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Mapping with census data and Landsat imagery

  • 1. Geographic Applications — Mapping
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Data Base Techniques for Pictorial Applications

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

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Abstract

Computer analysis of Landsat data can provide several types of useful information in urban and near-urban areas. Thematic classification gives a map of land cover or land use and multi-pass registration can detect areas of change or urban growth. These derived products have roughly the same character as Landsat; they are computer compatible, are in image format, and have a peculiar map projection. Geographic operations on these data require integration with standard digitized (vector) representations of point, line, and area data. One example is generation of maps superimposing image and boundary data. Another example is tabulation of the image data by district polygons.

The approach described here uses image processing technology to perform spital or geographic operations and concentrates upon the use of the image raster as a general representation for spatial data. Operations are provided for conversion of graphics (vector) data to image format, and for linking of image data to tabular files.

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9. References

  • Bauer, M.E., Cipra, J.E., Anuta, P.E., and Etheridge, J.B. (1979). Identification and area estimation of agricultural crops by computer classification of Landsat MSS data. Remote Sensing of Environment 8, 77–92.

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  • Bryant, N.A., and Zobrist, A.L. (1977). IBIS: a geographic information system based on digital image processing and image raster datatype. IEEE Transactions on Geoscience Electronics, GE-15, 13, 152–159.

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  • Tobler, W., and Lau, J., (1978). Isopleth mapping using histosplines. Geographical analysis, 10, 3, 273–279.

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  • U.S. Bureau of the Census, (1970). Census Use Study: The DIME Geocoding System, Report No. 4, Washington, D.C.

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A. Blaser

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© 1980 Springer-Verlag Berlin Heidelberg

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Zobrist, A.L. (1980). Mapping with census data and Landsat imagery. 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_3

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  • DOI: https://doi.org/10.1007/3-540-09763-5_3

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-09763-1

  • Online ISBN: 978-3-540-38651-3

  • eBook Packages: Springer Book Archive

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