Skip to main content

Evaluation of MK-4 multispectral satellite photography in land cover classification of eastern Ontario

Buy Article:

$63.00 plus tax (Refund Policy)

Abstract:

Russian MK-4 multispectral satellite photography has been investigated for potential in land cover classification. Thematic maps were generated using maximum likelihood, neural network and context classifiers. Classifications of the raw spectral data, of spectral transforms, and of combined spectral/textural data were evaluated. Low point-based class accuracies resulted for land cover types exhibiting high spatial variability at the given pixel spacing of 7.5m, while more spatially homogeneous cover types were well classified. Several issues arose which need to be addressed for effective future use of high-resolution satellite sensors in regional land cover mapping. They include the need for further research in techniques for classification and accuracy assessment which are sensitive to the spatial variance of such high resolution imagery, and optimization of class attribute definitions.

Document Type: Research Article

DOI: https://doi.org/10.1080/014311699211354

Publication date: 1999-11-15

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more