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Alternatives to sampling-theory stratified and regression estimators of crop production and timber biomass were examined. An alternative estimator which is viewed as especially promising is the errors-in-variable regression estimator. Investigations established the need for caution with this estimator when the ratio of two error variances is not precisely known.
Efforts in measuring, analyzing, and mathematically modeling the specular, polarized, and diffuse light scattering properties of several plant canopies and their component parts (leaves, stems, fruit, soil) as a function of view angle and illumination angle are reported. Specific objectives were: (1) to demonstrate a technique for determining the specular and diffuse components of the reflectance factor of plant canopies; (2) to acquire the measurements and begin assembling a data set for developing and testing canopy reflectance models; (3) to design and build a new optical instrument to measure the light scattering properties of individual leaves; and (4) to use this instrument to survey and investigate the information in the light scattering properties of individual leaves of crops, forests, weeds, and horticulture.
Progress and results in the measurement and scattering properties of crop canopies was examined. The following accomplishments are reported: (1) analysis of inhouse polarization, Sun/view angle data set of wheat was completed; (2) polarization photometer instrument system was completed; (3) light polarization properties (measured with polarization photometer) of individual plant leaves initiated, and twenty two species/varieties were measured before frost; (4) light polarizing properties of both moisture-stressed corn leaves and diseased wheat leaves were measured; (5) Sun/view angle data and ancillary data were acquired on two wheat canopies on two dates and on one sorghum canopy on two adjacent days.
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.
Statistical procedures were developed for large area assessments using both satellite and conventional data. Crop acreages, other ground cover indices, and measures of change were the principal characteristics of interest. These characteristics are capable of being estimated from samples collected possibly from several sources at varying times, with different levels of identification. Multiyear analysis techniques were extended to include partially identified samples; the best current year sampling design corresponding to a given sampling history was determined; weights reflecting the precision or confidence in each observation were identified and utilized, and the variation in estimates incorporating partially identified samples were quantified.
The total amount of water available to plants that is held against gravity in a soil is usually estimated as the amount present at -0.03 MPa average water potential minus the amount present at -1.5 MPa water potential. This value, designated available water-holding capacity (AWHC), is a very important soil characteristic that is strongly and positively correlated to the inherent productivity of soils. In various applications, including assessing soil moisture status over large areas, it is necessary to group soil types or series as to their productivity. Current methods to classify AWHC of soils consider only total capacity of soil profiles and thus may group together soils which differ greatly in AWHC as a function of depth in the profile. A general approach for evaluating quantitatively the multidimensional nature of AWHC in soils is described. Data for 902 soil profiles, representing 184 soil series, in Indiana were obtained from the Soil Characterization Laboratory at Purdue University. The AWHC for each of ten 150-mm layers in each soil was established, based on soil texture and parent material. A multivariate clustering procedure was used to classify each soil profile into one of 4, 8, or 12 classes based upon ten-dimensional AWHC values. The optimum number of classes depends on the range of AWHC in the population of oil profiles analyzed and on the sensitivity of a crop to differences in distribution of water within the soil profile.
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.
A generic, U.S.-based analysis approach was evaluated with respect to corn and soybean identification in Argentina. Using crop separability expectations derived from the analysis of Argentina ancillary data and U.S. spectral data, the approach was applied to Argentina spectral data by an expert analyst. Eight classes were detected and labeled independent of ground data. A high correspondence between the labels and limited ground data was achieved. It was concluded that an approach of this type could be applied to Argentina without major difficulty.
In a corn and soybeans test site in Webster County, Iowa, airborne radar scatterometers were used on August 19 and September 10, 1980, to investigate the backscattering properties of these crops at wavelengths of 2.3, 6.3, and 19 cm (Ku-, C-, and L-band, respectively). Both horizontal transmit-horizontal receiver (HH) polarization and horizontal transmit-vertical receive (HV) polarization combinations were used at L- and C-band. Only the VV polarization combination was available at Ku-band. Measurements were obtained at 10 angles of observation from 5 to 50 deg in steps of 5 deg (referenced to the nadir). Excellent separation between corn and soybeans was achieved when either C-band HV at 50 deg or when a defined depolarization factor was used at C-band. Good separation existed at L-band also using either L-band HH at 50 deg or an L-band polarization factor. Significant row direction effects were observed for all HH data near 10 deg. Significant effects of surface soil moisture were observed for all configurations at L-band and C-band.
The typical patterns of spectral development (profiles) for corn and soybeans are presented, based on field-collected reflectance data transformed to correspond to Landsat-MSS Tasseled Cap coordinates. Reasonable variations in field conditions and cultural practices are shown to significantly influence profile features. The separability of the two crops is determined to be primarily related to the maximum value of the reflectance equivalent of Greenness, and to the plateau effect seen in corn Greenness profiles. The impact of changes in conditions on separability is described. In addition, association is made between profile features and stages of development for corn and soybeans. Corn is shown to peak at a stage well before tasseling or maximum LAI, while the characteristics of the soybean profile are shown to be unrelated to any particular stage of development.
The development of a technique for estimating all canopy parameters occurring in a canopy reflectance model from the measured canopy reflectance data is summarized. The Suits and the SAIL model for a uniform and homogeneous crop canopy were used to determine if the leaf area index and the leaf angle distribution could be estimated. Optimal solar/view angles for measuring CR were also investigated. The use of CR in many wavelengths or spectral bands and of linear and nonlinear transforms of CRs for various solar/view angles and various spectral bands is discussed as well as the inversion of rediance data inside the canopy, angle transforms for filtering out terrain slope effects, and modification of one dimensional models.
A cooperative research project was initiated in 1982 to study differences in thematic mapper spectral characteristics caused by variable tillage and crop residue practices. Initial evaluations of radiometric data suggest that spectral separability of variably tilled soils can be confounded by moisture and weathering effects. Separability of bare tilled soils from those with significant amounts of corn residue is enhanced by wet conditions, but still possible under dry conditions when recent tillage operations have occurred. In addition, thematic mapper data may provide an alternative method to study the radiant energy balance at the soil surface in conjunction with variable tillage systems.
The airborne L-band synthetic aperture radar (SAR) collected multipolarization calibrated image data over an irrigated agricultural test site near Fresno, CA, on March 6, 1984. The conclusions of the study are as follows: (1) the effects of incidence angle on the measured backscattering coefficients could be removed by using a correction factor equal to the secant of the angle raised to the 1.4 power, (2) for this scene and time of year, the various polarization channels were highly correlated such that the use of more than one polarization added little to the ability of the radar to discriminate vegetation type or condition; the exception was barley which separated from vineyards only when a combination of like and cross polarization data were used (polarization was very useful for corn identification in fall crops), (3) an excellent separation between herbaceous vegetation (alfalfa, barley, and oats) or bare fields and trees in orchards existed in brightness was well correlated to alfalfa height or biomass, especially for the HH polarization combination, (5) vineyards exhibited a narrow range of brightnesses with no systematic effects of type or number of stakes nor of number of wires in the trellises nor of the size of the vines, (6) within the orchard classes, areal biomass characterized by basal area differences caused radar image brightness differences for small to medium trees but not for medium to large trees.
Research activities conducted under the auspices of National Aeronautics and Space Administration Cooperative Agreement NCC 9-9 are discussed. During this contract period research efforts are concentrated in two primary areas. The first are is an investigation of the use of measurement error models as alternatives to least squares regression estimators of crop production or timber biomass. The secondary primary area of investigation is on the estimation of the mixing proportion of two-component mixture models. This report lists publications, technical reports, submitted manuscripts, and oral presentation generated by these research efforts. Possible areas of future research are mentioned.
Two predawn ascending data-takes by the Shuttle Imaging Radar-B (SIR-B) were used to evaluate the effects of surface roughness, crop canopy, and soil moisture on radar backscatter. The two images, separated by three days, were both obtained at 30-deg local angle of incidence, but with opposite azimuth viewing directions. The imagery was externally calibrated with respect to the radar backscattering coefficient sigma(0) via response to arrays of point and area-extended targets of known radar cross section. Three land-cover classes: (1) corn, (2) corn stubble and plowed bare soil, and (3) disked bare soil, soybeans, soybean stubble, alfalfa, and clover could be readily separated for either observation date on the basis of image tone alone. The dependence of sigma(0) on the surface roughness and canopy brightness inhibits the capability of SIR to globally estimate the near-surface soil moisture from the value of sigma(0) for single date observations, unless the surface roughness or canopy cover conditions are accounted for. However, within given ranges of these conditions, the sigma(0) was found to be highly correlated with the soil moisture.
Crop analysis aided by mathematical transformation that optimizes perspective of six-dimensional, six-band, spectral data taken from spacecraft or aircraft. Transformation applied to any temperatureclimate vegetated scene, providing direct view of regions of data concentration resulting from band correlations and fundamental reflectance properties of scene classes. Almost all of data variability captured in three spectral features, thus reducing by factor of 2 number of spectral features carried, incurring minimal loss of important information. Three-dimensional representation with two principal planes retains about 95 percent of six-dimensional spectral data used to distinguish among scenes containing green plants and bare soil with varying degrees of moisture.
Consideration is given to the development of criteria for successful CELSS experiments on crop production in space. Also, the development of a standard procedure to produce a given expected yield is examined. Factors influencing the success of CELSS experiments are discussed, including environmental limits to growth, efficient use of resources, data collection sensitivity, stress, and the space in which the experiment is performed. The implications of the study for designing CELSS food production systems are noted.
Crop Growth Research Chambers (CGRCs) are being developed as CELSS research facilities for the NASA/Ames Research Center. The history of the CGRC project is reviewed, noting the applications of CGRC research for the development of the Space Station. The CGRCs are designed for CELSS research and development, system control and integration, and flight hardware design and experimentation. The atmospheric and hydroponic environments of the CGRC system are described and the science requirements for CGRC environmental control are listed.