海洋浮游植物藻华卫星监测系统
本网站基于Sentinel-3A、3B/OLCI数据，使用RDI算法，实现东中国海海域的藻华监测，可提供2016年至今的东中国海藻华高发月份（4月~10月）的藻华信息查询。在上传RDI结果影像前，以结果影像中的有效数据量为标准进行筛选，将有效数据量高于30%的影像上传至服务器，以供系统查询。Sentinel-3A和3B分别于2016年2月16日和2018年4月25日由欧空局发射，其搭载的OLCI传感器具有空间分辨率高，波段信息丰富的特点，Sentinel-3A和3B双星组网，时间分辨率最高可达一日两次。RDI算法是针对藻华水体开发的一种三波段比值模型(Shen and Tang et al., 2019)，能够准确提取藻华水体信息。结合OLCI影像和RDI算法可以实现东中国海藻华信息的高时间、高空间分辨率的精确监测。
This online auto-system monitors algal blooms in the Eastern Seas of China using Sentinel-3/OLCI images and the Red Tide Detection Index (RDI). It provides information on algal blooms in high-occurrence months (April to October) from 2016 to the present. Before uploading RDI result images, the system selects images with an effective pixel higher than 30%. Sentinel-3A and 3B were launched by European Space Agency (ESA) on February 16, 2016 and April 25, 2018, respectively. Their OLCI sensors offer high spatial resolution and spectral resolution, and networked operation of Sentinel-3 A/B can achieve a temporal resolution of up to twice a day. The RDI algorithm is a three-band ratio model developed for algal bloom detection (Shen and Tang et al., 2019), which accurately extracts pixels with potential algal blooms. Combining OLCI images with the RDI algorithm enables precise monitoring of algal bloom information in the East China Sea with high temporal and spatial resolution.
System Description
If you are interested in data in this system or have any question, please contact 51253904023@stu.ecnu.edu.cn.
This system utilizes numerous open-source software and development packages. We would like to express our gratitude to the developers for their contributions！
Including：Tianditu, Bootstrap, jQuery, OpenLayers, Django, SNAP, Anaconda GDAL, Numpy, GeoServer, C2RCC, Python, h5py, netCDF4, sentinelsat, WinRAR
The remote sensing data used in this system is Sentinel-3/OLCI. We would like to express our gratitude to the European Space Agency (ESA) for providing this data.
References for data processing in this system:
Shen Fang, Verhoef Wouter, Zhou Yunxuan, Salama Mhd. Suhyb, Liu Xiaoli(2010). Satellite estimates of wide-range suspended sediment concentrations in Changjiang (Yangtze) estuary using MERIS data. Estuaries and Coasts, Vol.33, No.6, 1420-1429
Brockmann, C., Doerffer, R., Peters, M., Kerstin, S., Embacher, S., & Ruescas, A. (2016). Evolution of the c2rcc neural network for sentinel 2 and 3 for the retrieval of ocean colour products in normal and extreme optically complex waters. In, Proceedings of the Living Planet Symposium. Prague, Czech Republic.
Shen, Fang, Tang, Rugang, Sun, Xuerong, & Liu, Dongyan (2019). Simple methods for satellite identification of algal blooms and species using 10-year time series data from the East China Sea. Remote Sensing of Environment, 235, 111484.
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