Information content characterization in remote sensing imagery based on classification accuracy

Ram Mohan Narayanan, M. K. Desetty, S. E. Reichenbach

Research output: Contribution to conferencePaper

Abstract

The information content in remote sensing imagery depends upon various factors. Various textural measures are used to characterize the image information content. Our approach to quantifying image information content is based upon classification accuracy. We have developed a negative-exponential model that relates information content to spatial resolution, which is seen to be applicable to real images acquired by Landsat TM optical as well as SIR-C SAR sensors. An interesting conclusion that emerges is that although the TM image has higher information content that the SIR-C image at lower pixel sizes, the opposite is true at higher pixel sizes. The transition occurs at a pixel size of about 720 meters. This tells us that for applications that require higher resolutions (or smaller pixel sizes), the TM sensor is more useful for terrain classification. On the contrary, for applications involving lower resolutions (or larger pixel sizes), the SIR-C sensor has an advantage. Thus, the model is useful in comparing different sensor types for different applications.

Original languageEnglish (US)
Pages131-133
Number of pages3
StatePublished - Jan 1 1999
EventProceedings of the 1999 IEEE International Geoscience and Remote Sensing Symposium (IGARSS'99) 'Remote Sensing of the Systems Earth - A Challenge for the 21st Century' - Hamburg, Ger
Duration: Jun 28 1999Jul 2 1999

Other

OtherProceedings of the 1999 IEEE International Geoscience and Remote Sensing Symposium (IGARSS'99) 'Remote Sensing of the Systems Earth - A Challenge for the 21st Century'
CityHamburg, Ger
Period6/28/997/2/99

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All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

Cite this

Narayanan, R. M., Desetty, M. K., & Reichenbach, S. E. (1999). Information content characterization in remote sensing imagery based on classification accuracy. 131-133. Paper presented at Proceedings of the 1999 IEEE International Geoscience and Remote Sensing Symposium (IGARSS'99) 'Remote Sensing of the Systems Earth - A Challenge for the 21st Century', Hamburg, Ger, .