위성영상을 이용한 대청호 남조류의 공간 분포 맵핑
Spatial Distribution Mapping of Cyanobacteria in Daecheong Reservoir Using the Satellite Imagery
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초록
Monitoring of cyanobacteria bloom in reservoir systems is important for water managers responsible of water supply system. Cyanobacteria affect thetaste and smell of water and pose considerable filtration problems at water use places. Harmful cyanobacteria bloom in reservoir have significanteconomic impacts. We develop a new method for estimating the cyanobacteria bloom using Landsat TM and ETM+ data. Developed model wascalibrated and cross-validated with existing in situ measurements from Daecheong Reservoir’s Water Quality Monitoring Program and Algae AlarmSystem. Measurements data of three stations taken from 2004 to 2012 were matched with radiometrically converted reflectance data from the LandsatTM and ETM+ sensor. Stepwise multiple linear regression was used to select wavelengths in the Landsat TM and ETM+ bands 1, 2 and 4 that were mostsignificant for predicting cyanobacteria cell number and bio-volume. Based on statistical analysis, the linear models were that included visible bandratios slightly outperformed single band models. The final monitoring models captured the extents of cyanobacteria blooms throughout the 2004-2012study period. The results serve as an added broad area monitoring tool for water resource managers and present new insight into the initiation andpropagation of cyanobacteria blooms in Daecheong reservoir.
Abstract
Monitoring of cyanobacteria bloom in reservoir systems is important for water managers responsible of water supply system. Cyanobacteria affect thetaste and smell of water and pose considerable filtration problems at water use places. Harmful cyanobacteria bloom in reservoir have significanteconomic impacts. We develop a new method for estimating the cyanobacteria bloom using Landsat TM and ETM+ data. Developed model wascalibrated and cross-validated with existing in situ measurements from Daecheong Reservoir’s Water Quality Monitoring Program and Algae AlarmSystem. Measurements data of three stations taken from 2004 to 2012 were matched with radiometrically converted reflectance data from the LandsatTM and ETM+ sensor. Stepwise multiple linear regression was used to select wavelengths in the Landsat TM and ETM+ bands 1, 2 and 4 that were mostsignificant for predicting cyanobacteria cell number and bio-volume. Based on statistical analysis, the linear models were that included visible bandratios slightly outperformed single band models. The final monitoring models captured the extents of cyanobacteria blooms throughout the 2004-2012study period. The results serve as an added broad area monitoring tool for water resource managers and present new insight into the initiation andpropagation of cyanobacteria blooms in Daecheong reservoir.
참고문헌 (20)
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