Skip to main content

Data base requirements for remote sensing and image processing applications

  • 4. Remote Sensing And Image Processing Applications
  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 81))

Abstract

Remote sensing of the earth has evolved from a film based, manual interpretation technology to a digital multispectral and multisensor technology with significant machine processing for correction, information extraction, data management, and modelling. This transition is not without growing pains. Of the 1015 bits of data that are currently acquired per year in the NASA program, only about 1013 bits are utilized. Future programs involving higher resolution and wider spectral range sensors will increase the data acquisition rates by an order of magnitude. Technological problems exist today in data correction, information extraction, processing, storage, retrieval and dissemination. This paper will identify some of the data base requirements for future programs, and discuss technological approaches for improving the handling and processing of remotely sensed data. Fundamental to this approach is the concept of a global data and information base that is geographically accessible, contains data from all earth observation programs, and is easily and economically disseminated. This capability is needed, and the technology is available for its implementation.

This is a preview of subscription content, log in via an institution.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Anderson, J. R., Hardy, E. E., Roach, J. T., and Witmer, R. E. (1976). A Land Use and Land Cover Classification System for Use with Remote Sensor Data, U.S. Geological Survey Paper #964, U.S. Government Printing Office, Washington, D.C.

    Google Scholar 

  • Anuta, P. E. (1970). Spatial Registration of Multispectral and Multitemporal Digital Imagery Using Fast Fourier Transform Techniques. IEEE Transactions on Geoscience Electronics, Vol. GE-8, pp. 353–368.

    Google Scholar 

  • Aviation Week & Space Technology, (1979). Earth Resources Concepts Proposed, March 26, 1979, pp. 46–53.

    Google Scholar 

  • Bernstein, R. (1978). Digital Image Processing for Remote Sensing. (Edited). IEEE Press & J. Wiley, pp. 121–174.

    Google Scholar 

  • Bernstein, R. (1975). All-Digital Precision Processing of ERTS Data. NASA Final Report, Contract No. NAS5-21716, FSD-75-0009.

    Google Scholar 

  • Catoe, C. E. (1978). End-to-End Data/Information Systems Concept: The Solution or the Problem? 8th Annual Remote Sensing Conference Proceedings, Space Institute, University of Tennessee.

    Google Scholar 

  • Colwell, R. N. (1974). Keynote Address, 1974 Annual Convention of the American Congress of Surveying and Mapping, American Society of Photogrammetry.

    Google Scholar 

  • Computer Design, (1979). Parallel Processor Will Be Capable of Performing 6 G Additions/S., pp. 55–56, March 1979.

    Google Scholar 

  • Foster, H. D. (1977). A Remote Sensing System for a Nationwide Data Bank, Proceedings, 1977 Machine Processing of Remotely Sensed Data Symposium, Purdue University, Lafayette, Indiana.

    Google Scholar 

  • Greenwood, L. R. (1978). Environmental Observations from Space; Present and Future. EASCON 1978 Record, IEEE Publication 78CH 1354-4 AES, 1978.

    Google Scholar 

  • Landgrebe, D. (1976). Computer-Based Remote Sensing Technology — A Look to the Future. Remote Sensing of the Environment, Vol. 5, No. 4.

    Google Scholar 

  • Martin, J. (1971). Future Developments in Telecommunications, Prentice-Hall.

    Google Scholar 

  • Nagler, R. G. (1978). Satellite Measurement Capabilities for Environmental and Resource Observations. EASCON 1978 Record, IEEE Publication 78CH 1354-4 AES.

    Google Scholar 

  • NASA 5-Year Planning, Fiscal Years 1979 through 1983. NASA Headquarters, Washington, D.C., March 1, 1978.

    Google Scholar 

  • Rosenfeld, A. (1969). Picture Processing by Computers. Academic Press, New York.

    Google Scholar 

  • Schoene, L. P. (1977). Master Data Processor, Technical Directions, FSD, Autumn 1977, Vol. 3, No. 2.

    Google Scholar 

  • Thompson, L. L. (1979). Remote Sensing Using Solid-State Array Technology, Photogrammetric Engineering and Remote Sensing. Vol. 45, No. 1, pp. 47–55.

    Google Scholar 

  • Van Vleck, E. M., Sinclair, K. F., Pitts, S. W., and Slye, R. E. (1973). Earth Resources Ground Data Handling Systems for the 1980's. NASA TMX-62, 240, p. 12.

    Google Scholar 

  • Wu, C. (1975). The Decision Tree Approach to Classification. PhD Thesis, Purdue University.

    Google Scholar 

  • Wood, J. T. (1976). Cartographic Data Available to Coastal Planners, 2nd Annual Pecora Symposium, ASP & USGS.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

A. Blaser

Rights and permissions

Reprints and permissions

Copyright information

© 1980 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bernstein, R. (1980). Data base requirements for remote sensing and image processing applications. In: Blaser, A. (eds) Data Base Techniques for Pictorial Applications. Lecture Notes in Computer Science, vol 81. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-09763-5_17

Download citation

  • DOI: https://doi.org/10.1007/3-540-09763-5_17

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-09763-1

  • Online ISBN: 978-3-540-38651-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics