| Title |
Estimating Chlorophyll-a Concentration using Spectral Mixture Analysis from RapidEye Imagery in Nak-dong River Basin |
| Authors |
이혁 ( Hyuk Lee ) ; 남기범 ( Gi Beom Nam ) ; 강태구 ( Tae Gu Kang ) ; 윤승준 ( Seung Joon Yoon ) |
| DOI |
https://doi.org/10.15681/KSWE.2014.30.3.329 |
| Keywords |
Chlorophyll-a concentration; Minimum noise fraction; MNF; Pixel purity index; PPI; RapidEye imagery; Spectral mixture analysis; SMA |
| Abstract |
This study aims to estimate chlorophyll-a concentration in rivers using multi-spectral RapidEye imagery and Spectral Mixture Analysis (SMA) and assess the applicability of SMA for multi-temporal imagery analysis. Comparison between images (acquired on Oct. and Nov., 2013) predicted and ground reference chlorophyll-a concentration showed significant performance statistically with determination coefficients of 0.49 and 0.51, respectively. Two band (Red-RE) model for the October and November 2013 RapidEye images showed low performance with coefficient of determinations (R2) of 0.26 and 0.16, respectively. Also Three band (Red-RE-NIR) model showed different performance with R2 of 0.016 and 0.304, respectively. SMA derived Chlorophyll-a concentrations showed relatively higher accuracy than band ratio models based values. SMA was the most appropriate method to calculate Chlorophyll-a concentration using images which were acquired on period of low Chlorophyll-a concentrations. The results of SMA for multi-temporal imagery showed low performance because of the spatio-temporal variation of each end members. This approach provides the potential of providing a cost effective method of monitoring river water quality and management using multi-spectral imagery. In addition, the calculated Chlorophyll-a concentrations using multi-spectral RapidEye imagery can be applied to water quality modeling, enhancing the predicting accuracy. |