Model-based remote sensing algorithms for particulate organic carbon (POC) in the Northeastern Gulf of Mexico SCIE

Cited 7 time in WEB OF SCIENCE
Title
Model-based remote sensing algorithms for particulate organic carbon (POC) in the Northeastern Gulf of Mexico
Author(s)
Son, Young Baek; Gardner, Wilford D.; Mishonov, Alexey V.; Richardson, Mary Jo
KIOST Author(s)
Son, Young Baek(손영백)
Alternative Author(s)
손영백
Publication Year
2009-02
Abstract
Hydrographic data, including particulate organic carbon (POC) from the Northeastern Gulf of Mexico (NEGOM) study, were combined with remotely-sensed SeaWiFS data to estimate POC concentration using principal component analysis (PCA). The spectral radiance was extracted at each NEGOM station, digitized, and averaged. The mean value and spurious trends were removed from each spectrum. De-trended data included six wavelengths at 58 stations. The correlation between the weighting factors of the first six eigenvectors and POC concentration were applied using multiple linear regression. PCA algorithms based on the first three, four, and five modes accounted for 90, 95, and 98% of total variance and yielded significant correlations with POC with R (2) = 0.89, 0.92, and 0.93. These full waveband approaches provided robust estimates of POC in various water types. Three different analyses (root mean square error, mean ratio and standard deviation) showed similar error estimates, and suggest that spectral variations in the modes defined by just the first four characteristic vectors are closely correlated with POC concentration, resulting in only negligible loss of spectral information from additional modes. The use of POC algorithms greatly increases the spatial and temporal resolution for interpreting POC cycling and can be extrapolated throughout and perhaps beyond the area of shipboard sampling.
ISSN
0253-4126
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/4333
DOI
10.1007/s12040-009-0001-1
Bibliographic Citation
JOURNAL OF EARTH SYSTEM SCIENCE, v.118, no.1, pp.1 - 10, 2009
Publisher
INDIAN ACAD SCIENCES
Subject
TEXAS-LOUISIANA SHELF; MISSISSIPPI RIVER; OCEAN COLOR; INFORMATION-CONTENT; CONTINENTAL-SHELF; COASTAL WATERS; SATELLITE DATA; VARIABILITY; ATLANTIC
Keywords
Particulate organic carbon; principal component analysis; remote sensing algorithm
Type
Article
Language
English
Document Type
Article
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