A Novel Algorithm for Predicting Phycocyanin Concentrations in Cyanobacteria: A Proximal Hyperspectral Remote Sensing Approach

Remote Sensing

Sachidananda Mishra¹  Deepak R. Mishra¹ 

[1] Geosystems Research Institute and Department of Geosciences, P.O. Box 5448, Mississippi State, MS39762-5448, USA; E-Mail:

关键词: phycocyanin;    cyanobacteria;    hyperspectral remote sensing;    spectral reflectance;   

DOI  :  10.3390/rs1040758

来源: mdpi

【 摘 要 】

The purpose of this research was to evaluate the performance of existing spectral band ratio algorithms and develop a novel algorithm to quantify phycocyanin (PC) in cyanobacteria using hyperspectral remotely-sensed data. We performed four spectroscopic experiments on two different laboratory cultured cyanobacterial species and found that the existing band ratio algorithms are highly sensitive to chlorophylls, making them inaccurate in predicting cyanobacterial abundance in the presence of other chlorophyll-containing organisms. We present a novel spectral band ratio algorithm using 700 and 600 nm that is much less sensitive to the presence of chlorophyll.

【 授权许可】

CC BY   
© 2009 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.