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Analyzing the Impact of Simulated Multispectral Images on Water Classification Accuracy by Means of Spectral Characteristics
Abstract
Remote sensing is widely applied in examining the parameters of the state and quality of water. Spectral characteristics of water are strictly connected with the dispersion of electromagnetic radiation by suspended matter and the absorp-tion of radiation by water and chlorophyll a and b.Multispectral sensor ALI has bands within the ranges of electromagnetic radia-tion: blue and infrared, absent in sensors such as Landsat, SPOT, or Aster. The main goal of the article was to examine the influence of the presence of these bands on water classification accuracy carried out for simulated images ALI, Landsat, Spot, and Aster. The simulation of images was based on the hyper-spectral image from a Hyperion sensor. Due to the spectral properties of water, all the operations on the images were carried out for the set of bands in visible and near-infrared (VNIR) spectral range. In the framework of these studies, the impact of removing individual bands or sets of bands on the classification results was tested. Tests were carried out for the area of the water body of the Dobczyce Reservoir. It was observed that the lack of a spectral response in the infrared range of ALI image can reduce the accuracy of a classification by as much as 60%. On the other hand, the lack of blue and red bands in the data-set for the classification decreased the accuracy of water classification by 15% and 10%, respectively.
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Authors (2)
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Ewa Głowienka dr inż.
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- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
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Geomatics and Environmental Engineering
no. 14,
pages 47 - 58,
ISSN: 1898-1135 - Language:
- English
- Publication year:
- 2020
- Bibliographic description:
- Michałowska K., Głowienka E.: Analyzing the Impact of Simulated Multispectral Images on Water Classification Accuracy by Means of Spectral Characteristics// Geomatics and Environmental Engineering -Vol. 14,iss. 1 (2020), s.47-58
- DOI:
- Digital Object Identifier (open in new tab) 10.7494/geom.2020.14.1.47
- Verified by:
- Gdańsk University of Technology
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