Problems associated with unsupervised classification of high resolution imagery ( pictures included )

Type :

Presentation

Pages :

6 pages

Format :

.doc

Published date :

10/15/2008

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Summary :

 
 

Table of Contents Problems associated with unsupervised classification of high resolution imagery ( pictures included ) Table of Contents

 
  1. Introduction.
  2. Scene information and classification approach.
    1. Difficulties with classifying a QuickBird image.
    2. Division of the scene into two image.
    3. Viewing the resulting image.
  3. Vector mask approach.
    1. Water - the primary feature to be excluded.
    2. Cropping the vector layer.
    3. Creation of a ?water only? image and an ?everything else? image.
  4. Alternative approaches.
    1. Creating buffers around the Wisconsin DNR water body polygons.
    2. Create new water body polygons.
    3. Incorporating a DEM or TIN.
    4. Software designed strictly for the purpose of high resolution image interpretation.
  5. Summary - conclusion.

Abstract

Early satellite systems with multispectral resolutions on the order of 20m (SPOT 1 - 4) or 30m (Landsat 4 - 7) have been able to obtain imagery of sufficient resolution to effectively classify areas with large contiguous areas of information classes, i.e. scenes of dense forest vegetation or cropland. However, accurate classifications of urban areas, where features on the ground change meter by meter, have been impossible to achieve with such lower resolution systems. Satellite systems like Ikonos and QuickBird with resolutions in the panchromatic band at 1 meter and resolutions in the multispectral range of 4 meters produce images of high enough resolution that classification of urban scenes can be done accurately.

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About the author :

pencil image Jamon V.  
Level :Advanced Study : Others School/University : University of Wisconsin-Madison

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