Fifth Annual Symposium
on
Machine Processing
of Remotely Sensed Data

The Laboratory for Applications of Remote Sensing
Purdue University
West Lafayette, Indiana 47907 USA

June 27-29, 1979

Edited by I. M. Tendam and D.B. Morrison
Cover Design and Layout by S. L. Ferringer

Copyright © 1979
The Institute of Electrical and Electronics Engineers, Inc.

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CATALOG NUMBERS

IEEE CATALOG NUMBER 79CH 1430 - 8 MPRSD
LIBRARY OF CONGRESS CATALOG NUMBER 78-78266

PREFACE

These Proceedings contain the written text of the long papers and the short paper abstracts presented during the Fifth Symposium on Machine Processing of Remotely Sensed Data.   The program features an Opening Plenary Session focusing on the Landsat-D project and Thematic Mapper (TM) development, nine Technical Sessions on the theory, implementation and applications of machine processing of remotely sensed data, and a Closing Plenary Session projecting the Future of Data Processing in Remote Sensing.   This symposium was designed to provide an opportunity for scientists working in machine processing of remotely sensed data to share current research and applications results with the scientific and user community at large and to serve as a catalyst to foster further development of the technology.

In addition to the formal presentations which are documented in these Proceedings, an evening discussion session was also included in the program to stimulate a more direct interchange of ideas on specific topics of interest.

The success of this symposium rests largely on the cooperation that the Laboratory for Applications of Remote Sensing has had from the co-sponsoring organizations, and the valuable technical and organizational input received from the program committee members and session chairmen.

Symposium Co-Chairman: Luis A. Bartolucci

Dr. Bartolucci received his B.S., M.S., and Ph.D. in Geophysics from Purdue University.   He has been involved in Remote Sensing research since 1969.   He has played an active role in the development of remote sensing technology applied to water resources and in the field of thermal infrared radiation.   Dr. Bartolucci has served as consultant to the U.S. Information Agency, the U.S. Agency for International Development, the Interamerican Development Bank and to several Latin American development agencies.   He as been Principal Investigator and Project Director of several domestic and international research and training programs involving computer-aided processing and analysis of remotely sensed data for earth resources inventories.   Dr. Bartolucci is currently responsible for the LARS educational and training programs.

Symposium Co-Chairman: Leroy F. Silva

B.S.E.E., Purdue University; M.S.E.E., Massachusetts Institute of Technology; Ph.D., Purdue University.   He has been employed by Lincoln Laboratories; Ballistic Research Lab, Aberdeen Proving Ground, Maryland; and C P Electronics, Inc., Columbus, Indiana.   He has also been a consultant in electronics and magnetics to several companies.   Dr. Silva has been associated with LARS since 1969, and has published in the areas of electronics, magnetics, optics, bioengineering and remote sensing.   He is a member of the Institute of Electrical and Electronic Engineers (Senior Member ) and the National Society of Professional Engineers and the American association for the Advancement of Science.   He is a Registered Professional Engineer, State of Indiana.

CO-SPONSORING ORGANIZATIONS

AMERICAN SOCIETY OF PETROLEUM GEOLOGISTS
AMERICAN SOCIETY OF AGRONOMY
AMERICAN SOCIETY OF PHOTOGRAMMETRY
CROP SCIENCE SOCIETY OF AMERICA
INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, INC.
            CENTRAL INDIANA SECTION
            COMPUTER SOCIETY
            GEOSCIENCE ELECTRONICS GROUP
NATIONAL AERONAUTICS AND SPACE ADMINISTRATION
REMOTE SENSING WORKING GROUP OF SOCIETY OF AMERICAN FORESTERS
SOIL SCIENCE SOCIETY OF AMERICA

SYMPOSIUM PROGRAM COMMITTEE

LUIS A. BARTOLUCCI, CO-CHAIRMAN
LEROY F. SILVA, CO-CHAIRMAN
SHIRLEY M. DAVIS
ROGER M. HOFFER
DAVID LANDGREBE
DOUGLAS B. MORRISON
JOHN B. PETERSON
TERRY L. PHILLIPS
RICHARD A. WEISMILLER

Other symposium proceedings pages not included in the papers below.

TABLE OF CONTENTS

1.0   OPENING PLENARY SESSION - THEMATIC MAPPER

  1. An Overview of the Landsat-D Project with Emphasis on the Flight Segment. Vincent V. Salomonson, Laboratory for Atmospheric Sciences; and A. B. Park, General Electric Company. Page 2. 10 pages.
  2. Design Challenges of the Thematic Mapper. L. E. Blanchard and Oscar Weinstein, Hughes Aircraft Company and Goddard Space Flight Center. Page 12. 1 page.
  3. Landsat-D Data Acquisition and Processing. Pierce L. Smith, Jr. and William C. Webb, NASA/Goddard Space Flight Center. Page 13. 8 pages.
  4. Landsat-D: International Interests and Plans. James V. Zimmerman, NASA Headquarters. Page 21. 1 page.
  5. Thematic Mapper Agricultural Applications Performance - Speculations and Implications for Research. M. C. Trichel and J. D. Erickson, NASA/Johnson Space Center. Page 22. 1 page.

2.1   PREPROCESSING I - PREPROCESSING

  1. A Method of Interpolation in Two Dimensions, and its Application to Multispectral Image Registration. Maria Garza and Renato Barrera, IIMAS, UNAM. Page 26. 8 pages.
  2. Transformation of Atmospheric and Solar Illumination Conditions on the CCRS Image Analysis System. Francis J. Ahern, Philippe M. Teillet and David G. Goodenough, Canada Centre for Remote Sensing. Page 34. 19 pages.
  3. Effect of the Atmosphere on the Classification of Landsat Data. Tsutomu Morimoto, Ravindra Kumar, and Luiz Carlos Baldicero Molion, Instituto de Pesquisas Espaciais. Page 53. 5 pages.
  4. Landsat MSS Coordinate Transformations. Berthold K. P. Horn, Massachusetts Institute of Technology; Rober J. Woodham, University of British Columbia. Page 59. 10 pages.
  5. California Desert Resource Inventory Using Multispectral Classification of Digitally Mosaicked Landsat Frames. Nevin A. Bryant, Ronald G. McLeod, Albert L. Zobrist, Jet Propulsion Laboratory; and Hyrum B. Johnson, Bureau of Land Management. Page 69. 11 Pages.

    6. Short Papers
  6. The Control Point Library Building System. Wayne Niblack, IBM. Page 80. 1 page.
  7. Precision Requirement in Measuring Aerosol Load for Remote Sensing Application. R. K. Kiang, S. G. Ungar, NASA/Goddard Institute for Space Studies; and E. S. Bryant, Dartmouth College. Page 81. 1 page.
  8. Atmospheric Effects on Band-Ratioing in Vegetation Monitoring from Satellites. J. Otterman, Tel Aviv University; and S. G. Ungar, R. K. Kiang, NASA/Goddard Institute for Space Studies. Page 82. 1 page.
  9. Three-Dimensional Object Representation for Exploitation of Remote Sensed Images. Michael Shantz and George Huang, Ford Aerospace & Comm. Corp. Page 83. 1 page.
  10. Some Effects of Nearest Neighbor, Bilinear Interpolation, and Cubic Convolution Resampling on Landsat Data. Jeanne Etheridge, LARS and Charles Nelson, EROS Data Center. Page 84. 1 page.

2.2   APPLICATIONS TO AGRICULTURAL CROPS I

  1. Crop-Area Estimates from Landsat; Transition from Research and Development to Timely Results. George Hanuschak, Richard Sigman, Michael Craig, Martin Ozga, Raymond Luebbe, Paul Cook, David Kleweno and Charles Miller, USDA/Economics, Statistics, and Cooperative Services. Page 86. 11 pages.
  2. Sampling for Area Estimations: A Comparison of Full-Frame Sampling with the Sample Segment Approach. Marilyn M. Hixson, Marvin E. Bauer, Purdue University; and Barbara J. Davis, Indiana Bell Telephone Company. Page 97. 8 pages.
  3. Multi-Temporal Classification of Winter Wheat Using a Growth State Model. Christine A. Hlavka, Stephen M. Carlyle, University of Kansas; Ryozo Yokoyama, Itawe University-Japan; and Robert M. Haralick, Virginia Polytechnic Institute. Page 105. 11 pages.

    4. Short Papers
  4. The LACIE Outlook. Forrest Hall, NASA/Johnson Space Flight Center. Page 116. 1 page.
  5. LACIE Results. Forrest Hall, NASA/Johnson Space Flight Center. Page 117. 1 page.
  6. LACIE Experiment Design. Forrest Hall, NASA/Johnson Space Flight Center. Page 118. 1 page.
  7. LACIE Overview. Forrest Hall, NASA/Johnson Space Flight Center. Page 119. 1 page.

2.3   APPLICATIONS TO LAND USE

  1. A Non-Interactive Approach to Land Use Determination. V. Ralph Algazi, Gary E. Ford, and Doreen I. Meyer, University of California. Page 122. 10 pages.
  2. Landsat-2 Data for Inventorying Rangelands in South Texas. James H. Everitt, Arthur J. Richardson, Alvin H. Gerbermann, A. Alaniz, USDA-SEA-AR-SR. Page 132. 10 pages.
  3. A Methodology for a National Coverage Land Use Study by Computer. Jose Armando Diez P., Socrates A. Rivera R., Grupo de Fisica and Miguel Medina G., Comision del Plan Nacional Hidraulico. Page 142. 7 pages.
  4. The Use of Landsat Multispectral Data to Drive Land Cover Information for the Location and Quantification of Non-Point Source Water Pollutants. Henry F. Fostel, Baltimore Regional Planning Council; James E. Manley, OMNI Information Services; and James P. Ormsby, Goddard Space Flight Center. Page 149. 10 pages.
  5. Computer Aided Assessment of Revegetation on Surface Mine Land Utilizing Color Infrared Aerial Photography. William D. McFarland, Terry W. Barney, Chris J. Johannsen, University of Missouri-Columbia. Page 159. 12 pages.

    6. Short Papers
  6. Development of a Mini-Computer Method to Detect Geologic Faults and Other Linear Features from Landsat Imagery for Mining Production Purposes. Richard G. Burdick, Denver Mining Research Center. Page 166. 1 page.
  7. Application of a Principal Components Analysis on Landsat Multispectral Data for Studies on Vegetation Cover Under Desert Conditions. Jelle U. Hielkema, Food and Agriculture Organization of the United Nations. Page 167. 1 page.
  8. The Monitoring of Marine Environmental Problems by Airborne and Landsat MSS Data. Hiroaki Ochiai, Toba Merchant Marine College; and Shoji Takeuchi, Remote Sensing Technology Center of Japan. Page 168. 1 page.
  9. Estimation of Soil Moisture Status and Actual Evapotranspiration Using Remotely Sensed Data. R. J. Gurney, Institute of Hydrology. Page 169. 1 page.
  10. The Use of Image Analysis Techniques with Geophysical Data. Robert D. Regan and John DeNoyer, Phoenix Corporation and the U.S. Geological Survey. Page 170. 1 page.

3.1   DATA PREPROCESSING II - SYSYTEMS

  1. Identification of Surface-Disturbed Features through ISURSL Non-Parametric Analysis of Landsat MSS Data. Leonard H. Alger, Paul W. Mausel, Robert R. Herner, Indiana State University. Page 172. 11 pages.
  2. A Merged Satellite Infrared and Manually Digitized Radar Product. Marshall P. Waters III, and Robert N. Green, National Environmental Satellite Service. Page 183. 9 pages.
  3. Heterarchical Architectures for Parallel Processing of Digital Images. Adolfo Guzman, A. Zorrilla, Computer Science Department, IIMAS University - Mexico. Page 192. 1 page.
  4. Analyzing Accuracy Attributes of Landsat and Digital Terrain Tape Data in the Context of a Digital Geobase Information System. Douglas A. Stow, John E. Estes, University of California at Santa Barbara. Page 193. 9 pages.
  5. An Image Registration Algorithm Using Sample Binary Correlation. Ernest W. Cordan Jr., Martin Marietta Aerospace Corporation; and Benjamin W. Patz, University of Central Florida. Page 202. 11 pages.
  6. A Parametric Model for Multi-spectral Scanners. Bijan G. Mobasseri, Clare D. McGillem, Paul E. Anuta, Purdue University. Page 213. 9 pages.

    7. Short Papers
  7. Imagery Processing System and Its Applications. N. V. Kulkov and V. P. Pyatkin, Computing Center, USSR. Page 222. 1 page.

3.2   APPLICATIONS TO SOILS

  1. Pasture/Wheat Surface Temperature Differences: Indicator of Relative Soil Moisture Difference. Wesley D. Rosenthal, J. C. Harlan, Bruce J. Blanchard, Texas A&M University; and G. Coleman, USDA-SEA-AR. Page 224. 10 pages.
  2. Mapping and Estimating Aerial Extent of Severely Eroded Soils of Selected Sites in Northern Indiana. C. E. Seubert, M. F. Baumgardner, R. A. Weismiller, Purdue University and F. R. Kirschner, USDA/Soil Conservatin Service. Page 234. 16 pages.
  3. Landsat MSS Data as an Aid to Soil Survey - An Operational Concept. R. A. Weismiller, S. K. Kast, M. F. Baumgardner, Purdue University; and F. R. Kirshchner, USDA/Soil Conservation Service. Page 240. 2 pages.
  4. Extraction of Soil Information from Vegetated Area. Michikazu Fukuhara, Shigechika Hayashi, Hokkaido National Agricultural Experiment Station; Yoshizumi Yasuda, Ichio Asanuma, Yasufumi Emori, Institute of Color Technology/Chiba University; and Joji Iisaka, IBM - Japan. Page 242. 11 pages.
  5. Extension of Laboratory-Measured Soil Spectra to Field Conditions. Eric R. Stoner, Marion F. Baumgardner, Richard A. Weismiller, Larry L. Biehl, Barrett F. Robinson, Purdue University/LARS. Page 253. 11 pages.
  6. Predictability of Change in Soil Reflectance on Wetting. John B. Peterson, Barrett F. Robinson, Purdue University/LARS; and Robert H. Beck, University of Illinois. Page 264. 11 pages.

    7. Short Papers
  7. A Comprehensive Computer-Aided Soil Map Obtained via Satellite MSS Data. S. J. Kristof, Purdue University/LARS. Page 275. 1 page.

3.3   TECHNOLOGY TRANSFER

  1. Transfer of Remote Sensing Computer Technology to the Developing World - Case Examples. Charles K. Paul, Agency for International Development. Page 278. 6 pages.
  2. Evaluation of Remote Sensing Technology for Natural Resources Inventories in Central America. Pierre-Marie Adrien, Inter-American Development Bank; and Luis A. Bartolucci, Purdue University/LARS. Page 284. 2 pages.
  3. IMAGENET - An Image Analysis Network. P. R. Pearl, DIPIX Systems Ltd. Page 286. 8 pages.
  4. A System for Processing Landsat and Other Georeferenced Data for Resource Management Applications. Sidney L. Whitley, Earth Resources Laboratory, NASA. Page 294. 10 pages.
  5. Georgia's Operational Landsat Processing System. N. L. Faust, L. E. Jordan, Georgia Tech; and B. Q. Rado, State of Georgia. Page 304. 7 pages.

    6. Short Papers
  6. OCCULT - A Medium for Technology Transfer. H. K. Ramapriyan, Goddard Space Flight Center; and K. P. Young, Computer Sciences Corporation. Page 311. 1 page.
  7. Experience Derived from Transfer of JPL's VICAR Image Processing System to Other Organizations. W. B. Green, Jet Propulsion Lab. Page 312. 1 page.

4.1   DATA PROCESSING III - INFORMATION EXTRACTION

  1. Directed Canonical Analysis and the Performance of Classifiers Under Its Associated Linear Transformations. Benjamin F. Merembeck, Brian J. Turner, The Pennsylvania State University. Page 314. 9 pages.
  2. An Approach to Nonlinear Mapping for Pattern Recognition. Nguyen Duong, Ruh-Ming Li, Daryl B. Simons, Colorado State University. Page 323. 8 pages.
  3. An Analytical Approach to the Design of Spectral Measurements in the Design of Multispectral Sensor. Daniel J. Wiersma, Minneapolis Honeywell; and David A. Landgrebe, Purdue University/LARS. Page 331. 12 pages.
  4. A Method for Classifying Multispectral Remote Sensing Data Using Context. Philip H. Swain, Howard J. Siegel, Bradley W. Smith, Purdue University. Page 343. 9 pages.

    5. Short Papers
  5. An Alternative Approach to Training Analysis. Douglas E. Meisner and Thomas A. Lillesand, University of Minnesota. Page 354. 1 page.
  6. Threshold Selection for Line Detection Algorithms. Charlotte M. Gurney, Department of Geography, University of Reading and Image Analysis Group, A.E.R.E., Harwell, U.K. Page 355. 1 page.
  7. The Use of Prior Probabilities in Maximum Likelihood Classification. Alan H. Strahler, University of California at Santa Barbara. Page 356. 1 page.
  8. A New Model for Estimating Proportions of Land Cover Classes Within a Pixel. Curtis E. Woodcock, T. R. Smith, A. H. Strahler, University of California at Santa Barbara. Page 357. 1 page.
  9. An Inter-Class Feature Selection Procedure. Manmohan Trivedi, Clair L. Wyatt and David R. Anderson, Utah State University. Page 358. 1 page.
  10. Training Samples for Classification of Multispectral Earth Observation Data. Marwan J. Muasher, David A. Landgrebe, Purdue University/LARS. Page 359. 1 page.
  11. Image Representation of Digital Remote Sensing Data: A Perspective. David M. Freeman, Purdue University/LARS. Page 360. 1 page.
  12. An Unsupervised Procedure Using Multi-Dimensional Histogram Information. D. S. Kamat, K. Padmanabhan, and K. L. Majumdar, Space Applications Centre, India. Page 361. 1 page.

4.2   APPLICATIONS TO FORESTRY

  1. Using Guided Clustering Techniques to Analyze Landsat Data for Mapping Forest Land Cover in Northern California. Lawrence Fox III and Kenneth E. Mayer, Humboldt State University. Page 364. 4 pages.
  2. A Forester's Look at the Application of Image Manipulation Techniques to Multitemporal Landsat Data. Darrel L. Williams, NASA/Goddard Space Flight Center; and Mark L. Staufer, K. C. Leung, Computer Sciences Corporation. Page 368. 9 pages.
  3. Machine Processing of Landsat MSS Data and DMA Topographic Data for Forest Cover Type Mapping. Michael D. Fleming and Roger M. Hoffer, Purdue University/LARS. Page 377. 14 pages.
  4. Implications of Ten-Ecosystems Study Results to the Future Operational Use of Landsat Technology by the U.S. Forest Service. F. P. Weber, USDA Forest Service; and A. V. Mazade, R. E. Joosten, NASA/JSC. (no paper)
  5. Texture Analysis by Space Filter and Application to Forest Type Classification. Joji Iisaka, Tokyo Scientific Center, IBM Japan, Ltd. Page 392. 2 pages.

    6. Short Papers
  6. The Error Associated with Density Number (DN) Resampling of Landsat Forest Imagery for Multidate Registration. Thomas L. Logan, Jet Propulsion Laboratory. Page 394. 1 page.
  7. Use of a Standard Deviation Based Texture Channel for Landsat Classification of Forest Strata. Thomas L. Logan, Informatics, Inc.; and Alan H. Strahler, Curtis E. Woodcock, University of California at Santa Barbara. Page 395. 1 page.

4.3   APPLICATIONS TO AGRICULTURAL CROPS II

  1. Computer Recognition of Citrus Infestations. D. H. Williams, University of Texas at El Paso; and J. K. Aggarwal, University of Texas at Austin. Page 398. 10 pages.
  2. An Interactive Color Display System for Labelling Crops. Toyohisa Kaneko, Linda K. Moore, and Robert T. Smart, IBM - Federal Systems Division. Page 408. 12 pages.
  3. Classification of Areas Using Pixel-By-Pixel and Sample Classifiers. Ravindra Kumar, Madelena Niero, Adalton Paes Manso, Liani Antunes Maciel Lucht and Maria Suelena Santiago Barros, Instituto de Pesquisas Espaciais (INPE/CNPq). Page 420. 9 pages.

    4. Short Papers
  4. An Integrated Application of Remote Sensing, Digitization and Computer Processing to the Analysis of Multiple Tidal Drainage Networks. Joe R. Wadsworth, Jr. and Zee Berger, University of Georgia. Page 429. 1 page.
  5. Lithologic Discrimination by Fourier Analysis of Image Texture. Michael Daily, Susan Williams and William D. Strombert, Jet Propulsion Laboratory/California Institute of Technology. Page 430. 1 page.
  6. Small Area Replacement in Digital Thematic Maps. P. J. Letts, DIPIX Systems, Ltd. Page 431. 1 page.
  7. Agricultural Systems in East Africa Viewed from Landsat. Tina K. Cary, Columbia University and Goddard Institute for Space Studies. Page 432. 1 page.
  8. Applications of Landsat Data for Resource Inventories on Federal Lands in the Western United States. William D. DiPaolo, U.S. Bureau of Land Management (BLM). Page 433. 1 page.

5.0   CLOSING PLENARY SESSION - A LOOK AT THE FUTURE OF DATA PROCESING IN REMOTE SENSING

  1. Future Trends in Image Processing Software and Hardware. William B. Green, Jet Propulsion Laboratory. Page 436. 11 pages.
  2. Machine Processing Issues in Crop Type Identification and Estimation. Forrest G. Hall, NASA/Johnson Space Flight Center. Page 447. 1 page.
  3. The Need for New and Combined Techniques for Processing Future Types and Combinations of Data. George McMurtry, ORSER/The Pennsylvania State University. (no paper)
  4. A Digital Processor for the Production of SEASAT Synthetic Aperture Radar Imagery. John R. Bennett and Ian G. Cumming, MacDonald, Dettwiler & Associates, Ltd., Richmond, B.C., Canada. Page 449. 1 page.

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