星载GNSS-R检测太湖水华可行性分析

张云; 王雨; 周绍辉; 孟婉婷; 韩彦岭; 杨树瑚

doi:10.13700/j.bh.1001-5965.2022.0298

星载GNSS-R检测太湖水华可行性分析

doi: 10.13700/j.bh.1001-5965.2022.0298

张云^{1, 2},
王雨^{1, 2},
周绍辉³,
孟婉婷⁴,
韩彦岭^{1, 2},
杨树瑚^{1, 2, ,}

1.
上海海洋大学信息学院，上海 201306
2.
上海海洋智能信息与导航遥感工程技术研究中心，上海 201306
3.
上海航天空间技术有限公司，上海 201109
4.
上海航天电子技术研究所，上海 201109

基金项目: 国家自然科学基金(41871325,42176175)；国家重点研发计划(2019YFD0900805)

详细信息

通讯作者:
E-mail：shyang@shou.edu.cn

中图分类号: P715.6
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- 被引次数: 0
出版历程
- 收稿日期: 2022-04-29
- 录用日期: 2022-05-27
- 网络出版日期: 2022-05-31
- 整期出版日期: 2024-03-27

Analysis on feasibility of detecting water blooms in Taihu Lake with spaceborne GNSS-R

ZHANG Yun^{1, 2},
WANG Yu^{1, 2},
ZHOU Shaohui³,
MENG Wanting⁴,
HAN Yanling^{1, 2},
YANG Shuhu^{1, 2
, ,}

1.
College of Information Technology，Shanghai Ocean University，Shanghai 201306，China
2.
Shanghai Research Center of Marine Intelligent Information and Navigation Remote Sensing Engineering Technology，Shanghai 201306，China
3.
Shanghai Aerospace Space Technology Co.，Ltd.，Shanghai 201109，China
4.
Shanghai Academy of Spaceflight Technology，Shanghai 201109，China

Funds: National Natural Science Foundation of China (41871325,42176175); National Key R & D Program of China (2019YFD0900805)

More Information

Corresponding author: E-mail：shyang@shou.edu.cn

摘要

摘要:
星载全球导航卫星系统反射信号(GNSS-R)属于被动遥感技术，具有数据重访周期高、全天时、全天候、信号源丰富等优势。基于此，研究星载GNSS-R检测太湖水华的可行性。星载GNSS-R可以有效检测反射面的粗糙程度，通过使用相干反射表征反射面的粗糙度，研究不同风速区间内相干反射与蓝藻水华的关系。利用2020年4—8月美国气旋全球导航卫星系统(CYGNSS)数据，计算CYGNSS镜面反射点的时延多普勒图(DDM)功率比。以“哨兵-3”卫星水色遥感仪器(OLCI) 影像最大特征峰高度(MPH)算法反演出的太湖叶绿素浓度作为参照，与欧洲中期天气预报中心(ECMWF)的风速产品进行时空间线性匹配，分析发现，在1～2.5 m/s风速区间内，叶绿素浓度达到0.1 mg/L以上时，极易引起镜面反射点发生相干反射，且功率比与叶绿素浓度的相关系数为0.84，具有良好的相关性。实验结果证明了利用星载GNSS-R的功率比及相关特性实现太湖水华检测的可行性。
- 气旋全球导航卫星系统 /
- 全球导航卫星系统反射信号 /
- 功率比 /
- 水色遥感仪器 /
- 最大特征峰高度算法
Abstract:
Spaceborne global navigation satellite system-reflectometry (GNSS-R) is a passive remote sensing technology with the advantages of high data revisit cycle, all-day coverage, all-weather services, and abundant signal sources. Based on this, the feasibility of detecting water blooms in the Taihu Lake by on-board GNSS-R is studied. Spaceborne GNSS-R can effectively detect the roughness of the reflective surface. By using coherent reflection to characterize the roughness of the reflective surface, the relationship between coherent reflection and cyanobacterial blooms in different wind speed ranges is studied. The US cyclone global navigation satellite system (CYGNSS) is used to track the reflected signals of the global positioning system and calculate the power ratio of the delay Doppler map (DDM) of the CYGNSS mirror reflection point using CYGNSS data from April to August 2020. The chlorophyll concentration in Taihu Lake is used as a reference, retrieved from the maximum characteristic peak height (MPH) algorithm of the imagery from the ocean and land colour instrument (OLCI) aboard on “Sentinel-3” satellite. The time-space linear matching is also conducted with wind speed products of the European Centre for Medium-Range Weather Forecasts (ECMWF). Data analysis shows that in the range of wind speed 1−2.5 m/s and with the chlorophyll concentration reaching more than 0.1 mg/L, coherent reflection tends to occur at the specular reflection point, and the correlation coefficient between the power ratio and the chlorophyll concentration is 0.84, which has a good correlation. Experimental results verify the feasibility of detecting the Taihu Lake water bloom using the power ratio and related features.

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图 1 时延多普勒单元与反散射面之间的关系

Figure 1. Relationship between delayed Doppler cells and backscattering surfaces

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图 2 反射面粗糙度与电磁波散射的关系

Figure 2. Relationship between reflection surface roughness and electromagnetic scattering

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图 3 DDM峰值功率值与风速的关系

Figure 3. Relationship between DDM peak power and wind speed

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图 4 CYGNSS筛选范围（紫色区域）

Figure 4. CYGNSS filter range (purple region)

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图 5 2020年6月30日“哨兵-3”卫星反演的太湖叶绿素浓度分布

Figure 5. Chlorophyll concentration distribution in Taihu Lake retrieved by “Sentinel-3” satellite on June 30, 2020

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图 6 2020年6月30日CYGNSS镜面反射点叶绿素浓度与风速匹配图

Figure 6. Matching diagram of chlorophyll concentration and wind speed at CYGNSS specular reflection point on June 30, 2020

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图 7 数据处理流程

Figure 7. Data processing flow

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图 8 2类DDM热噪声去除前后对比及多普勒频移等于0时的切片

Figure 8. Two types of DDM thermal noise before and after removal and slices when Doppler frequency is equal to 0

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图 9 2020年4月太湖区域风速与功率比、相干反射分布图

Figure 9. Wind speed to power ratio and coherent reflection distribution map in Taihu Lake area in April, 2020

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图 10 匹配后镜面反射点功率比、风速与叶绿素浓度相关图

Figure 10. Diagram of correlation of PR, wind speed and chlorophyll concentration after matching

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图 11 功率比、叶绿素浓度拟合结果(风速为1～2.5 m/s)

Figure 11. Fitting results of power ratio and chlorophyll concentration (wind speed is 1−2.5 m/s)

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图 12 功率比、叶绿素浓度拟合结果(风速为2.5～4 m/s)

Figure 12. Fitting results of power ratio and chlorophyll concentration (wind speed is 2.5−4 m/s)

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表 1 “哨兵-3”卫星光学影像与CYGNSS匹配后的数据量(风速≥1 m/s)

Table 1. Data volume of “Sentinel-3” satellite optical image after matching CYGNSS (wind speed ≥ 1 m/s)

日期	匹配前数据量	匹配后数据量
2020年4月20日	8	8
2020年4月28日	9	9
2020年4月29日	18	12
2020年5月3日	23	21
2020年5月13日	15	15
2020年5月19日	21	14
2020年6月30日	31	23
2020年8月2日	11	11
2020年8月25日	7	7

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表 2 不同风速区间的异常数据统计

Table 2. Statistical of abnormal data in different wind speed intervals

风速区间/(m·s⁻¹)	镜面反射点总数	异常数据数量
1～2.5	36	2
2.5～4	59	22
>4	25	0

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