Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326443
Title: The geometric correction and registration of airborne line-scanned imagery for temporal thermal studies
Author: Gregory, Simon
ISNI:       0000 0001 3518 5058
Awarding Body: Aston University
Current Institution: Aston University
Date of Award: 2001
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Abstract:
This thesis begins by providing a review of techniques for interpreting the thermal response at the earth's surface acquired using remote sensing technology. Historic limitations in the precision with which imagery acquired from airborne platforms can be geometrically corrected and co-registered has meant that relatively little work has been carried out examining the diurnal variation of surface temperature over wide regions. Although emerging remote sensing systems provide the potential to register temporal image data within satisfactory levels of accuracy, this technology is still not widely available and does not address the issue of historic data sets which cannot be rectified using conventional parametric approaches. In overcoming these problems, the second part of this thesis describes the development of an alternative approach for rectifying airborne line-scanned imagery. The underlying assumption that scan lines within the imagery are straight greatly reduces the number of ground control points required to describe the image geometry. Furthermore, the use of pattern matching procedures to identify geometric disparities between raw line-scanned imagery and corresponding aerial photography enables the correction procedure to be almost fully automated. By reconstructing the raw image data on a truly line-by-line basis, it is possible to register the airborne line-scanned imagery to the aerial photography with an average accuracy of better than one pixel. Providing corresponding aerial photography is available, this approach can be applied in the absence of platform altitude information allowing multi-temporal data sets to be corrected and registered.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.326443  DOI: Not available
Keywords: Civil Engineering ; Transport Logistics Pattern recognition systems Pattern perception Image processing Geomagnetism Cartography Geodesy
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