@Article{OgashawaraMisMisCurSte:2013:PeReRe,
author = "Ogashawara, Igor and Mishra, Deepak and Mishra, Sachidananda and
Curtarelli, Marcelo Pedroso and Stech, Jose Luiz",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and Univ
Georgia, Dept Geog, Athens, GA 30602 USA and Dow Agrosci,
Indianapolis, IN 46268 USA and {Instituto Nacional de Pesquisas
Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais
(INPE)}",
title = "A Performance Review of Reflectance Based Algorithms for
Predicting Phycocyanin Concentrations in Inland Waters",
journal = "Remote Sensing",
year = "2013",
volume = "5",
number = "10",
pages = "4774--4798",
month = "Oct.",
keywords = "cyanobacteria, phycocyanin, chlorophyll-a, band ratio, remote
sensing reflectance, hyperspectral sensors, chlorophyll-a
concentration, turbid productive waters, cyanobacterial blooms,
remote, pigments.",
abstract = "We evaluated the accuracy and sensitivity of six previously
published reflectance based algorithms to retrieve Phycocyanin
(PC) concentration in inland waters. We used field radiometric and
pigment data obtained from two study sites located in the United
States and Brazil. All the algorithms targeted the PC absorption
feature observed in the water reflectance spectra between 600 and
625 nm. We evaluated the influence of chlorophyll-a (chl-a)
absorption on the performance of these algorithms in two
contrasting environments with very low and very high cyanobacteria
content. All algorithms performed well in low to moderate PC
concentrations and showed signs of saturation or decreased
sensitivity for high PC concentration with a nonlinear trend. MM09
was found to be the most accurate algorithm overall with a RMSE of
15.675%. We also evaluated the use of these algorithms with the
simulated spectral bands of two hyperspectral space borne sensors
including Hyperion and Compact High-Resolution Imaging
Spectrometer (CHRIS) and a hyperspectral air borne sensor,
Hyperspectral Infrared Imager (HyspIRI). Results showed that the
sensitivity for chl-a of PC retrieval algorithms for Hyperion
simulated data were less noticable than using the spectral bands
of CHRIS; HyspIRI results show that SC00 could be used for this
sensor with low chl-a influence. This review of reflectance based
algorithms can be used to select the optimal approach in studies
involving cyanobacteria monitoring through optical remote sensing
techniques.",
doi = "10.3390/rs5104774",
url = "http://dx.doi.org/10.3390/rs5104774",
issn = "2072-4292",
label = "lattes: 2691497637313274 5 OgashawaraMisMisCurSte:2013:PeReRe",
language = "en",
urlaccessdate = "26 abr. 2024"
}