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 language | English (US) |
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Pages | 131-133 |
Number of pages | 3 |
State | Published - Jan 1 1999 |
Event | 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 Duration: Jun 28 1999 → Jul 2 1999 |
Other
Other | 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' |
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City | Hamburg, Ger |
Period | 6/28/99 → 7/2/99 |
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- General Earth and Planetary Sciences