Symposium
on
Machine Processing
of Remotely Sensed Data

June 29 - July 1, 1976

The Laboratory for Applications of
Remote Sensing
Purdue University

West Lafayette
Indiana

Copyright © 1976
The Institute of Electrical and Electronics Engineers, Inc.

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Symposium Committee
P.H. Swain, Symposium Chairman, M.E. Bauer, D.A. Landgrebe, J.C. Lindenlaub, D.B. Morrison, R.P. Mroczynski, T.L. Phillips

Editorial Staff
P.H. Swain, Editor; D.B. Morrison, Asst. Editor; D.E. Parks, Asst. Editor

Cosponsors of the Conference
American Society of Agronomy, Central Indiana Section of IEEE, Computer Society of IEEE, Crop Science Society, Geoscience Electronics Group of IEEE, NASA Office of Applications, Remote Sensing and Photogrammetry Working Group, Soil Science Society of America, with cooperation of The American Society of Photogrammetry

Library of Congress Catalog card Number 73-89454

Preface

The symposium for which these Proceedings are the written record marks two anniversaries.

Ten year ago several scientists and engineers at Purdue University joined forces to seek effective ways to bring the modern technologies of sensor systems and computers to bear on problems related to monitoring and managing the Earth's resources. Thus was born the Laboratory for Agricultural Remote Sensing (LARS), later to broaden its initial charter and become the Laboratory for Applications of Remote Sensing. In the years since, the importance of conserving our resources has become frighteningly apparent. As the urgency of this problem has grown, so too has the potential payoff of research into machine processing of remotely sensed data. Since 1966, when only a few relatively isolated organizations were pursuing this research, we have seen the evolution of a full-blown research commmunity, the scale and scope of which is well reflected by the list of contributors to this symposium.

Four years ago this July the first Earth Resources Technology Satellite, now called LANDSAT-1, was successfully orbited, and remote sensing took a giant stride forward. Through use of the LANDSAT data, it would soon be demonstrated more clearly than ever before that the synthesis of advanced sensor systems and data processing by computer could provide, on a cost-effective and timely basis, information vitally needed by those engaged in monitoring and planning the conservation of our resources.

Progress toward realizing the potential of this technology continues to be great on many fronts. Thus the purpose of these symposia on machine processing of remotely sensed data is to periodically bring together scientists, engineers, and others interested in an in-depth review of recent results in the theory and application of the technology.

These Proceedings contain the full text of the full-length papers plus the titles and abstracts of the short papers presented at this symposium and are intended not only as a record and reference for those attending the symposium but also as a source of current research information for those not able to attend.

Philip H. Swain
Symposium Chairman

Other symposium proceedings pages not included in the papers below.

Table of Contents

A Multidimensional Look at Remote Sensing. Plenary Session P-A. (Session Chair: Phillip H. Swain)

  1. A Review of the History of Multispectral Sensing and Image Processing. Archibald B. Park, Applications Program Manager, G.E. Space Systems Division. (no paper).
  2. The Applicatbility of LANDSAT Data to Water Management and Control Needs. J.W. Jarman, Chief, Office of Stafing and Management, U.S. Army Corps of Engineers. PA-1. 6 pages.
  3. A view of Remote Sensing Programs After LANDSAT C. William E. Stoney, Chief, Earth Observation, NASA. (no paper).
  4. Remote Sensing Technology - A Look to the Future. David A. Landgrebe, Director, LARS. PA-7. 12 pages.

Systems. Session 1-A. (Session Chair: David Simonett)

  1. IBIS: A Geographic Information System Based on Digital Image Processing and Image Raster Datatype. N. A. Bryant and A. L. Zobrist, JPL. 1A-1. 7 pages.
  2. KANDIDATS Image Processing System. R. M. Haralick, W. F. Bryant, G. J. Minden, A. Singh, C. A. Paul. University of Kansas. Dale R. Johnson. IBM. 1A-8. 10 pages.
  3. The Earth Resources Interactive Processing System (ERIPS) Image Data Access Method (IDAM). A. E. Pape, D. L. Truitt. IBM. 1A-18. 5 pages.
  4. PROCAMS: A Second Generation Multispectral-Multitemporal Data Processing System for Agricultural Mensuration. J. D. Erickson, R. F. Nalepka. ERIM. 1A-23. 5 pages

    Short Papers
  5. The Application of a Parallel Processing Computer in the Large Area Crop Inventory Experiment. S. Ruben. Goodyear. J. C. Lyon, M. J. Quinn, Jr.. NASA/JSC.   1A-28. 1 page.
  6. General Polygons Used to Determine Training and Test Areas in Digital Remote Sensing. R. H. Hieber. ERIM. 1A-29. 1 page.
  7. Processing Remotely Sensed Data with Array Processors. A. S. Margulies, CSPT. 1A-30. 1 page.

Natural Resources. Session 1-B. (Session Chair: Richard H. Gilbert)

  1. Resource Inventory Using LANDSAT Data for Areawide Water Quality Planning. R. N. Schecter. Triangle J Council of Governments. 1B-1. 10 pages.
  2. Analysis of Geophysical Remote Sensing Data Using Multivariate Pattern Recognition Techniques. P. E. Anuta, H. Hanuska, S. W. Levandowski. LARS. 1B-11. 4 pages.
  3. The Automated Recognition of Urban Development from LANDSAT Images. P. Carter. AERE Harwell. M. Jackson. Department of Environment. London. 1B-15. 10 pages.

    Short Papers
  4. Natural Resource Classification from LANDSAT Data Using a Film Recorder. R. A. Mead, J. A. Brass. University of Minnesota. 1B-25. 1 page.
  5. A Remote Sensing-Aided System for Evaporation and Watershed-Wide Evapotranspiration Estimation. S. Khorran, R. W. Thomas. University of California. 1B-26. 1 page.
  6. Use of Digital LANDSAT Data to Map the Geology of Ambrosia Lake, New Mexico. John O. Bennett. EXXON Production Research Co. 1B-27. 1 page.

Data Analysis I. Session 2-A. (Session Chair: Richard F. Nalepka)

  1. Linear Dimensionality of LANDSAT Agricultural Data with Implications for Classification. S. G. Wheeler, P. N. Misra. IBM. Q. A. Holmes. NASA/JSC. 2A-1. 9 pages.
  2. Tree System Approach for LANDSAT Data Interpretation. R. Y. Li, L. S. Fu. Purdue University. 2A-10. 8 pages.
  3. The Use of Spatial Characteristics for the Improvement of Multispectral Classification of Remotely Sensed Data. D. J. Wiersma, D. A. Landgrebe. LARS. 2A-18. 8 pages.
  4. Stratification of LANDSAT Data by Clustering. M. E. Bauer, B. J. Davis. LARS. 2A-26. 10 pages.
  5. LANDSAT Signature Development Program. R. N. Hall, K. G. McGuire. Federal Electric Corporation. R. A. Bland. NASA/JFK. 2A-36. 7 pages.

    Short Papers
  6. Hindu: Histogram Inspired Neighborhood Discerning Unsupervised Pattern Recognition System. B. V. Dasarathy. Computer Sciences Corporation. 2A-43. 1 page.
  7. Processing Multispectral Scanner Data Using Correlation Clustering and Nonparametric Classification Techniques. R. E. Haskell, D. E. Boddy. Oakland University. 2A-44. 1 page.

Research Forum: Data Processing. Session 2-B (Session Chair: Robert M. Haralick)

  1. A Non-Parametric Approach to Classifying Remotely Sensed Data. J. Tubbs. NRC/JSC. J. Engvall. JSC. 2B-1. 1 page.
  2. Evaluation of Image Registration Accuracy in the Large Area Crop Inventory Experiment. T. Kaneko. IBM. J. Engvall. NASA/JSC. 2B-2. 1 page.
  3. Determination of Planimetric Features by Interactive Image Processing. J. Y. C. Wang. Engineering Topographic Laboratories. 2B-3. 1 page.
  4. Generating Character Maps on a Remote Terminal By Use of Simplified Software. P. Poonai, W. J. Floyd. Bethune-Cookman College. R. Hall. Federal Electric Corporation. C. J. Upp.   Consultant on Remote Terminals. 2B-3. 1 page.
  5. Sequential Classification and Clustering Methods Applied to Digitized Photographs. C. P. Gleason. USDA. 2B-4. 1 page.
  6. Automated Ground Coordinate Sampling. G. E. Lukes. U. S. Army Topographic Laboratories. 2B-4. 1 page.
  7. Digital Image Processing of LANDSAT I MSS Data Specifically Designed for Linear Enhancement in Southwestern Jordan. P. S. Chavez, Jr., G. L. Berlin. A. V. Acosta. USGS. 2B-5. 1 page.
  8. Linear Atmospheric Transform on LANDSAT Measurements. R. K. Kiang. GTE Information Systems. W. E. Collins. Goddard. 2B-5. 1 page.
  9. Correcting LANDSAT Data for Changes in Sun Angle, Haze Level, and Background Reflectance. J. F. Potter. Lockheed. 2B-6. 1 page.
  10. SAR Enhancement of LANDSAT Imagery.   H. E. Maurer.   P. K. Clemens. NASA/Wallops. 2B-6. 1 page.
  11. Application of a Class of Sequential Classifiers to Multitemporal Remote Sensing Data. H. Hauska, P. H. Swain. LARS. 2B-7. 1 page.

USDA-SRS. Plenary Session P-B (Session Chairs: M. E. Bauer, W. H. Wigton)

  1. Current Methods and Policies of the Statistical Reporting Service. C. E. Caudill. SRS/USDA. PB-1. 5 pages.
  2. Use of LANDSAT Technology by Statistical Reporting Service. W. H. Wigton. USDA. PB-6. 5 pages.
  3. LANDSAT Estimation with Cloud Cover. G. A. Hanuschak. USDA.   PB-11. 3 pages.
  4. Illinois Crop-Acreage Estimation Experiment. R. M. Ray III. University of Illinois at Urbana-Champaign. H. F. Huddleston. USDA. PB-14. 8 pages.

Transfer of Technology. Plenary Session P-C (Session Chair: John C. Lindenlaub)

  1. University Education in Remote Sensing: Ill-defined and Ill-equipped. S. A. Morain. University of New Mexico. PC-1. 4 pages.
  2. So You Think You are Ready for Remote Sensing - Implementation Considerations of Remote Sensing Technology in a Private Industrial Environment. G. R. Barker. St. Regis Paper Company. PC-5. 5 pages.
  3. Pacific Northwest Resources Inventory Demonstration. J. D. Nichols. ESL Incorporated. PC-10. 6 pages.
  4. Remote Sensing - The Role of the Supplier. S. S. Viglione. McDonnell Douglas Astronautics Company. PC-16. 2 pages.
  5. Needed: A Better Approach to State and Federal Agencies. C. J. Johannsen. University of Missouri. PC-18. 3 pages.

Data Analysis II. Session 3-A (Session Chair: Fred C. Billingsley)

  1. An Approach to the Design of a Linear Binary Tree Classifier. K. C. You, K.S. Fu. Purdue University. 3A-1. 10 pages.
  2. Selecting Class Weights to Minimize Classification Bias in Acreage Estimation. W. M. Belcher, T. C. Minter. Lockheed. 3A-11. 5 pages.
  3. Estimation of the Probability of Error Without Ground Truth and Known a Priori Probabilities. K. A. Havens, T. C. Minter, S. G. Thadani. Lockheed. 3A-16. 6 pages.
  4. Bayes Estimation on Parameters of the Single-Classifier. G. C. Lin, T. C. Minter. Lockheed. 3A-22. 6 pages.
  5. Number of Signatures Necessary for Accurate Classification. W. Richardson, A. Pentland, R. Crane, H. Horwitz. ERIM. 3A-28. 7 pages.

    Short Papers
  6. Classification by Clustering. A. Pentland. ERIM. 3A-35. 1 page.
  7. Improved Signature Definition Through Boundary-Edited Clustering. D. P. Rice. ERIM. 3A-36. 1 page.

Research Forum: Applications. Session 3-B (Session Chair: David Simonett)

  1. Comparison of Vegetation Classes in the Great Dismal Swamp Using Two Individual LANDSAT Images and a Temporal Composite. P. T. Gammon. Dismal Swamp National Wildlife Refuge. V. P. Carter. USGS. 3B-1. 1 page.
  2. Computer Location of Citrus Trees Using Color Aerial Infrared Transparencies. D. H. Williams, J. K. Aggarwal. University of Texas at Austin. 3B-2. 1 page.
  3. Land Use Studies with SKYLAB S-l92 Data. D. S. Simonett. University of California at Santa Barbara. R. L. Shotwell, N. Belknap. EARTHSAT. 3B-3. 1 page.
  4. Remote Sensing Applications for Identifying Potential Recreation Resources. W. C. Beattie, K. A. Wenner. Ohio State University. 3B-4.   1 page.
  5. Thermal Sensing of the Chihuahuan Feasibility Study with the NOAA-4. W. R. Hazard. University of Texas. 3B-5. 1 page.
  6. Statistical Analysis of Texture in LANDSAT Images of the United Kingdom. R. M. Lee, P. Gray, M. E. Barnett. Blackett Laboratory. 3B-6. 1 page.
  7. A Real Time Freeze Prediction Model Based Upon Remotely Sensed Surface Temperatures. R. A. Sutherland, J. F. Bartholic. University of Florida. 3B-6. 1 page.
  8. Digital Analysis of Human Impact on Tropical Vegetation. S. Textor. Columbia University. J. C. Coiner. Goddard. 3B-7. 1 page.
  9. Forest Type Mapping Using Computer Classification of LANDSAT Data. E Bryant. Goddard. A. G. Dodge, Jr.. University of New Hampshire. 3B-7. 1 page.
  10. A Computerized Mapping System for Forest Resource Management Planning. D. W. Smith, S. A. Nottingham, C. W. Wade. Virginia Polytechnic Institute and State University. 3B-8. 1 page.

Preprocessing. Session 4-A (Session Chair: Paul E. Anuta)

  1. Effects of Misregistration on Multispectral Recognition. R. C. Cicone, W. A. Malila, J. M. Gleason, R. F. Nalpeka. ERIM. 4A-1. 8 pages.
  2. Experimental Examination of Similarity Measures and Preprocessing Methods Used for Image Registration. M. Svedlow, C. D. McGillem, P. E. Anuta. LARS. 4A-9. 9 pages.
  3. A LANDSAT Digital Image Rectification System.  P. Van Wie, M. Stein. Goddard. 4A-18. 9 pages.
  4. Filtering to Remove Cloud Cover in Satellite Imagery. O. R. Mitchell, P. L. Chen. Purdue University. 4A-27. 5 pages.
  5. Experiments in Iterative Enhancement of Linear Features. G. J. Vanderbrug. University of Maryland. 4A-32
  6. Signature Extension Through the Application of Cluster Matching Algorithms to Determine Appropriate Signature Transformations. P. F. Lambeck, D. P. Rice. ERIM. 4A-45. 7 pages.

Agriculture/Forestry. Session 4-B (Session Chair: Warren E. Frayer)

  1. Automatic Detection and Classification of Infestations of Crop Insect Pests and Diseases from Infrared Aerial Color Photographs. M. Ali, J. K. Aggarwal. University of Texas at Austin.   4B-1. 11 pages.
  2. LANDSAT Forest and Range Inventory of Southeast Texas Counties by Administrative Boundaries. C. A. Reeves, T. Austin, A. Kerber. Lockheed. 4B-12. 12 pages.
  3. Evaluation of Classification Procedures for Estimating Wheat Acreage in Kansas. L. M. Flores, D. T. Register. Lockheed. 4B-24. 10 pages.
  4. Machine Estimation of Timber Volumes for Use in Sampling Surveys--A method for High Flight and Space Imagery, Interface Considerations and Results. J. W. van Roessel. Earth Satellite Corporation. 4B-34. 7 pages.
  5. The Tasselled Cap -- A graphic Description of the Spectral-Temporal Development of Agricultural Crops as seen by LANDSAT, Kauth, R.J., G.S. Thomas. ERIM. 4B-41, 11 pages.

    Short Papers
  6. Computer Analysis of Remotely Sensed Wheat Canopy Data. M. S. Sohel. Prairie View A&M University. 4B-52. 1 page.
  7. A New Computer Approach to Mixed Feature Classification for Forestry Application. E. P. Kan, J. K. Lo. Lockheed. 4B-53. 1 page.

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