首页|Multi-sensor monitoring of Ulva prolifera blooms in the Yellow Sea using different methods

Multi-sensor monitoring of Ulva prolifera blooms in the Yellow Sea using different methods

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The massive Ulva (U.)prolifera bloom in the Yellow Sea was first observed and reported in summer of 2008.After that, the green tide event occurred every year and influenced coastal areas of Jiangsu and Shandong provinces of China.Satellite remote sensing plays an important role in monitoring the floating macroalgae.In this paper, U.prolifera patches are detected from quasisynchronous satellite images with different spatial resolution, i.e., Aqua MODIS (Moderate Resolution Imaging Spectroradiometer), HJ-1A/B (China Small Satellite Constellation for Environment and Disaster Monitoring and Forecasting), CCD (Charge-Coupled Device), Landsat 8 OLI (Operational Land Imager), and ENVISAT (Environmental Satellite) ASAR (Advanced Synthetic Aperture Radar) images.Two comparative experiments are performed to explore the U.prolifera monitoring abilities by different data using detection methods such as NDVI (Normalized Difference Vegetation Index) with different thresholds.Results demonstrate that spatial resolution is an important factor affecting the extracted area of the floating macroalgae.Due to the complexity of Case II sea water characteristics in the Yellow Sea, a fixed threshold NDVI method is not suitable for U.prolifera monitoring.A method with adaptive ability in time and space, e.g., the threshold selection method proposed by Otsu (1979), is needed here to obtain accurate information on the floating macroalgae.

Ulva proliferathe Yellow SeaMODISCCDOLISARNDVI

Qing XU、Hongyuan ZHANG、Yongcun CHENG

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Jiangsu Key Laboratory of Coast Ocean Resources Development and Environment Security, Hohai University, Nanjing 210098, China

College of Harbour, Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China

Center for Coastal Physical Oceanography, Old Dominion University, Norfolk, VA 23508, USA

This work was supported by the National Natural Science Foundation of ChinaThis work was supported by the National Natural Science Foundation of Chinaopen research fund of the Laboratory of Data Analysis and Application, State Oceanic Administrationand the program of outstanding innovative talents by Hohai University

4130619441576168LDAA-2013-02

2016

10.1007/s11707-015-0528-1

地球科学前沿
高等教育出版社

地球科学前沿

CSCDSCI
影响因子：0.585
ISSN：2095-0195
年,卷(期)：2016.10(2)
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