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薛坤，马荣华，曹志刚，胡旻琪，李佳鑫.2023.HY-1C/D卫星CZI数据监测湖泊藻华的适用性评价与方法选择.遥感学报，27（1）： 171-186
Xue K，Ma R H，Cao Z G，Hu M Q and Li J X. 2023. Applicability evaluation and method selection in detecting cyanobacterial bloom using HY-1C/D CZI data for inland lakes. National Remote Sensing Bulletin， 27（1）：171-186
随着湖泊富营养化加剧，蓝藻水华频发暴发，藻华的卫星遥感监测面临着中高空间分辨率卫星过境时间长、中低空间分辨率卫星数据在小型湖泊监测能力不足的问题。海洋水色业务卫星海洋一号C星和D星（HY-1C/D）搭载的海岸带成像仪CZI（Coastal Zone Imager）具有50 m空间分辨率，3 d重访周期，是内陆中小型湖泊藻华遥感监测的重要数据源。本文构建了以CZI数据的绿光（560 nm）—近红外波段（825 nm）连线作为基线，红光波段（650 nm）到该基线的垂直距离作为藻华识别指数AFAH（Adjusted Floating Algae Height），并将其应用在4个典型的富营养化湖泊（太湖、巢湖、滇池、星云湖），评价了其在湖泊藻华遥感监测方面的适用性和不确定性。结果表明：（1）在无云的理想条件下4种藻华识别指数的藻华识别精度高于0.93；在非理性条件下的藻华识别方面，AFAH优于NDVI（Normalized Difference Vegetation Index）、DVI（Difference Vegetation Index）和VB-FAH（Virtual baseline floating macroAlgae Height），对太阳耀斑、云、气溶胶厚度敏感性较低；（2）采用最大梯度法确定了单景影像的AFAH的藻华提取阈值，太湖、巢湖、滇池、星云湖有藻华的数据共180景，AFAH藻华提取阈值的统计均值为0.041，标准差为0.013；（3）2019年7月到2021年7月期间4个湖泊的藻华发生频率空间分布结果与已有研究一致，藻华暴发频率大于5%的面积分别为609.05 km
2
、134.43 km
2
、20.91 km
2
、14.50 km
2
，主要集中在太湖竺山湾、梅梁湾、太湖西部，巢湖西部，滇池和星云湖分散状全湖分布。研究表明，AFAH可以应用于仅包含一个近红外波段的中高空间分辨率卫星，可拓展到多源卫星数据的藻华业务化监测，以提高观测频次。
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 (
R
rc
(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 km
2
134.43 km
2
20.91 km
2
and 14.50 km
2
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.
湖泊水色遥感富营养化湖泊蓝藻水华HY-1C/D海岸带成像仪CZI光谱基线法
water color remote sensingeutrophic lakescyanobacterial bloomHY-1C/D satelliteCoastal Zone Imager (CZI)baseline subtraction method
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