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Applicability evaluation and method selection in detecting cyanobacterial bloom using HY-1C/D CZI data for inland lakes

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

  • Email：kxue@niglas.ac.cn
  • Introduction：薛坤，研究方向为湖泊环境遥感。E-mail： kxue@niglas.ac.cn
XUE Kun1,  
  • role： Corresponding author通信作者
  • Affiliation：

    State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

  • Email：rhma@niglas.ac.cn
  • Introduction：马荣华，研究方向为湖泊环境遥感。E-mail： rhma@niglas.ac.cn
MA Ronghua1*,  
  • Affiliation：

    State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

CAO Zhigang1,  
  • Affiliation：

    State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

HU Minqi1,  
  • Affiliation：

    State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

    University of Chinese Academy of Sciences, Beijing 100049, China

LI Jiaxin12

реферат

Intense cyanobacterial blooms often occur in eutrophic lakes, satellite data with high spatial resolution often has low temporal frequency, and nearly daily revisiting satellite data has coarse spatial resolution, limiting the monitoring of floating blooms in small lakes. The Coastal Zone Imager (CZI) onboard HY-1C/1D satellite provides a new data source to monitor the cyanobacterial bloom of inland lakes with 50 m spatial resolution, revisit time of 3 d. An index, namely the Adjusted Floating Algae Height (AFAH), is developed based on the difference between red band (Rrc(650)), and a baseline between green band (560 nm) and NIR band (near infrared, 825 nm). AFAH was then applied in four eutrophic lakes, for instance, Lake Taihu, Lake Chaohu, Lake Dianchi, and Lake Xingyun, and its advantages and uncertainties in monitoring cyanobacterial blooms were evaluated. The results showed that: (1) In cloudless conditions, AFAH, NDVI (Normalized Difference Vegetation Index), DVI (Difference Vegetation Index), and VB-FAH (Virtual baseline floating macroAlgae Height) have high accuracy larger than 0.93. AFAH has advantages over NDVI, EVI, and VA-FAH, as it is less sensitivity to the solar/viewing geometry, aerosol type and thickness, thin cloud, and sun glint. (2) The maximum gradient method is used to derive the AFAH threshold to extract bloom pixels, total of 180 images with cyanobacterial blooms are used to calculate the mean (0.041) and standard deviation (0.013) of AFAH threshold values. (3) The spatial distribution of cyanobacterial blooms from July, 2019 to July, 2021 in Lake Taihu, Lake Chaohu, Lake Dianchi, and Lake Xingyun is accordance with the previous studies. The areas with bloom frequency larger than 5% are 609.05 km2, 134.43 km2, 20.91 km2, and 14.50 km2 for Lake Taihu, Lake Chaohu, Lake Dianchi, and Lake Xingyun. The Zhushan Bay, Meiliang Bay, and western part of Lake Taihu, the western part of Lake Chaohu, and most part of Lake Dianchi and Lake Xingyun have high frequency of floating blooms. This study indicated that AFAH has good performance in detecting floating blooms using satellite data with only one NIR band, and multi-source satellite data should be combined in the following study in order to improve the temporal frequency of bloom monitoring.

ключеви́че слова́

water color remote sensing;eutrophic lakes;cyanobacterial bloom;HY-1C/D satellite;Coastal Zone Imager (CZI);baseline subtraction method

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