利用遥感技术估算南海北部表层异养细菌丰度*

doi:10.11978/2020125

热带海洋学报 ›› 2021, Vol. 40 ›› Issue (5): 53-62.doi: 10.11978/2020125CSTR: 32234.14.2020125

利用遥感技术估算南海北部表层异养细菌丰度^*

王剑^1,^2,³(), 陈楚群^1,^2,³(), 周伟华⁴, 李祥付¹, 吴颉¹, 叶海彬¹, 唐世林^1,³

1.热带海洋环境国家重点实验室(中国科学院南海海洋研究所), 广东广州 510301
2.中国科学院大学, 北京 100049
3.广东省海洋遥感重点实验室(中国科学院南海海洋研究所), 广东广州 510301
4.热带海洋生物资源与生态重点实验室(中国科学院南海海洋研究所), 广东广州510301

收稿日期:2020-10-30 修回日期:2020-12-21 出版日期:2021-09-10 发布日期:2020-12-24
通讯作者: 陈楚群
作者简介:王剑(1994—), 男, 湖北省安陆市人, 硕士研究生, 主要从事海洋水色遥感研究。email: 18810916182@163.com
基金资助:
国家重点研发计划专项(2018YFC1406604);国家自然科学基金委-广东省联合基金(U1901215);南方海洋科学与工程广东省实验室(广州)人才团队引进重大专项(GML2019ZD0305)(GML2019ZD0305);广东省科技计划项目(2017B0202017002)

Estimating the spatial distribution of heterotrophic bacteria abundance in the Northern South China Sea using remote sensing^*

WANG Jian^1,^2,³(), CHEN Chuqun^1,^2,³(), ZHOU Weihua⁴, LI Xiangfu¹, WU Jie¹, YE Haibin¹, TANG Shilin^1,³

1. State Key Laboratory of Tropical Oceanography (South China Sea Institute of Oceanology, Chinese Academy of Sciences), Guangzhou 510301, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
3. Guangdong Key Laboratory of Ocean Remote Sensing (South China Sea Institute of Oceanology, Chinese Academy of Sciences), Guangzhou 510301, China
4. Key Laboratory of Tropical Marine Bio-resources and Ecology (South China Sea Institute of Oceanology, Chinese Academy of Sciences), Guangzhou 510301, China

Received:2020-10-30 Revised:2020-12-21 Online:2021-09-10 Published:2020-12-24
Contact: CHEN Chuqun
Supported by:
National Key Research and Development Projects(2018YFC1406604);National Natural Science Foundation of China(U1901215);Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong, Laboratory(Guangzhou)(GML2019ZD0305);Science and Technology Planning Project of Guangdong Province, China(2017B0202017002)

摘要/Abstract

摘要：

常规异养细菌监测方法精度高但费时费力且不能连续观测, 而卫星遥感成本低、可以大面积同步、长时间周期观测, 可与常规方法互补。文章利用南海北部10个航次采集的表层异养细菌丰度和卫星遥感反射率, 采用统计回归的方法建立了异养细菌丰度的遥感模型, 其模型决定系数为0.81, 均方根误差为2.44×10⁸个·L^-1, 平均相对误差为21%, 具有较好表现。利用该模型估算南海北部表层异养细菌丰度, 结果显示: 从珠江河口到南海北部开阔海域, 异养细菌丰度逐渐减小。夏季河口地区平均异养细菌丰度最高, 春季最低; 近岸海域靠近珠江河口西侧的平均异养细菌丰度高于东侧; 冬季陆架地区平均异养细菌丰度最高, 夏季最低; 开阔海域的异养细菌丰度变化幅度较小。

关键词: 异养细菌, 水色遥感, 空间分布, 南海北部

Abstract:

Heterotrophic bacteria play an important role in using organic matter, and their abundance indicates eutrophication of water. The conventional methods of monitoring heterotrophic bacteria abundance are highly accurate but time-consuming and laborious; measurements are discrete. Satellite remote sensing technology, characterized by low-cost, large-area synchronization, and long-term repeated observations, is complement with conventional methods. In this study, we use the abundance of heterotrophic bacteria observed during 10 cruises in the northern South China Sea and satellite remote sensing reflectance data to develop an algorithm to estimate heterotrophic bacteria abundance using statistical regression methods. The coefficient of determination of this model is 0.81, the root-mean-square error is 2.44×10⁸ cells·L^-1, and the average relative error is 21%. The established model is used for retrieving the abundance of heterotrophic bacteria on the surface of the northern South China Sea. The abundance of heterotrophic bacteria gradually decrease from the Pearl River Estuary to the open sea. The average abundance of heterotrophic bacteria in the estuary area reaches the highest in summer and the lowest in spring. The average bacterial abundance in the coastal waters near the Pearl River Estuary is higher on the west side than on the east side. Bacterial abundance in the shelf area is the highest in winter and lowest in summer; bacterial abundance in the open sea has little variation from season to season.

Key words: heterotrophic bacteria, ocean color remote sensing, spatial distribution, Northern South China Sea

中图分类号:

P735.13

王剑, 陈楚群, 周伟华, 李祥付, 吴颉, 叶海彬, 唐世林. 利用遥感技术估算南海北部表层异养细菌丰度^*[J]. 热带海洋学报, 2021, 40(5): 53-62.

WANG Jian, CHEN Chuqun, ZHOU Weihua, LI Xiangfu, WU Jie, YE Haibin, TANG Shilin. Estimating the spatial distribution of heterotrophic bacteria abundance in the Northern South China Sea using remote sensing^*[J]. Journal of Tropical Oceanography, 2021, 40(5): 53-62.

图/表 8

图1

表1

图2

图3

表2

较好表现的7种异养细菌丰度与遥感反射率模型"

序号	模型		模型评估
序号	模型		R²	RMSE /(×10⁸个·L^-1)	MAPD /%
1	$\text{HBA}=8.12\times {{\text{e}}^{({{R}_{\text{rs}}}(551)-{{R}_{\text{rs}}}(412))/({{R}_{\text{rs}}}(551)+{{R}_{\text{rs}}}(412))}}-1.58$	0.72		3.02	30
2	$\text{HBA}=11.75\times {{\text{e}}^{({{R}_{\text{rs}}}(551)-{{R}_{\text{rs}}}(443))/({{R}_{\text{rs}}}(551)+{{R}_{\text{rs}}}(443))}}-3.34$	0.71		3.16	32
3	$\text{HBA}=8.95\times {{\text{e}}^{({{R}_{\text{rs}}}(551)-{{R}_{\text{rs}}}(412))/({{R}_{\text{rs}}}(551)+{{R}_{\text{rs}}}(412))}}-154.4\times {{\text{e}}^{({{R}_{\text{rs}}}(551)-{{R}_{\text{rs}}}(412))}}+151.8$	0.76		2.83	25
4	$\text{HBA}=5.81\times {{\text{e}}^{\text{(}{{R}_{\text{rs}}}(551)-{{R}_{\text{rs}}}(412)\text{)/(}{{R}_{\text{rs}}}(551)+{{R}_{\text{rs}}}(412)\text{)}}}\text{+0}\text{.41}\times {{\text{e}}^{{{R}_{\text{rs}}}(667)/{{R}_{\text{rs}}}(443)}}-0.35$	0.81		2.44	21
5	$\begin{align} & \text{HBA}=11.52\times {{\left[ ({{R}_{\text{rs}}}(531)-{{R}_{\text{rs}}}(443))/({{R}_{\text{rs}}}(531)+{{R}_{\text{rs}}}(443)) \right]}^{2}}+ \\& \ \ \ \ \ \ \ \ \ \ 16.38\times ({{R}_{\text{rs}}}(531)-{{R}_{\text{rs}}}(5443))/({{R}_{\text{rs}}}(531)+{{R}_{\text{rs}}}(443))+5.86 \\\end{align}$	0.71		3.35	35
6	$\begin{align}& \text{HBA}=6.11\times {{\left[ ({{R}_{\text{rs}}}(551)-{{R}_{\text{rs}}}(412))/({{R}_{\text{rs}}}(551)+{{R}_{\text{rs}}}(412)) \right]}^{2}}+ \\& \ \ \ \ \ \ \ \ \ \ 4.18\times ({{R}_{\text{rs}}}(551)-{{R}_{\text{rs}}}(412))/({{R}_{\text{rs}}}(551)+{{R}_{\text{rs}}}(412))+5.89 \\\end{align}$	0.75		2.95	28
7	$\begin{align}& \text{HBA}=11.68\times {{\left[ ({{R}_{\text{rs}}}(551)-{{R}_{\text{rs}}}(443))/({{R}_{\text{rs}}}(551)+{{R}_{\text{rs}}}(443)) \right]}^{2}}+ \\& \ \ \ \ \ \ \ \ \ \ 14.58\times ({{R}_{\text{rs}}}(551)-{{R}_{\text{rs}}}(443))/({{R}_{\text{rs}}}(551)+{{R}_{\text{rs}}}(443))+5.92 \\\end{align}$	0.74		2.98	29

表2

图4

表3

图5

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观测时间	站点个数	观测量
2010年8月3—8日, 2011年1月6—10日	航次观测位置一致, 各16组数据	HBA, POC, Chl a
2015年5月10—12日, 2015年8月7—11日, 2016年1月10—14日, 2017年6月10—15日	航次观测位置一致, 各8组数据	HBA, Chl a
2004年9月18日—10月3日	16组数据	HBA, POC, Chl a
2005年9月6—22日	17组数据	HBA, Chl a
2006年9月15—27日	10组数据	HBA, Chl a
2014年8月20日	5组数据	HBA

序号	模型	R²	RMSE/(×10⁸个·L^-1)	MAPD / %
1	lg(HBA)=0.37×lg(POC)+6.07	0.78	2.66	28
2	lg(HBA)=0.28×lg(Chl a)+5.88	0.76	2.43	25

利用遥感技术估算南海北部表层异养细菌丰度^*

Estimating the spatial distribution of heterotrophic bacteria abundance in the Northern South China Sea using remote sensing^*

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利用遥感技术估算南海北部表层异养细菌丰度*

Estimating the spatial distribution of heterotrophic bacteria abundance in the Northern South China Sea using remote sensing*

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利用遥感技术估算南海北部表层异养细菌丰度^*

Estimating the spatial distribution of heterotrophic bacteria abundance in the Northern South China Sea using remote sensing^*