Engineering topics

Macdonald, R. B.

Publications and source records attributed to Macdonald, R. B..

At least 19 records

NASA NTRS1986

Spectral characterization of biophysical characteristics in a boreal forest - Relationship between Thematic Mapper band reflectance and leaf area index for Aspen

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.

Badhwar, G. D.↗

NASA NTRS1986

Satellite-derived leaf-area-index and vegetation maps as input to global carbon cycle models - A hierarchical approach

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.

Badhwar, G. D.↗

NASA NTRS1985

Preliminary Evaluation of Thematic Mapper Image Data Quality

Improvements in the ability to monitor renewable resources/vegegation due to improvements in the spatial, spectral and radiometric resolution of TM data were evaluated. Results presented from the first 4 months of analysis presented include: (1) geometric performance; (2) band-to-band registration; (3) modulation transfer function; and (4) crop separabililty performance. Crop separability in Webster County, Iowa and in Mississippi County, Arkansas as determined by cluster and principal components analyses is assessed.

Macdonald, R. B.↗

NASA NTRS1984

A summary of the history of the development of automated remote sensing for agricultural applications

An historical account is given of the development of technology for the processing of satellite-acquired multispectral data aimed at the identification of the type, condition, and ontogenic stages of agricultural areas. During 1972 and 1973, research established the feasibility of automating digital classification for the processing of large volumes of Landsat MSS data. This capability was successfully demonstrated during the Large Area Crop Inventory Experiment, which estimated wheat crop production on a global basis. This achievement in turn led to the Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing, which investigated other portions of the electromagnetic spectrum and expanded the study of key commercial crops in important agricultural areas.

Macdonald, R. B.↗

NASA NTRS1984

Spectral characterization of biophysical characteristics in a boreal forest: Relationship between Thematic Mapper band reflectance and leaf area index for Aspen

Badhwar, G.↗

NASA NTRS1984

Preliminary Evaluation of Thematic Mapper Image Data Quality

Thematic Mapper (TM) data from Mississippi County, Arkansas, and Webster County, Iowa, were examined for the purpose of evaluating the image data quality of the TM which was launched on board the LANDSAT-4 spacecraft. Preliminary clustering and principal component analysis indicates that the middle infrared and thermal infrared data of TM appear to add significant information over that of the near IR and visible bands of the multispectral scanner data. Moreover, the higher spatial resolution of TM appears to provide better definition of the edges and the within variability of agricultural fields. The geometric performance of TM data, without ground control correction, was found to exceed expectations. The modulation transfer function for the 1.65 m band was found to agree with prelaunch specifications when the effects of the GSFC cubic convolution and the atmosphere were removed. The band to band registration for the bands within the noncooled focal plane was found to be better than specified. However, the middle infrared and thermal infrared, which are on a separate cooled focal plane were found to be misregistered and were significantly worse than prelaunch specifications.

Macdonald, R. B.↗

NASA NTRS1983

A summary of the history of the development of automated remote sensing for agricultural applications

The research conducted in the United States for the past 20 years with the objective of developing automated satellite remote sensing for monitoring the earth's major food crops is reviewed. The highlights of this research include a National Academy of Science study on the applicability of remote sensing monitoring given impetus by the introduction in the mid-1960's of the first airborne multispectral scanner (MSS); design simulations for the first earth resource satellite in 1969; and the use of the airborne MSS in the Corn Blight Watch, the first large application of remote sensing in agriculture, in 1970. Other programs discussed include the CITAR research project in 1972 which established the feasibility of automating digital classification to process high volumes of Landsat MSS data; the Large Area Crop Inventory Experiment (LACIE) in 1974-78, which demonstrated automated processing of Landsat MSS data in estimating wheat crop production on a global basis; and AgRISTARS, a program designed to address the technical issues defined by LACIE.

Macdonald, R. B.↗

NASA NTRS1983

A survey of automated remote sensing for agriculture

The state-of-the-art of the technology available to make remote sensing crop production estimates is reviewed with reference to several past and present research projects. In particular, attention is given to Landsat data acquisition, registration and preprocessing, data transformation, data modeling, proportion estimation, and labeling. Development stage models and crop condition models are briefly characterized, and areas where further research is needed are identified.

Hall, F. G.↗

NASA NTRS1982

Thematic mapper data quality and performance assessment in renewable resource/agricultural remote sensing

A "quick look" investigation of the initial LANDSAT-4, thematic mapper (TM) scene received from Goddard Space Flight Center was performed to gain early insight into the characteristics of TM data. The initial scene, containing only the first four bands of the seven bands recorded by the TM, was acquired over the Detroit, Michigan, area on July 20, 1982. It yielded abundant information for scientific investigation. A wide variety of studies were conducted to assess all aspects of TM data. They ranged from manual analyses of image products to detect obvious optical, electronic, or mechanical defects to detailed machine analyses of the digital data content for evaluation of spectral separability of vegetative/nonvegetative classes. These studies were applied to several segments extracted from the full scene. No attempt was made to perform end-to-end statistical evaluations. However, the output of these studies do identify a degree of positive performance from the TM and its potential for advancing state-of-the-art crop inventory and condition assessment technology.

Erickson, J. D.↗

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 NTRS1980

Global crop forecasting

The needs for and remote sensing means of global crop forecasting are discussed, and key results of the Large Area Crop Inventory Experiment (LACIE) are presented. Current crop production estimates provided by foreign countries are shown often to be inadequate, and the basic elements of crop production forecasts are reviewed. The LACIE project is introduced as a proof-of-concept experiment designed to assimilate remote sensing technology, monitor global wheat production, evaluate key technical problems, modify the technique accordingly and demonstrate the feasibility of a global agricultural monitoring system. The global meteorological data, sampling and aggregation techniques, Landsat data analysis procedures and yield forecast procedures used in the experiment are outlined. Accuracy assessment procedures employed to evaluate LACIE technology performance are presented, and improvements in system efficiency and capacity during the three years of operation are pointed out. Results of LACIE estimates of Soviet, U.S. and Canadian wheat production are presented which demonstrate the feasibility and accuracy of the remote-sensing approach for global food and fiber monitoring.

Macdonald, R. B.↗

NASA NTRS1979

Advances in the development of remote sensing technology for agricultural applications

The application of remote sensing technology to crop forecasting is discussed. The importance of crop forecasts to the world economy and agricultural management is explained, and the development of aerial and spaceborne remote sensing for global crop forecasting by the United States is outlined. The structure, goals and technical aspects of the Large Area Crop Inventory Experiment (LACIE) are presented, and main findings on the accuracy, efficiency, applicability and areas for further study of the LACIE procedure are reviewed. The current status of NASA crop forecasting activities in the United States and worldwide is discussed, and the objectives and organization of the newly created Agriculture and Resources Inventory Surveys through Aerospace Remote Sensing (AgRISTARS) program are presented.

Powers, J. E.↗

NASA NTRS1978

LACIE: An experiment in global crop forecasting

The author has identified the following significant results. Both the accuracy and efficiency with which LACIE crop survey estimates were made have shown significant improvement in three years. In the U.S. and U.S.S.R. winter wheat regions, the original accuracy goals were met or exceeded, with 90/90 estimates achieved in the United States 1.5 to 2 months before harvest. Additionally, all available accuracy parameters indicate 90/90 estimates for the U.S.S.R. total crop. Key technology problems were identified during phase 2 with spring wheat in the United States and Canada which prevented the attainment of 90/90 accuracies in these regions. Technology solutions developed and tested in phase 3 partly resolved these issues with a significant improvement realized in the accuracy of the spring wheat area estimates.

Macdonald, R. B.↗

NASA NTRS1978

The outlook for satellite remote sensing for crop inventory

There are no author-identified significant results in this report.

Erb, R. B.↗

NASA NTRS1977

The large area crop inventory experiment: A major demonstration of space remote sensing

Strategies are presented in agricultural technology to increase the resistance of crops to a wider range of meteorological conditions in order to reduce year-to-year variations in crop production. Uncertainties in agricultral production, together with the consumer demands of an increasing world population, have greatly intensified the need for early and accurate annual global crop production forecasts. These forecasts must predict fluctuation with an accuracy, timeliness and known reliability sufficient to permit necessary social and economic adjustments, with as much advance warning as possible.

Macdonald, R. B.↗

NASA NTRS1977

The large area crop inventory experiment - A major demonstration of space remote sensing

The NASA-U.S. Department of Agriculture Large Area Crop Inventory Experiment (LACIE), aimed at using multispectral remote sensing data from Landsat 1 and 2 to generate accurate annual global crop production forecasts, is discussed. The forecasts take into account meteorological conditions as well as yield and acreage, and may be used to increase the discrimination of U.S. harvest estimates down to regional levels and to provide more accurate early-season predictions. Sample problems involving the determination of wheat harvests and the monitoring of drought conditions are described. Difficulties related to misidentification of abnormally-developing plantations, the automatic classification of homogeneous spectral groups, the computerized generation of colored maps, and the estimation of yields during years when exceptional meteorological conditions prevail are also considered. Samples of Landsat-generated classification maps for Western U.S. and for the Saratov, U.S.S.R. crop regions are given.

Macdonald, R. B.↗

NASA NTRS1977

LACIE: A look to the future

The Large Area Crop Inventory Experiment (LACIE) is a project designed to demonstrate the applicability of remote sensing technology to monitor globally an important world food crop - wheat. The need for more timely and reliable monitoring of food and fiber supplies is discussed, and the monitoring systems currently utilized are reviewed. The fundamentals involved in assessing the impact of variable weather and economic conditions on wheat acreage, yield, and production are elucidated. The experiment's approach to production monitoring is described, and its status is reviewed. Examples of acreage and yield monitoring in the Soviet Union are used to illustrate the experiment's approach.

Macdonald, R. B.↗

NASA NTRS1977

LACIE - A look to the future

The Large Area Crop Inventory Experiment (LACIE) is a 'proof of concept' project designed to demonstrate the applicability of remote sensing technology to the global monitoring of wheat. This paper discusses the need for more timely and reliable monitoring of food and fiber supplies, reviews the monitoring systems currently utilized by the USDA and United Nations Food and Agriculture Organization in the United States and in foreign countries, and elucidates the fundamentals involved in assessing the impact of variable weather and economic conditions on wheat acreage, yield, and production. The experiment's approach to production monitoring is described briefly, and its status is reviewed as of the conclusion of 2 years of successful operation. Examples of acreage and yield monitoring in the Soviet Union are used to illustrate the experiment's approach.

Macdonald, R. B.↗