Share Email Print

Proceedings Paper

Developing a two-step method for detecting red tide in East China Sea using MERIS data
Author(s): Xiaohui Xu
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Red tide is an ecological anomaly that phytoplankton in seawater suddenly proliferation or aggregation under certain environmental conditions and within a period of time, resulting in seawater discoloration. Red tide not only endangers marine fisheries and aquaculture, deteriorates the marine environment, affects coastal tourist industry, but also causes human health problems. East China Sea (ECS) is a high incidence region of red tide disasters. Remote sensing is an effective means of monitoring red tides. In this paper, the high-incidence area of the red tide in the East China Sea is selected as the study area, MERIS L2 data is used as the data source to analyze and compare the normalized water radiation (nlw) spectral difference between the red tide water body and the non-red tide water body in the red tide event. Based on the spectral difference, this paper develops nlw560/nlw490>1.25 and nlw681-nlw665>0 algorithm to extract the red tide information of ECS. Applying the algorithm to ECS, the results show that the developed model can effectively determine the location of the red tide and correspond well with the results of the official bulletin. This indicates that the algorithm can effectively extract red tide information.

Paper Details

Date Published: 14 October 2019
PDF: 7 pages
Proc. SPIE 11150, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2019, 111501E (14 October 2019); doi: 10.1117/12.2532984
Show Author Affiliations
Xiaohui Xu, Third Institute of Oceanography (China)

Published in SPIE Proceedings Vol. 11150:
Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2019
Charles R. Bostater Jr.; Xavier Neyt; Françoise Viallefont-Robinet, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?