Conference on
Machine Processing of
Remotely Sensed Data

October 16 - 18, 1973

The Laboratory for Applications of
Remote Sensing
Purdue University

West Lafayette
Indiana

Copyright © 1973
Purdue Research Foundation

These papers are provided for personal educational use only,
under permission from Purdue Research Foundation.

Conference Committee
C.D. McGillem, Chairman, M. Baumgardner, R. Bula, K. Fu, C. Jenks, T. Phillips, J. Rouse

Editorial Staff
C.D. McGillem, Editor; T.C. Builta, Asst. Editor; M. Svedlow, Asst. Editor

Cosponsors of the Conference
American Society of Agronomy, Central Indiana Section of IEEE, Computer Society of IEEE, Crop Science Society of America, Geoscience Electronics Group of IEEE, NASA, Purdue University, Soil Science Society of America

Preface

These Proceedings are made up of the contributed papers presented at the Conference on Machine Processing of Remotely Sensed Data held at Purdue University, October 16-18, 1973. It was the purpose of this conference to bring together engineers, scientists and other interested individuals for an in-depth presentation of new results in the theory, technology and application of computer processing of remotely sensed data. As evidenced by the papers contained herein the conference was successful in meeting its objective. It is hoped that these Proceedings will serve as a record and reference for those attending the conference and as a source of current research information for those unable to attend.
Clare D. McGillem, Conference Chairman.

Other symposium proceedings pages not included in the papers below.

Table of Contents

Technical Session 1a: Data Management and Processing Systems

  1. On the Management and Processing of Earth Resources Information. R.C. Gonzalez, University of Tennessee; C.W. Skinner. North Carolina State University. 1A-1. 11 pages.
  2. The Role of Computer Networks in Remote Sensing Data Analysis. J.C. Lindenlaub, T.L. Phillips, P.H. Swain. LARS, Purdue University. 1A-12. 7 pages.
  3. Combining Human and Computer Interpretation Capabilities to Analyze ERTS Imagery, J.D. Nichols, W.M. Senkus. University of Calibornia/Berkeley. 1A-19. 6 pages.
  4. The Design and Use of Special Purpose Processors for the Machine Processing of Remotely Sensed Data. G.R. Allen, L.O. Bonrun, J.J. Cosgrove, R.M. Stone. Control Data Corporation. 1A-25. 18 pages.

Technical Session 1b: Image Registration and Calibration

  1. Techniques for Image Registration. W.F. Webber. McDonnell Douglas Astronautics Company. 1B-1. 7 pages.
  2. A Method for Digital Image registtration Using a mathematical Programming Technique. S.S. Yao. Lockheed Electronics Company, Inc. 1B-8. 16 pages.
  3. Multitemporal Geometric distortion Correction Utilizing the Affine Transformation. R.A. Emmert, Lawrence Livermore Laboratory; C.D. McGillem, LARS/Purdue University. 1B-24. 9 pages.

Technical Session 2a: Land Use Planning Applications

  1. A land Use Classification System for Use with Remote-Sensor Data. J.R. Anderson, E. E. Hardy.  Cornell University. 2A-1. 6 pages.
  2. Urban Land-Use Mapping by Machine Processing of ERTS-1 Multispectral Data:  A San Francisco Bay Area Example.  R. Ellefsen, California State University/San Jose; P.H. Swain, LARS/Purdue University; J.R. Wray, U.S. Geological Survey. 2A-7. 16 pages.
  3. Land Use Classification of Marion County, Indiana by Spectral Analysis of Digitized Satellite Data.  M. Baumgardner, W.J. Todd, LARS/Purdue University. 2A – 23. 10 pages.
  4. ERTS-1 Aircraft Support, 24-Channel MSS CCT Experiences and Land Use Classification Results. M.R. Gautreaux, A.J. Richardson, C.L. Wiegand, USDA/Agricultural Research Service. 2A-33. 21 pages.
  5. A Computer Recognition of Bridges, Island, Rivers and Lakes from Satellite Pictures. R. Bajcsy, M. Tavakoli, University of Pennsylvania. 2A-54. 15 pages.
  6. Comparative Evaluation of Spatial Features in Automatic Land Use Classification from Photographic Imagery. J.H. Herzog, R.C. Rathja, Oregon State University. 2A-69. 8 pages.

Technical Session 2b: Geometrical Transformations and Mapping

  1. Correlation of ERTS MSS Data and Earth Coordinate Systems.  R.H. Hieber, W.A. Malila, A.P. McCleer, Environmental Research Institute of Michigan. 2B-1. 13 pages.
  2. Experience with the Program System KARIN for the Mapping of Remote Sensing Information. E.R. Bosman, E. Clerical, D. Eckhart, K. Kubik, Ministry of Water Control and Public Works/The Netherlands. 2B-14. 11 pages.
  3. Weighting Function Techniques for Storage and Analysis of Mass Remote Sensing Data. J.R. Jancaitis, J.L. Junkis, University of Virginia. 2B-25. 12 pages.

Technical Session 3a:  Earth Resource Measurements and Applications

  1. Mapping Soil Associations Using ERTS MSS Data. J.E. Cipra, LARS/Purdue University. 3A-1. 10 pages.
  2. Analysis of Remotely Sensed Data for Detecting Soil Limitations. L.A. Benson, C.J. Frazee, F.A. Waltz, South Dakota State University. 3A-11. 9 pages.
  3. Numerical Classification Procedures in Fluvial Geomorphology. G.C. Guatafson, University of Munich/West Germany. 3A-20. 15 pages.
  4. Computerized Interpretation of ERTS Data for Forest Management. L. Kirvida, Honeywell Inc. 3A-35. 7 pages.
  5. Classification of Turbidity Levels in the Texas Marine Coastal Zone. C.A. Reees, E.A. Weisblatt, Lockheed Electronics Company, Inc, J.B. Zaitzeff, NOAA. 3A-42. 18 pages.
  6. Pattern Analysis and Recognition Techniques Applied to the Identification of Ecological Anomalies. R.J. Hoffmann, J.E. Turinetti, Rome Air Development Center. 3A-60. 8 pages.

Technical Session 3b: Classification and Feature Selection I

  1. An Iterative Approach to the Feature Selection Problem. H.P. Decell, University of Houston, J.A. Quirein, TRW Systems. 3B-1. 12 pages.
  2. Feature Selection via an Upper Bound (to any Degree Tightness) on Probability of Misclassification.  C.R. Hallum, Loyola University. 3B-13. 14 pages.
  3. Extraction and Classification of Objects in Multispectral Images. T.V. Robertson, LARS/Purdue University. 3B-27. 8 pages.
  4. The Use of the Cholesky Decomposition in Divergence and Classification Calculations. M.S. Lynn, C.H. Snyder, D.L. Van Rooy, Rice University. 3B-35. 13 pages.
  5. Iterative Techniques to Estimate Signature Vectors for Mixture Processing of Multispectral Data. P. Salvato Jr, TRW Systems Group. 3B-48. 15 pages.

Technical Session 4a: Special Systems and Techniques

  1. Remote Wind Profile Measurement at Optical Frequencies Using a Spectral Density Approach. J.E. Nuwer, T.H. Pries, J. Smith, F.J. Taylor, University of Texas at El Paso. 4A-1, 13 pages.
  2. A Machine Processing of ERTS and Ground Truth Data.  K. Peacock, R.H. Rogers, Bendix Aerospace Systems Division. 4A-14, 14 pages.
  3. Information Preserving Coding for Multispectral Data.  J.R. Duan, P.A. Wintz, LARS/Purdue University. 4A-28, 8 pages.
  4. Fast Automated Analysis and Classification of Color Pictures by Signature and Pattern Recognition Using a Color Scanner. H.S. Helbig, Institute of Satellite Electronics/Germany. 4A-36. 5 pages.

Technical Session 4b: Classification and Feature Selection II

  1. Deriving Spectral and Spatial Features to Establish a Hierarchical Classification System. R.J. Hoffman, Rome Air Development Center, J.E. Skaley, Cornell University. 4B-1. 5 pages.
  2. Feature Extraction of Multispectral Data.  R.B. Crane, T. Crimmons, J.F. Reyer, Environmental Research Institute of Michigan. 4B-6. 10 pages.
  3. Estimation of Proportions of Objects and Determination of Training Sample-Size in a Remote Sensing Application.  R.S. Chhikara, P.L. Odell, University of Texas at Dallas.  4B-16.  9 pages.
  4. Machine Boundary Finding and Sample Classification of Remotely Sensed Agricultural Data.  J.N. Gupta, R.L. Kettig, D.A. Landgrebe, P.A. Wintz, LARS/Purdue University. 4B-25. 11 pages.
  5. The JSC Clustering Program ISOCLS and its Applications.  W.A. Holley, E.P.F. Kan, H.D. Parker, Lockheed Electronics Company, Inc. 4B-36. 15 pages.
  6. Multivariate Interactive Digital Analysis System (Midas): A New Fast Multispectral Recognition System.  C. Connell, M. Gordon, R. Kistler, F. Kriegler, S. Lampert, R. Marshall, Environmental Research Institute of Michigan. 4B-51. 13 pages.

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