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Heydorn, R. P.

Publications and source records attributed to Heydorn, R. P..

18 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Lunar precursor missions for human exploration of Mars--III: studies of system reliability and maintenance

Discussions of future human expeditions into the solar system generally focus on whether the next explorers ought to go to the Moon or to Mars. The only mission scenario developed in any detail within NASA is an expedition to Mars with a 500-day stay at the surface. The technological capabilities and the operational experience base required for such a mission do not now exist nor has any self-consistent program plan been proposed to acquire them. In particular, the lack of an Abort-to-Earth capability implies that critical mission systems must perform reliably for 3 years or must be maintainable and repairable by the crew. As has been previously argued, a well-planned program of human exploration of the Moon would provide a context within which to develop the appropriate technologies because a lunar expedition incorporates many of the operational elements of a Mars expedition. Initial lunar expeditions can be carried out at scales consistent with the current experience base but can be expanded in any or all operational phases to produce an experience base necessary to successfully and safely conduct human exploration of Mars. Published by Elsevier Ltd.

Moon↗
NASA NTRS1986

On the design of classifiers for crop inventories

Crop proportion estimators that use classifications of satellite data to correct, in an additive way, a given estimate acquired from ground observations are discussed. A linear version of these estimators is optimal, in terms of minimum variance, when the regression of the ground observations onto the satellite observations in linear. When this regression is not linear, but the reverse regression (satellite observations onto ground observations) is linear, the estimator is suboptimal but still has certain appealing variance properties. In this paper expressions are derived for those regressions which relate the intercepts and slopes to conditional classification probabilities. These expressions are then used to discuss the question of classifier designs that can lead to low-variance crop proportion estimates. Variance expressions for these estimates in terms of classifier omission and commission errors are also derived.

Heydorn, R. P.↗
NASA NTRS1984

Fundamental remote science research program. Part 2: Status report of the mathematical pattern recognition and image analysis project

The Mathematical Pattern Recognition and Image Analysis (MPRIA) Project is concerned with basic research problems related to the study of he Earth from remotely sensed measurements of its surface characteristics. The program goal is to better understand how to analyze the digital image that represents the spatial, spectral, and temporal arrangement of these measurements for purposing of making selected inferences about the Earth. This report summarizes the progress that has been made toward this program goal by each of the principal investigators in the MPRIA Program.

Heydorn, R. P.↗
NASA NTRS1984

Estimating location parameters in a mixture

The problem of estimating the parameters in a finite mixture is considered. The approach is based on an integral equation formulation of the form h sub t (x) = integral (limits b and a) f(x-y) g sut t (y)dy where h sub t is a smoothed version of h and g sub t is a prior function that tends to be concentrated on the translation values. A solution for g sub t that uses the method of regularization and one based on a posterior operator approach is considered. Numerical simulations are presented to bring out some of the estimation and numerical problems of these approaches.

Heydorn, R. P.↗
NASA NTRS1983

Estimating proportions of materials using mixture models

An approach to proportion estimation based on the notion of a mixture model, appropriate parametric forms for a mixture model that appears to fit observed remotely sensed data, methods for estimating the parameters in these models, methods for labelling proportion determination from the mixture model, and methods which use the mixture model estimates as auxiliary variable values in some proportion estimation schemes are addressed.

Heydorn, R. P.↗
NASA NTRS1983

Estimating Location Parameters in a Mixture Model

Mixture models of the form h = sum to M terms, one for each positive integer from 1 to N lambda sub j f (j) sub theta sub j where theta sub j is a translation parameter are considered. An approach is discussed which makes use of a Caratheodory theorem on the trigonometric moment problem to determine M and theta sub j j = 1,2,...,M. This theorem is also applied to show that translates of many common distributions lead to identifiable mixtures.

Heydorn, R. P.↗
NASA NTRS1983

Improving our understanding of the remote sensing process

Plans for two fundamental research programs aimed at improving an understanding of the physics and mathematics of remote sensing are discussed. The first program, Scene Radiation and Atmospheric Research Program, is concerned with developing the capability to determine biophysical attributes of terrestrial scenes through an improved understanding of the relationships between those properties and remotely sensed radiation. The research issues in the second program, Mathematical Pattern Recognition and Image Analysis, are discussed with reference to the following five categories: preprocessing, digital image representation, object scene inference, computational structures, and continuing studies.

Calabrese, M. A.↗
NASA NTRS1982

Crop proportion estimation problems in AgRISTARS

Some mathematical/statistical problems within the AgRISTARS program amendable to investigations involving the use of surface fitting techniques are overviewed. The Bayes and maximum likelihood rules, bias determination, regression estimators, parameter estimation, and classifier design are addressed.

Heydorn, R. P.↗
NASA NTRS1982

Can crop types be resolved using mixture distribution components - Some initial results and implications

For the analysis of remotely sensed data, it is frequently necessary to design a classifier in order to locate a ground cover class of interest or to estimate the proportion of this ground cover class. Advantages of a mixture distribution formulation are discussed, and a description is presented of the results of estimating the proportion of small grains in ten Landsat data segments using the mixture model. It is found that the mixture model proportion estimates have a very low variance and coefficient of variation. The discussed investigation implies that the mixtures model is a viable method for determining the distributions of classes of interest in remote sensing problems and in estimating the proportions of these classes directly.

Lennington, R. K.↗
NASA NTRS1981

Monitoring global vegetation

An attempt is made to identify the need for, and the current capability of, a technology which could aid in monitoring the Earth's vegetation resource on a global scale. Vegetation is one of our most critical natural resources, and accurate timely information on its current status and temporal dynamics is essential to understand many basic and applied environmental interrelationships which exist on the small but complex planet Earth.

Macdonald, R. B.↗
NASA NTRS1979

Classification and mensuration of LACIE segments

The theory of classification methods and the functional steps in the manual training process used in the three phases of LACIE are discussed. The major problems that arose in using a procedure for manually training a classifier and a method of machine classification are discussed to reveal the motivation that led to a redesign for the third LACIE phase.

Heydorn, R. P.↗
NASA NTRS1979

Methods for segment wheat area estimation

The major research conducted during the three years of LACIE to solve problems associated with segment wheat area estimation is reviewed. Topics covered include proportion estimation, clustering, feature extraction, and signature extension. It would appear that LANDSAT-1 and LANDSAT-2 data do not contain enough information to discriminate between crop types perfectly all the time and, therefore, a basic problem arises when no ground truth data on crop types in the area are available. New approaches are needed to reduce labeling error. Perhaps better use of multiyear LANDSAT data, a more detailed understanding of the cropping practices in the area, better crop calendar prediction, and a better understanding of the limiting sources of error in LANDSAT data related to crop discrimination may provide the insight required to develop improved designs.

Heydorn, R. P.↗
NASA NTRS1979

An evaluation of procedure 1

LACIE Procedure 1 has undergone continuous testing and evaluation, starting with analytical and experimental studies even before it was implemented in ERIPS software and continuing to the present with performance evaluations using blind-site data. The strengths and weaknesses of the procedure are indicated and some areas for possible improvement are identified. Results from three of the experiments performed and an evaluation of LACIE Procedure 1 proportion estimates for some blind-site segments are discussed.

Wheeler, S. G.↗