Proceedings of the 2015 International Conference on Environmental Engineering and Remote Sensing

Modeling for Estimation of Algal Bloom in Daecheong Lake Using the Satellite Imagery

Authors
Shincheol Back, Jinki Park, Jonghwa Park
Corresponding Author
Shincheol Back
Available Online September 2015.
DOI
https://doi.org/10.2991/eers-15.2015.25How to use a DOI?
Keywords
algal bloom; phycocyanin; aquatic resourcese; chlorophyll a;Landsat TM and ETM+
Abstract

Blooms of harmful algae and phycocyanin represent a significant and expanding threat to human health and aquatic resources throughout the South Korea. Algal blooms can be seen in a variety of phenomenon in nature, ranging from massive accumulations of cells that discolor the water, to dilute, inconspicuous, but highly harmful populations. Estimating the distribution and growth of algae in lake systems are particularly important for the personnel of water managements and water supply system. Algae affect the taste and smell which pose considerable filtration problems for the communities using the water system such as Daecheong Lake. Many harmful algal blooms (HABs) have significant economic impacts especially in pisciculture. We developed empirical remote sensing models to estimate Chlorophyll a (Chl.-a) concentrations and cyanobacteria synoptically, over the Daecheong lake using available Landsat TM and ETM+ data. In contrast to previous in situ studies of the cyanobacterial specific pigment such as phycocyanin, we developed remote sensing models capable of directly detecting cyanobacterial biovolume. This distinction is important because Landsat TM and ETM+ data lacks the spectral band information required for optimal phycocyanin detection. Developed model was calibrated and cross-validated with existing in situ measurements from Daecheong lake’s Long-Term Water Quality Monitoring Program and Algae Alam System (AAS). Three lake station measurements taken between 2004 and 2012 were matched with radiometrically converted reflectance data from three spectral bands on the Landsat TM and ETM+ sensor. Step-wise multi-linear regression indicated data from Landsat TM and ETM+ bands 1, 2 and 4 were most significant for predicting Chl.-a and cyanobacteria biovolume. Based on statistical analysis, the linear models are that included visible band ratios slightly outperformed single band models. The final models captured the extents of cyanobacterial blooms throughout the 2004-2012 study period. The results serve as an added broad area monitoring tool for water resource managers and present new insight into the initiation and propagation of cyanobacterial blooms in Daecheong lake

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 International Conference on Environmental Engineering and Remote Sensing
Series
Advances in Computer Science Research
Publication Date
September 2015
ISBN
978-94-6252-106-3
ISSN
2352-538X
DOI
https://doi.org/10.2991/eers-15.2015.25How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Shincheol Back
AU  - Jinki Park
AU  - Jonghwa Park
PY  - 2015/09
DA  - 2015/09
TI  - Modeling for Estimation of Algal Bloom in Daecheong Lake Using the Satellite Imagery
BT  - Proceedings of the 2015 International Conference on Environmental Engineering and Remote Sensing
PB  - Atlantis Press
SP  - 101
EP  - 105
SN  - 2352-538X
UR  - https://doi.org/10.2991/eers-15.2015.25
DO  - https://doi.org/10.2991/eers-15.2015.25
ID  - Back2015/09
ER  -