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Image calibration to like-values in mapping shallow water quality from multitemporal data

Islam, MA, Gao, J, Ahmad, W, Neil, D and Bell, P (2003). Image calibration to like-values in mapping shallow water quality from multitemporal data. Photogrammetric Engineering and Remote Sensing,69(5):567-575.

Document type: Journal Article
Citation counts: TR Web of Science Citation Count  Cited 7 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 7 times in Scopus Article | Citations
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ISI LOC 000221193300011
Title Image calibration to like-values in mapping shallow water quality from multitemporal data
Author Islam, MA
Gao, J
Ahmad, W
Neil, D
Bell, P
Journal Name Photogrammetric Engineering and Remote Sensing
Publication Date 2003
Volume Number 69
Issue Number 5
ISSN 0099-1112   (check CDU catalogue open catalogue search in new window)
Scopus ID 2-s2.0-0038713382
Start Page 567
End Page 575
Total Pages 9
Place of Publication United States
Publisher American Society for Photogrammetry and Remote Sensing
Field of Research 0499 - Other Earth Sciences
0909 - Geomatic Engineering
HERDC Category C1 - Journal Article (DEST)
Abstract The applicability of image calibration to like-values in mapping water quality parameters from multitemporal images is explored, Six sets of water samples were collected at satellite overpasses over Moreton Bay, Brisbane, Australia. Analysis of these samples reveals that waters in this shallow bay are mostly TSS-dominated, even though they are occasionally dominated by chlorophyll as well. Three of the images were calibrated to a reference image based on invariant targets. Predictive models constructed from the reference image were applied to estimating total suspended sediment (TSS) and Secchi depth from another image at a discrepancy of around 35 percent. Application of the predictive model for TSS concentration to another image acquired at a time of different water types resulted in a discrepancy of 152 percent. Therefore, image calibration to like-values could be used to reliably map certain water quality parameters from multitemporal TM images so long as the water type under study remains unchanged. This method is limited in that the mapped results could be rather inaccurate if the water type under study has changed considerably. Thus, the approach needs to be refined in shallow water from multitemporal satellite imagery.
Keywords suspended sediment concentrations
landsat thematic mapper
 
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