Engineering topics
Publications and source records attributed to Badhwar, G. D..
The absolute flux of cosmic ray positrons has been measured using a balloon-borne magnet-spectrometer. Based on 193 positrons observed from 3.57 GV/c to 50 GV/c rigidity at the payload, the integral flux about 5 GeV kinetic energy at the top of the atmosphere is found to be (0.33 + or - .07)e(+)/m-sq-str-s. At the top of the atmosphere the effective energy interval for the observation is 4.5 to 64 GeV.
A Landsat MSS and TM classification approach based on three features derived from the greenness profile has proved very effective in separating and identifying corn, soybeans, and other ground cover classes in the U.S. The objective of this study is to investigate the separation of summer crops in Argentina, one of the most important commodity exporters, using the same greenness profile features that have proved effective in the U.S. Corn Belt. The area chosen for study is a more complex cropping practice area located in the north-west corner of Buenos Aires province in Pampa Humeda, where corn, soybean, sorghum, sunflower, and pastures are cultivated. It is shown that the profile features can provide very effective separation, except in the case of corn from sorghum. Separation between corn and soybeans was found to be greater than in the U.S. This study suggests that the automatic, unsupervised classification approach developed in the U.S., with relatively minor modification, can be used for summer crop area estimation in Argentina.
An X-band FM-CW very fine range resolution scatterometer was used to acquire backscattering data for a number of tree species. Using a model to describe the scattering source function and an experimental procedure for selected removal of plant parts allows the estimation of the volume backscatter coefficient and the volume extinction coefficient. It is found that: (1) leaves are strong attenuators as well as scatterers; (2) the albedo at a given angle of incidence is nearly independent of the tree type; (3) the tree limbs are good attenuators but rather poor scatterers; and (4) the albedo changes as a function of the angle of incidence and for deciduous trees is also a function of the season.
An experimental technique that permits the extraction of orbit-averaged, differential energy spectra of trapped radiation belt protons using simple passive detectors is described. An inversion technique is used for the data analysis. The basic principle of the described system is measurement of the energy deposited in six thermoluminescent (TLD) detector assemblies behind various spherical absorbers. The technique has been applied to a detector assembly flown on four Shuttle flights. Although severe restraints were placed on the flight package, the differential energy spectra derived from these measurements are in good agreement with analytical results using a modified trapped proton environment model. The technique shows good promise for measuring the spectra in low inclination orbits where the flux of high energy galactic cosmic rays protons is small. Modifications to the detector assembly to improve the accuracy and to extend the range of the system to higher energies are suggested.
Results from analysis of a data set of simultaneous measurements of Thematic Mapper band reflectance and leaf area index are presented. The measurements were made over pure stands of Aspen in the Superior National Forest of northern Minnesota. The analysis indicates that the reflectance may be sensitive to the leaf area index of the Aspen early in the season. The sensitivity disappears as the season progresses. Based on the results of model calculations, an explanation for the observed relationship is developed. The model calculations indicate that the sensitivity of the reflectance to the Aspen overstory depends on the amount of understory present.
This article describes a separability measure for class discrimination. This measure is based on the Fisher information measure for estimating the mixing proportion of two classes. The Fisher information measure not only provides a means to assess quantitatively the information content in the features for separating classes, but also gives the lower bound for the variance of any unbiased estimate of the mixing proportion based on observations of the features. Unlike most commonly used separability measures, this measure is not dependent on the form of the probability distribution of the features and does not imply a specific estimation procedure. This is important because the probability distribution function that describes the data for a given class does not have simple analytic forms, such as a Gaussian. Results of applying this measure to compare the information content provided by three Landsat-derived feature vectors for the purpose of separating small grains from other crops are presented.
Digitized agricultural field boundary taken in the United States and Canada during the LACIE and AgRISTARS programs, in 1977 through 1980, were used to construct histograms showing the distributions of field area, width, and length for crops for which there were data for 700 or more fields per state. The observed distributions of area and width for fields of 10 crops grown in 13 states of the United States and Canada were compared with best-fit inverse Gaussian distributions and with log-normal distributions. For 28 distributions of area and 16 distributions of width there was found to be a probability of greater than .01 of their being inverse Gaussian. There were 10 distributions of area for which there was probability of greater than .005 of their being log-normal. Distributions of area and width stratified by state and crop type appear to be unique. The inverse Gaussian, which represents a wide range of statistical distributions from skewed to almost symmetrical, can provide a useful model for distributions of field area.
A hierarchical procedure for developing a leaf area index (LAI) map of deciduous boreal forests is studied. The collection of spectral reflectance data from the Boundary Waters Canoe area in Minnesota using helicopter-, high-altitude aircraft-, and Landsat-mounted spectral sensors is described. The relationship between LAI and biomass and the reflectance ratio is analyzed. The sensitivity of canopy reflectance in the visible and infrared to the LAI of the canopy for various boreal forest species is evaluated. The data reveal that Landsat data are useful for producing LAI maps of deciduous forest areas and the maps provide data which clarifies the function of vegetation in the global carbon cycle models.
In order to exploit the use of thematic mapper (TM) data to obtain vegetation and net primary productivity maps in the boreal forest, three aircraft flights were undertaken over the area near Ely, MN, with the NS 001 Thematic Mapper Simulator. Attention is presently given to an analysis of these 1983 data, which attempted to separate coniferous trees from deciduous ones. Canopy reflectance models and measured optical properties of the scattering elements have been used to deepen understanding of this separability, and to relate the ratio of nadir view reflectances in TM bands 4 and 3 to the overstory leaf area index. A map that is proportional to the leaf area index for deciduous species is presented.
A detailed comparison of the observed soybeans and corn canopy reflectance with that calculated from three vegetative canopy reflectance models have shown systematic angular deviations. A likely cause of these effects is noninclusion of leaf specular reflectance. In this paper a formulation to calculate the component of canopy specular reflectance as a function of incident solar and view zenith angles, leaf area index, leaf angle distribution, and leaf specular reflectance has been developed. The SAIL model has been modified to include this component and the results are compared with an extensive observational data set on soybeans. It is shown that the systematic differences between the SAIL model and observations dependent on scattering azimuth are removed. An analysis of variance shows model improvement of 30 percent over the uncorrected SAIL model.
Much of the early research in remote sensing follows along developing spectral signatures of cover types. It was found, however, that a signature from an unknown cover class could not always be matched to a catalog value of known cover class. This approach was abandoned and supervised classification schemes followed. These were not efficient and required extensive training. It was obvious that data acquired at a single time could not separate cover types. A large portion of the proposed research has concentrated on modeling the temporal behavior of agricultural crops and on removing the need for any training data in remote sensing surveys; the key to which is the solution of the so-called 'signature extension' problem. A clear need to develop spectral estimaters of crop ontogenic stages and yield has existed even though various correlations have been developed. Considerable effort in developing techniques to estimate these variables was devoted to this work. The need to accurately evaluate existing canopy reflectance model(s), improve these models, use them to understand the crop signatures, and estimate leaf area index was the third objective of the proposed work. A synopsis of this research effort is discussed.
Proton and helium nuclei differential spectra were gathered with a balloon borne magnet spectrometer. The data were fitted to the assumption that the differential flux can be represented by a power law in rigidity. In the rigidity range 10 to 25 GV/c the spectral indices were found to be -(2.74 plus or minus 0.04) for protons and -(2.71 plus or minus 0.05) for helium nuclei. A brief discussion is given by systematic errors.
The positron data gathered in conjunction with electron data published elsewhere is reported. The basic recognition scheme was to look for low mass positive particles that cause a cascade in a 7 radiation length shower counter. The mass criteria is imposed by selecting particles that were accompanied by Cherenkov light but whose rigidity was below the proton Cherenkov threshold. Thus the proton Cherenkov threshold represents an upper limit to the range of the experiment.
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.
A model, utilizing direct relationship between remotely sensed spectral data and the development stage of both corn and soybeans has been proposed and published previously (Badhwar and Henderson, 1981; and Henderson and Badhwar, 1984). This model was developed using data acquired by instruments mounted on trucks over field plots of corn and soybeans as well as satellite data from Landsat. In all cases, the data was analyzed in the spectral bands equivalent to the four bands of Landsat multispectral scanner (MSS). In this study the same model has been applied to corn and soybeans using Landsat-4 Thematic Mapper (TM) data combined with simulated TM data to provide a multitemporal data set in TM band intervals. All data (five total acquisitions) were acquired over a test site in Webster County, Iowa from June to October 1982. The use of TM data for determining development state is as accurate as with Landsat MSS and field plot data in MSS bands. The maximum deviation of 0.6 development stage for corn and 0.8 development stage for soybeans is well within the uncertainty with which a field can be estimated with procedures used by observers on the ground in 1982.
A method for estimating the biophysical properties of a forest canopy through inversion of microwave scatterometer data is discussed. A C-band scatterometer flown over an aspen site in northern Minnesota during 19 days from May 2 to October 20, 1984, was modified to enable continuous recording of the range of the target. This provided the backscatter cross section as a function of range and was used to study scattering processes within the canopy. The remote estimates of HH, VV, and HV extinction coefficient values agreed well with the estimates obtained with the use of an active radar calibrator.
A balloon-borne superconducting magnet spectrometer was used to measure the absolute flux of cosmic-ray electrons. The instrument consisted of a gas Cerenkov detector, a momentum spectrometer, and a lead-scintillator shower counter. In order to determine electron flux in the interstellar medium, observed fluxes for energy loss in the atmosphere and the payload were corrected, taking into account solar modulation effects and bremsstrahlung energy losses. Fluxes were measured at an average atmospheric depth of 5.8 g/sq cm, and the solar modulation was 300 MeV. A cosmic-ray electron flux of 367 E to the exp(3.15 + or -0.2) per sq m/sr s GeV was obtained in the energy range 4.5-63.5 GeV. The uncertainty of the absolute (electron-positron) flux was 10 percent. A summary of the electron data is given in a table.
The present model for the temporal behavior of agricultural greenness is applied to the extraction of Landsat-derived profile features, distinguishing small from large grain crops. An additional feature derivable from the temporal behavior of the ratio of greenness to brightness is noted which aids in the separation of crops from other vegetation. A limited training set of 20 pure pixels/class, obtained from ground data, is subjected to the Ho-Kashyap (1965) linear classifier. The initial correct classification value for pure pixels of about 85 percent drops to 75 percent for all Landsat pixels.