additional feature to discriminate between crops such as wheat and barley, two crops which are so spectrally similar that they are misclassified with unacceptable frequency. Examination of the model suggests that, potentially, satellite polarization measurements may be used to monitor crop development stage, leaf water content, leaf area index, hail damage, and certain plant diseases. The information content of these measurements is needed to evaluate the proposed polarization sensor for the satellite-borne multispectral resource sampler.

Vanderbilt, V. C.↗

NASA NTRS1982

Spectral estimates of solar radiation intercepted by corn canopies

Reflectance factor data were acquired with a Landsat band radiometer throughout two growing seasons for corn (Zea mays L.) canopies differing in planting dates, populations, and soil types. Agronomic data collected included leaf area index (LAI), biomass, development stage, and final grain yields. The spectral variable, greenness, was associated with 78 percent of the variation in LAI over all treatments. Single observations of LAI or greenness have limited value in predicting corn yields. The proportions of solar radiation intercepted (SRI) by these canopies were estimated using either measured LAI or greenness. Both SRI estimates, when accumulated over the growing season, accounted for approximately 65 percent of the variation in yields. Models which simulated the daily effects of weather and intercepted solar radiation on growth had the highest correlations to grain yields. This concept of estimating intercepted solar radiation using spectral data represents a viable approach for merging spectral and meteorological data for crop yield models.

Bauer, M. E.↗

NASA NTRS1982

Association of spectral development patterns with development stages of corn

Association is made between the development stages of corn as defined by Hanway and the temporal-spectral development pattern of corn in a transformed data space derived from Landsat-MSS band reflectance values, using field-collected reflectance and associated data. Results indicate that the spectral vegetation index used (a reflectance equivalent of Tasseled Cap Greenness) reaches a maximum well before the stage at which corn is expected to achieve its peak leaf area index. Possible physiological and canopy geometry related causes for this and other results are presented.

Crist, E. P.↗

NASA NTRS1982

Biophysical and spectral modeling

Activities and results of a project to develop strategies for modeling vegetative canopy reflectance are reported. Specific tasks included the inversion of canopy reflectance models to estimate agronomic variables (particularly leaf area index) from in-situ reflectance measurements, and a study of possible uses of ecological models in analyzing temporal profiles of greenness.

Goel, N. S.↗

NASA NTRS1982

Modeling of vegetation canopy reflectance: Status, issues and recommended future strategy

Various technical issues related to mapping of vegetative type, condition and stage of maturity, utilizing remotely sensed spectral data are reviewed. The existing knowledge base of models, especially of radiative properties of the vegetation canopy and atmosphere, is reviewed to establish the state of the art for addressing the problem of vegetation mapping. Activities to advance the state of the art are recommended. They include working on canopy reflectance and atmospheric scattering models, and field measurements of canopy reflectance as well as of canopy components. Leaf area index (LAI) and solar radiation interception (SRI) are identified as the two most important vegetation variables requiring further investigation. It is recommended that activities related to sensing them or understanding their relationships with measurable variables, should be encouraged and supported.

Goel, N. S.↗

NASA NTRS1982

Relation of agronomic and multispectral reflectance characteristics of spring wheat canopies

The relationships between crop canopy variables such as leaf area index (LAI) and their multispectral reflectance properties were investigated along with the potential for estimating canopy variables from remotely sensed reflectance measurements. Reflectance spectra over the 0.4 to 2.5 micron wavelength range were acquired during each of the major development stages of spring wheat canopies at Williston, North Dakota, during three seasons. Treatments included planting date, N fertilization, cultivar, and soil moisture. Agronomic measurements included development stage, biomass, LAI, and percent soil cover. High correlations were found between reflectance and percent cover, LAI, and biomass. A near infrared wavelength band, 0.76 to 0.90 microns, was most important in explaining variation in LAI and percent cover, while a middle infrared band, 2.08 to 2.35 microns, explained the most variation in biomass and plant water content. Transformations, including the near infrared/red reflectance ratio and greenness index, were also highly correlated to canopy variables. The relationship of canopy variables to reflectance decreased as the crop began to ripen. the canopy variables could be accurately predicted using measurements from three to five wavelength bands. The wavelength bands proposed for the thematic mapper sensor were more strongly related to the canopy variables than the LANDSAT MSS bands.

Bauer, M. E.↗

NASA NTRS1983

Field measurements, simulation modeling and development of analysis for moisture stressed corn and soybeans, 1982 studies

The experimental design, data acquisition and analysis procedures for agronomic and reflectance data acquired over corn and soybeans at the Sandhills Agricultural Laboratory of the University of Nebraska are described. The following conclusions were reached: (1) predictive leaf area estimation models can be defined which appear valid over a wide range of soils; (2) relative grain yield estimates over moisture stressed corn were improved by combining reflectance and thermal data; (3) corn phenology estimates using the model of Badhwar and Henderson (1981) exhibited systematic bias but were reasonably accurate; (4) canopy reflectance can be modelled to within approximately 10% of measured values; and (5) soybean pubescence significantly affects canopy reflectance, energy balance and water use relationships.

Blad, B. L.↗

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 NTRS1984

A Study of the Relation Between Crop Growth and Spectra Reflectance Parameters

The relationship between crop growth and spectra reflectance parameters was studied. The dynamic behavior of canopy reflectance versus time and the relationship of trajectories to canopy dynamics, ontogeny and morphology was investigated. The determination of which transformations of spectral data best suited for observing key canopy characteristics, such as leaf area index and vegetation identification are understood. A physical basis to understand how various spectral transform trajectories depend on vegetation type and models that describe the time delayed interaction of reflectance in the chlorophyll and water absorption bands to monitor stress were formulated. The general process of physical understanding of canopy reflectance is evaluated and existing canopy models are improved.

Badhwar, G.↗

NASA NTRS1984

Habitability of the Earth

Test methods to measure land vegetation biomass, net biological production and leaf area index by remote sensing are applied to estimate the biomass and net biological productivity of selected biomes, including the boreal forests and north temperate grasslands. Field verification is conducted in conjunction with remote sensing of pertinent variables and the development of a data base of relevant material initiated. Measurements are made in the Superior National Forest, Minnesota with the following remote sensing instruments: (1) an airborne 8 band Barnes radiometer; (2) the thematic mapper simulator flown in a NASA C-130 aircraft; (3) MSS data from LANDSAT 3; and (4) AVHRR data from the NOAA Satellite. Vegetation data collected as field verification in the Superior National Forest is summarized.

Botkin, D. B.↗

NASA NTRS1983

A mathematical model for crop spectral-temporal trajectories based on a plant growth model

The Kubelka-Munk radiative transfer model is combined with an approximation of Kauth-Thomas greeness and brightness transforms to derive approximate closed form expressions for crop greeness and brightness surrogates in terms of canopy biomass. The greeness relation derived resembles an existing empirical relation between leaf area index and greeness. A simple growth model based on interception and utilization of photosynthetically active radiation is developed and used to describe the time evolution of greeness and brightness. The model developed does not yet yield definitive profile calculations but suggests a conceptual framework which may be found useful for further profile analysis.

Woolford, T. L.↗

NASA NTRS1983

Inversion of vegetation canopy reflectance models for estimating agronomic variables. I - Problem definition and initial results using the Suits model

An important but relatively uninvestigated problem in remote sensing is the inversion of vegetative canopy reflectance models to obtain agrophysical parameters, given measured reflectances. The problem is here formally defined and its solution outlined. Numerical nonlinear optimization techniques are used to implement this inversion to obtain the leaf area index using Suits' canopy reflectance model. The results for a variety of cases indicate that this can be done successfully using infrared reflectances at different views or azimuth angles or a combination thereof. The other parameters of the model must be known, although reasonable measurement errors can be tolerated without seriously degrading the accuracy of the inversion. The application of the technique to ground based remote-sensing experiments is potentially useful, but is limited to the degree to which the canopy reflectance model can accurately predict observed reflectances.

Goel, N.↗

NASA NTRS1984

Biogeochemical cycling and remote sensing

The present investigation is concerned with the role of remote sensing in the analysis of biochemical cycling. A general review is provided of the interest of NASA in biochemical cycling, taking into account an assessment of the state and dynamics of the pools and fluxes of four major elements (carbon, nitrogen, phosphorus, sulfur), an understanding of the coupling and interaction of the biosphere and the atmosphere, and an understanding of the biosphere and the oceans. Attention is given to biogeochemical cycling science issues, the potential remote sensing role, the vegetation type, aspects of vegetation structure, the leaf area index, the canopy height, functional relationships, environmental and soil variables, questions of experimental design, sampling sites and ground data, and radiometric data and analysis.

Peterson, D. L.↗

NASA NTRS1984

Exploring the use of structural models to improve remote sensing agricultural estimates

Satellite estimates of agricultural characteristics often are not sufficiently precise for reliable use in small geographical regions. The precision of estimates of agricultural characteristics such as crop proportions and leaf area indexes can be increased by modeling ground observations as a function of satellite estimates. Linear regression models using least squares estimators of the model parameters are most often advocated as an appropriate methodology; however, least squares estimation requires that the predictor variables are measured without error, an unreasonable assumption for this application. An alternative estimation methodology which assumes that both the response variables (ground observations) and the predictor variables (satellite estimates) are measured with error involves the use of linear structural models. The application of linear structural models to the estimation of agricultural characteristics using satellite spectral measurements is examined.

Gunst, R. F.↗

NASA NTRS1983

Characterization of terrestrial ecosystems for biogeochemical studies using remote sensing

Work is in progress to estimate leaf area index (LAI) of temperate closed canopy coniferous forests using transects in Oregon and California. This variable will be measured using remote sensing techniques including correlations of ground dimensional analysis with linear waveband combinations. LAI will be related to important biological variables such as net primary productivity, biomass, and biogenic gas emission fluxes. The spatial variation in LAI, when coupled with species composition, will be used in part to describe the spatial variation and temporal dynamics of biogeochemical cycling.

Peterson, D. L.↗

NASA NTRS1985

Comparative study of Suits and SAIL canopy reflectance models

A detailed understanding of the relationships between the canopy reflectance and the characteristics of canopy elements is an important factor for the full exploitation of the potential of remote sensing from aircraft and spacecraft altitudes to map vegetation and estimate key agronomic parameters such as the leaf area index (LAI) and biomass (BM). Suits (1972) idealized the canopy geometry by replacing each plant component with three orthogonal projections of that component. Verhoeff and Bunnik (1981) extended the Suits model, henceforth called the SAIL (Scattering from Arbitrarily Inclined Leaves) model, by removing certain constraints. The present investigation is concerned with an evaluation of the performance of the Suits and SAIL models, taking into account two data sets on soybean and corn. It was found that the tested models have significant deficiencies. However, the performance of the SAIL model is better than that of the Suits model because it provides a more realistic description of the canopy architecture.

Badhwar, G. D.↗

NASA NTRS1985

Evaluation of a canopy reflectance model for LAI estimation through its inversion

A technique for estimating leaf area indices (LAIs) based on bidirectional canopy reflectance (CR) data is applied to three plant canopies: a naturally growing healthy soybean canopy; and a clumped and tufted orchardgrass canopy, respectively. The CR data were collected using a PARABOLA instrument which is capable of acquiring complete sky-and-ground looking hemispheres in 11 seconds. The model fit and LAI estimates were good for the soybean and clumped orchardgrass canopies, but poor for the tufted orchardgrass canopy when the maximum zenith angle was less than 50 percent. It is shown that the biophysical parameter estimation based on CR measurements applied well to homogeneous herbaceous vegetation types, while better CR models are needed to adequately represent discontinuous plant canopies.

Goel, N. S.↗