Volume XLII-4/W18
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 609–613, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-609-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 609–613, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-609-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  18 Oct 2019

18 Oct 2019

HARMFUL ALGAL BLOOMS MONITORING USING SENTINEL-2 SATELLITE IMAGES

M. H. Khalili and M. Hasanlou M. H. Khalili and M. Hasanlou
  • Dept. of Geomatic and Geospatial Engineering, University of Tehran, Kargar Street, Tehran, Iran

Keywords: Red tide, Harmful Algal Blooms (HAB), Sentinel-2, Lantau Island, Hongkong, Spectral feature

Abstract. Over the last few decades in coastal areas, the occurrence of Harmful Algal Blooms (HAB) has increased. The phenomenon is harmful to the health of coastal residents as well as marine organisms and can cause damage to the economy of the region. In this article, considering the need of a method for detecting red tide phenomenon using high spatial resolution satellite images, we tried to test the capability of spectral features, which can be generated using Sentinel-2 satellite images, in detecting red tide phenomenon. For this purpose, we generated an algorithm for detecting spectral features, which the red tide phenomenon causes a noticeable change in their value compared with the non-blooming condition. The ability of the selected spectral features in detecting HABs has been evaluated using statistical methods such as type I and II error, overall accuracy, kappa coefficient, and ROC curves. The best case, for the spectral feature, is (R4−R8A)/(R4+R8A), 5% for type I and 6% for type II error were achieved where R4 stands for reflectance in band 4 and R8A is the reflectance in band 8A of a Sentinel-2 satellite image.