TY - GEN
T1 - Evaluation of the black ocean pixel assumption for MODIS imagery over the Arabian Gulf
AU - Shehhi, Maryam Rashed Al
AU - Gherboudj, Imen
AU - Ghedira, Mohamed Hosni
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/1
Y1 - 2017/12/1
N2 - Red tides have frequently occurred in the Arabian Gulf in the last three decades, which have caused massive fish mortalities, degradation of the water quality, and interruption the operation of the coastal desalination plants. Several studies have been undertaken to monitor this phenomenon from space by developing ocean color models that can quantify red tide by Chlorophyll a (Chl a) parameter. However, these models showed poor performance over this region due to the effect of water and atmospheric turbidity, despite of the use of atmospheric correction model on the data. This could be explained by the failure of this atmospheric correction model, which is based on assuming zero NIR reflectance (black pixel assumption) to correct the satellite imagery. In this paper, we have evaluated the black pixel assumption model and presented an empirical attempt that improve the estimation of water reflectance and Chl a. We found that the uncertainty of this model is mainly caused by the: (i) aerosol loading, which requires further correction (ii) water turbidity, and (iii) water depth.
AB - Red tides have frequently occurred in the Arabian Gulf in the last three decades, which have caused massive fish mortalities, degradation of the water quality, and interruption the operation of the coastal desalination plants. Several studies have been undertaken to monitor this phenomenon from space by developing ocean color models that can quantify red tide by Chlorophyll a (Chl a) parameter. However, these models showed poor performance over this region due to the effect of water and atmospheric turbidity, despite of the use of atmospheric correction model on the data. This could be explained by the failure of this atmospheric correction model, which is based on assuming zero NIR reflectance (black pixel assumption) to correct the satellite imagery. In this paper, we have evaluated the black pixel assumption model and presented an empirical attempt that improve the estimation of water reflectance and Chl a. We found that the uncertainty of this model is mainly caused by the: (i) aerosol loading, which requires further correction (ii) water turbidity, and (iii) water depth.
KW - Arabian Gulf
KW - atmospheric correction
KW - Chlorophyll a
KW - red tide
UR - https://www.scopus.com/pages/publications/85041858932
U2 - 10.1109/IGARSS.2017.8127386
DO - 10.1109/IGARSS.2017.8127386
M3 - Conference contribution
AN - SCOPUS:85041858932
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 2058
EP - 2061
BT - 2017 IEEE International Geoscience and Remote Sensing Symposium
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017
Y2 - 23 July 2017 through 28 July 2017
ER -
