TY - JOUR

T1 - Estimation of Colored Dissolved Organic Matter from Landsat-8 Imagery for Complex Inland Water

T2 - Case Study of Lake Huron

AU - Chen, Jiang

AU - Zhu, Wei Ning

AU - Tian, Yong Q.

AU - Yu, Qian

N1 - Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grant 41471346, in part by Central Michigan University, and in part by the National Science Foundation under grant 1025547 and Grant 1230261.
Publisher Copyright:
© 1980-2012 IEEE.

PY - 2017/4

Y1 - 2017/4

N2 - Spectral reflectance data, including irradiance reflectance (R-t) and remote sensing reflectance (R-mathrm rs , sr -1) , and colored dissolved organic matter (CDOM) absorption coefficients a-mathrm CDOM (440), were collected in the Saginaw River and Kawkawlin River plume regions of Lake Huron. We developed an empirical band ratio algorithm to derive a-mathrm CDOM (440) that could be directly applicable to Landsat-8 imagery. A model ranking method is used to determine the best band ratios as well as their empirical functions. One problem of previous CDOM estimations from Landsat imagery is that they usually use R-t or R-t/\pi rather than the real R-mathrm rs as the input data, but as a result of our study, algorithms derived using R-mathrm rs performed much better than using R-t. The green/red band ratio gave the best accuracies by fitting with power and exponential models (power model: R2 = 0.819 and RMSE =0.889\textm-1 and exponential model: R2 = 0.829 and RMSE =0.863\textm-1). The power and exponential models were further validated using an independent data group, achieving excellent results with the RMSE of 0.642 and 0.504 \textm-1 , respectively. The application of the exponential model a-mathrm CDOM (440) = 40.75e-2.463x, x = R-mathrm rs (B3)/ R-mathrm rs (B4) on two Landsat-8 images demonstrated that estimating CDOM from to Landsat-8 imagery has potential applications for monitoring water quality in long term and large scale.

AB - Spectral reflectance data, including irradiance reflectance (R-t) and remote sensing reflectance (R-mathrm rs , sr -1) , and colored dissolved organic matter (CDOM) absorption coefficients a-mathrm CDOM (440), were collected in the Saginaw River and Kawkawlin River plume regions of Lake Huron. We developed an empirical band ratio algorithm to derive a-mathrm CDOM (440) that could be directly applicable to Landsat-8 imagery. A model ranking method is used to determine the best band ratios as well as their empirical functions. One problem of previous CDOM estimations from Landsat imagery is that they usually use R-t or R-t/\pi rather than the real R-mathrm rs as the input data, but as a result of our study, algorithms derived using R-mathrm rs performed much better than using R-t. The green/red band ratio gave the best accuracies by fitting with power and exponential models (power model: R2 = 0.819 and RMSE =0.889\textm-1 and exponential model: R2 = 0.829 and RMSE =0.863\textm-1). The power and exponential models were further validated using an independent data group, achieving excellent results with the RMSE of 0.642 and 0.504 \textm-1 , respectively. The application of the exponential model a-mathrm CDOM (440) = 40.75e-2.463x, x = R-mathrm rs (B3)/ R-mathrm rs (B4) on two Landsat-8 images demonstrated that estimating CDOM from to Landsat-8 imagery has potential applications for monitoring water quality in long term and large scale.

KW - Band ratio algorithm

KW - Lake Huron

KW - Landsat-8 Operational Land Imager (OLI)

KW - colored dissolved organic matter (CDOM)

KW - irradiance reflectance

KW - remote sensing reflectance

UR - http://www.scopus.com/inward/record.url?scp=85009895161&partnerID=8YFLogxK

U2 - 10.1109/TGRS.2016.2638828

DO - 10.1109/TGRS.2016.2638828

M3 - Article

AN - SCOPUS:85009895161

SN - 0196-2892

VL - 55

SP - 2201

EP - 2212

JO - IEEE Transactions on Geoscience and Remote Sensing

JF - IEEE Transactions on Geoscience and Remote Sensing

IS - 4

M1 - 7815300

ER -