Paper Info
Title
Estimation of Chlorophyll a Concentration Using NIR/Red Bands of MERIS and Classification Procedure in Inland Turbid Water
Abstract
The classification criteria are established to classify the water of Taihu Lake into four classes based on above-water remote sensing reflectance (Rrs), i.e., types A to D. Among the four water types, type A spectra represented the case of waters where algal blooms or aquatic plants appeared, while type B is referred to the water with high suspended matter concentration and low chlorophyll a concentration (Cchla). Both types A and B were not suitable for retrieving Cchla from image data. Hence, three-band, four-band, and two-band ratio algorithms were constructed to retrieve Cchla from water types C and D. The obtained results showed that the relation trends between Cchla and Rrs were different between type C and type D waters. By using Medium Resolution Imaging Spectrometer images, acquired on November 11, 2007 and November 20, 2008, the Cchla of Taihu Lake was mapped by band 9/band 7 models; it could be concluded that the Cchla mainly ranged from 0 to 20 mg · m-3, accounting for 83.70% of the whole lake area in 2007 image, while the area was 86.63% in 2008 image. The estimation accuracies varied from different Cchla ranges. The mean absolute percent errors obtained by band 9/band 7 models were 106.23%, 56.79%, 38.04%, 33.80%, and 58.74% for the ranges 0 mg · m-3 <; Cchla <; = 5 mg · m-3, 5 mg · m-3 <; Cchla <; = 10 mg · m-3, 10 Cchla <; = 20 mg · m-3, 20 mg · m-3 <; Cchla <; = and 30 mg · m-3 <; Cchla, respectively. Correspondingly, the root-mean-square errors were 5.02, 4.45, 5.59, 8.72, and 32.55 mg · m-3, respectively.
Year
DOI
Venue
2012
10.1109/TGRS.2011.2163199
IEEE T. Geoscience and Remote Sensing
Keywords
Field
DocType
relation trends,two-band ratio algorithm,type c water,remote sensing,medium resolution imaging spectrometer (meris),root-mean-square errors,type d water,lakes,low chlorophyll a concentration,estimation accuracies,classification criteria,china,classification procedure,algal blooms,mean absolute percent errors,near infrared (nir)/red model,hydrological techniques,taihu lake,high suspended matter concentration,image classification,nir bands,geophysical image processing,chlorophyll a concentration,image data,four-band ratio algorithm,inland turbid water,type a spectra,three-band ratio algorithm,red bands,water types,aquatic plants,medium resolution imaging spectrometer images,water classification,turbidity,above-water remote sensing reflectance,near infrared,root mean square error,algal bloom,data models,data model,imaging spectrometer,atmospheric modeling,water
Algal bloom,Imaging spectrometer,Aquatic plant,Turbidity,Chlorophyll a,Remote sensing,Turbid water,Atmospheric measurements,Reflectivity,Mathematics
Journal
Volume
Issue
ISSN
50
3
0196-2892
Citations 
PageRank 
References 
13
1.70
2
Authors
7
Name
Order
Citations
PageRank
Yunmei Li1398.09
Qiao Wang29721.94
Chuanqing Wu3245.26
Shaohua Zhao4132.04
Xing Xu519927.30
Yanfei Wang68917.61
Changchun Huang7285.68