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ASME Press Select Proceedings
Intelligent Engineering Systems through Artificial Neural Networks, Volume 20
ISBN:
9780791859599
No. of Pages:
686
Publisher:
ASME Press
Publication date:
2010
eBook Chapter
66 Comparing Supervised and Unsupervised Classifiers for Multispectral Image Analysis
By
Arun Kulkarni
,
Arun Kulkarni
Dept. of Computer Science
The University of Texas at Tyler
Tyler, Texas
, USA
.
Search for other works by this author on:
Kiran Parimi
Kiran Parimi
Dept. of Computer Science
The University of Texas at Tyler
Tyler, Texas
, USA
.
Search for other works by this author on:
Page Count:
8
-
Published:2010
Citation
Kulkarni, A, & Parimi, K. "Comparing Supervised and Unsupervised Classifiers for Multispectral Image Analysis." Intelligent Engineering Systems through Artificial Neural Networks, Volume 20. Ed. Dagli, CH. ASME Press, 2010.
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This paper compares supervised and unsupervised classification of using satellite multi-spectral images for monitoring vegetation growth on lakes and its effect on water quality. The area of interest (AOI) is Lake Tyler which is the main water source for the City of Tyler. It is important to maintain the water quality by monitoring various parameters such as the amount of vegetation growth, surface area covered by water, water pollution, etc. Traditional field based mapping and monitoring present several challenges including inaccessibility and in identifying dynamic changes. Multi-spectral images from Landsat-5 Thematic Mapper (TM), along with the ground truth provided by...
Abstract
Introduction:
Data Acquisition:
Supervised Classification:
Unsupervised Classification:
Results and Discussion
Reference
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