Hyperspectral remote sensing of cyanobacterial pigments as indicators for cell populations and toxins in eutrophic lakes
Hunter, PD; Tyler, AN; Carvalho, L; Codd, GA; Maberly, SC
HERO ID
2623404
Reference Type
Journal Article
Year
2010
Language
English
| HERO ID | 2623404 |
|---|---|
| In Press | No |
| Year | 2010 |
| Title | Hyperspectral remote sensing of cyanobacterial pigments as indicators for cell populations and toxins in eutrophic lakes |
| Authors | Hunter, PD; Tyler, AN; Carvalho, L; Codd, GA; Maberly, SC |
| Journal | Remote Sensing of Environment |
| Volume | 114 |
| Issue | 11 |
| Page Numbers | 2705-2718 |
| Abstract | The growth of mass populations of toxin-producing cyanobacteria is a serious concern for the ecological status of inland waterbodies and for human and animal health. In this study we examined the performance of four semi-analytical algorithms for the retrieval of chlorophyll a (Chl a) and phycocyanin (C-PC) from data acquired by the Compact Airborne Spectrographic Imager-2 (CASI-2) and the Airborne Imaging Spectrometer for Applications (AISA) Eagle sensor. The retrieval accuracies of the semi-analytical models were compared to those returned by optimally calibrated empirical band-ratio algorithms. The best-performing algorithm for the retrieval of Chl a was an empirical band-ratio model based on a quadratic function of the ratio of reflectance at 710 and 670 nm (R(2) = 0.832; RMSE =29.8%). However, this model only provided a marginally better retrieval than the best semi-analytical algorithm. The best-performing model for the retrieval of C-PC was a semi-analytical nested band-ratio model (R(2) = 0.984; RMSE = 3.98 mg m(-3)). The concentrations of C-PC retrieved using the semi-analytical model were correlated with cyanobacterial cell numbers (R(2) = 0.380) and the particulate and total (particulate plus dissolved) pools of microcystins (R(2) = 0.858 and 0.896 respectively). Importantly, both the empirical and semi-analytical algorithms were able to retrieve the concentration of C-PC at cyanobacterial cell concentrations below current warning thresholds for cyanobacteria in waterbodies. This demonstrates the potential of remote sensing to contribute to early-warning detection and monitoring of cyanobacterial blooms for human health protection at regional and global scales. (C) 2010 Elsevier Inc. All rights reserved. |
| Doi | 10.1016/j.rse.2010.06.006 |
| Wosid | WOS:000282242000026 |
| Is Certified Translation | No |
| Dupe Override | No |
| Comments | Scopus URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-77956174742&doi=10.1016%2fj.rse.2010.06.006&partnerID=40&md5=4791ddd9b895f01304129d91e6c5ac7e |
| Is Public | Yes |
| Language Text | English |
| Keyword | Cyanobacteria; Human health; Lakes; Microcystin; Imaging spectrometry; Risk assessment |