中国近海绿潮生物量的卫星光学遥感估算

唐君; 陆应诚; 焦俊男; 刘建强; 胡连波; 丁静; 邢前国; 王福涛; 宋庆君; 陈艳拢; 田礼乔; 王心源; 刘锦超

doi:10.11834/jrs.20232535

大气与海洋 | 浏览量 : 0 下载量: 2291 CSCD: 1

R-PDF
PDF
导出
分享
收藏
专辑

中国近海绿潮生物量的卫星光学遥感估算
High-precision monitoring of green tide biomass in the Yellow Sea of China through optical remote sensing
2023年27卷第11期页码：2484-2498
收稿：2022-10-12，

纸质出版：2023-11-07
DOI： 10.11834/jrs.20232535
稿件说明：

移动端阅览

唐君，陆应诚，焦俊男，刘建强，胡连波，丁静，邢前国，王福涛，宋庆君，陈艳拢，田礼乔，王心源，刘锦超.2023.中国近海绿潮生物量的卫星光学遥感估算.遥感学报，27（11）： 2484-2498 DOI： 10.11834/jrs.20232535.

Tang J，Lu Y C，Jiao J N，Liu J Q，Hu L B，Ding J，Xing Q G，Wang F T，Song Q J，Chen Y L，Tian L Q，Wang X Y and Liu J C. 2023. High-precision monitoring of green tide biomass in the Yellow Sea of China through optical remote sensing. National Remote Sensing Bulletin， 27（11）：2484-2498 DOI： 10.11834/jrs.20232535.

摘要

生物量是精准量化海洋大型漂浮藻类的关键参数，是反映海洋生态环境变化的有效指标。光学遥感卫星能为绿潮的精细化监测与评估提供数据支持，实现绿潮的精准识别与量化估算。针对中国海洋一号C/D卫星（HY-1C/D）海岸带成像仪CZI（Coastal Zone Imager）、美国中分辨率成像光谱仪MODIS（Moderate-resolution Imaging Spectroradiometer）、欧洲空间局哨兵2号卫星多光谱成像仪MSI （Multi Spectral Instrument）等光学遥感数据特点，基于绿潮生物量变化模拟与观测验证数据，本研究提出了适用于不同光学卫星数据的绿潮生物量估算模型与计算方法，开展了中国近海绿潮生物量光学遥感估算与交叉验证。结果表明：相较于绿潮像元面积和覆盖面积，绿潮生物量估算结果的不确定性最小，该参数能有效减少面积参数所内含的尺度效应差异，能更准确地用于海洋绿潮的量化与评估。此外，基于CZI和MODIS数据开展2021年中国近海绿潮生物量协同监测应用，有效提高了绿潮生物量监测的精度，详细量化了2021年中国近海绿潮生物量的年内变化，展现了绿潮生物量的精细空间分布格局与变化趋势。多源光学遥感数据开展绿潮生物量遥感估算，对中国近海漂浮藻类的精准、定量、动态监测，具有重要的方法与数据参考意义。

Abstract

Large-scale green tides occurring in the Yellow Sea (YS) of China have become a critical eco-environmental problem

causing serious damage to marine and the coastal ecological environment

aquaculture

and tourism since 2007. Green tide biomass is a key parameter for accurate quantification of floating macroalgae

serving as an effective indicator for monitoring changes in the marine ecological environment. Satellite remote sensing technology plays a pivotal role in supporting the monitoring and assessment of green tide. Spaceborne optical sensors

in particular

offer a wealth of data that is indispensable for the fine-scale quantitative monitoring and assessment of green tide. In this study

we have established robust statistical relationships between Biomass Per Area (BPA) and various optical remote sensing indices by modeling the laboratory measurements of

U. prolifera

biomass (wet weight) per unit area and the corresponding spectral reflectance data. The computational methods of BPA have been carefully designed and validated for different optical data

including Moderate Resolution Imaging Spectroradiometer (MODIS)

the Multispectral Instrument (MSI) onboard Sentinel-2 satellites

and the Coastal Zone Imager (CZI) onboard China’s HaiYang-1C/D (HY-1C/D) satellites. These results indicate that BPA can serve as a highly effective parameter in quantifying green tide using remote sensing data. Unlike common parameters such as pixel area or coverage area

BPA can mitigate the scale effects of spatial resolution differences from various observations

minimizing the uncertainty especially when integrating multiple remote sensing data. With the coordinated utilization of CZI and MODIS data in 2021 and the developed BPA models

the detailed intra-annual variations in green tide biomass in the YS of China were quantified. This analysis has revealed the intricate spatial distribution patterns and trends inherent in green tide biomass fluctuations. The utilization of multiple optical remote sensing data sources for the estimation of green tide biomass carries important methodological significance and serves as an accurate data reference for the precise

quantitative

and dynamic monitoring of green tide in the YS of China.

关键词

Keywords

references

Garcia R A , Fearns P , Keesing J K and Liu D Y . 2013 . Quantification of floating macroalgae blooms using the scaled algae index . Journal of Geophysical Research: Oceans , 118 ( 1 ): 26 - 42 [ DOI: 10.1029/2012JC008292 http://dx.doi.org/10.1029/2012JC008292 ]

Hu C M . 2009 . A novel ocean color index to detect floating algae in the global oceans . Remote Sensing of Environment , 113 ( 10 ): 2118 - 2129 [ DOI: 10.1016/j.rse.2009.05.012 http://dx.doi.org/10.1016/j.rse.2009.05.012 ]

Hu C M and He M X . 2008 . Origin and offshore extent of floating algae in Olympic sailing area . Eos, Transactions American Geophysical Union , 89 ( 33 ): 302 - 303 [ DOI: 10.1029/2008eo330002 http://dx.doi.org/10.1029/2008eo330002 ]

Hu C M , Li D Q , Chen C S , Ge J Z , Muller-Karger F E , Liu J P , Yu F and He M X . 2010 . On the recurrent Ulva prolifera blooms in the Yellow Sea and East China Sea . Journal of Geophysical Research: Oceans , 115 ( C5 ): C 05017 [ DOI: 10.1029/2009JC005561 http://dx.doi.org/10.1029/2009JC005561 ]

Hu L B , Hu C M and He M X . 2017 . Remote estimation of biomass of Ulva prolifera macroalgae in the Yellow Sea . Remote Sensing of Environment , 192 : 217 - 227 [ DOI: 10.1016/j.rse.2017.01.037 http://dx.doi.org/10.1016/j.rse.2017.01.037 ]

Hu L B , Zeng K , Hu C M and He M X . 2019 . On the remote estimation of Ulva prolifera areal coverage and biomass . Remote Sensing of Environment , 223 : 194 - 207 [ DOI: 10.1016/j.rse.2019.01.014 http://dx.doi.org/10.1016/j.rse.2019.01.014 ]

Keesing J K , Liu D Y , Fearns P and Garcia R . 2011 . Inter-and intra-annual patterns of Ulva prolifera green tides in the Yellow Sea during 2007—2009, their origin and relationship to the expansion of coastal seaweed aquaculture in China . Marine Pollution Bulletin , 62 ( 6 ): 1169 - 1182 [ DOI: 10.1016/j.marpolbul.2011.03.040 http://dx.doi.org/10.1016/j.marpolbul.2011.03.040 ]

Li L , Xing Q G , Li X R , Yu D F , Zhang J and Zou J Q . 2018 . Assessment of the impacts from the world's largest floating macroalgae blooms on the water clarity at the west Yellow Sea using MODIS data (2002—2016) . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 11 ( 5 ): 1397 - 1402 [ DOI: 10.1109/JSTARS.2018.2806626 http://dx.doi.org/10.1109/JSTARS.2018.2806626 ]

Liu D Y , Keesing J K , Dong Z J , Zhen Y , Di B P , Shi Y J , Fearns P and Shi P . 2010 . Recurrence of the world’s largest green-tide in 2009 in Yellow Sea, China: Porphyra yezoensis aquaculture rafts confirmed as nursery for macroalgal blooms . Marine Pollution Bulletin , 60 ( 9 ): 1423 - 1432 [ DOI: 10.1016/j.marpolbul.2010.05.015 http://dx.doi.org/10.1016/j.marpolbul.2010.05.015 ]

Liu D Y , Keesing J K , Xing Q G and Shi P . 2009 . World’s largest macroalgal bloom caused by expansion of seaweed aquaculture in China . Marine Pollution Bulletin , 58 ( 6 ): 888 - 895 [ DOI: 10.1016/j.marpolbul.2009.01.013 http://dx.doi.org/10.1016/j.marpolbul.2009.01.013 ]

Liu J C , Liu J Q , Ding J and Lu Y C . 2022 . A refined imagery algorithm to extract green tide in the Yellow Sea from HY-1C satellite CZI measurements . Haiyang Xuebao , 44 ( 5 ): 1 - 11

刘锦超 , 刘建强 , 丁静 , 陆应诚 . 2022 . HY-1C卫星CZI载荷的黄海绿潮提取研究 . 海洋学报 , 44 ( 5 ): 1 - 11 [ DOI: 10.12284/hyxb2022097 http://dx.doi.org/10.12284/hyxb2022097 ]

Liu J Q , Ye X M , Song Q J , Ding J and Zou B . 2023 . Products of HY-1C/D ocean color satellites and their typical applications . National Remote Sensing Bulletin , 27 ( 1 ): 1 - 13

刘建强 , 叶小敏 , 宋庆君 , 丁静 , 邹斌 . 2023 . HY-1C/D海洋水色卫星产品体系及其典型应用 . 遥感学报 , 27 ( 1 ): 1 - 13 [ DOI: 10.11834/jrs.20235002 http://dx.doi.org/10.11834/jrs.20235002 ]

Liu X Q , Wang Z L and Zhang X L . 2016 . A review of the green tides in the Yellow Sea, China . Marine Environmental Research , 119 : 189 - 196 [ DOI: 10.1016/j.marenvres.2016.06.004 http://dx.doi.org/10.1016/j.marenvres.2016.06.004 ]

Lu T , Lu Y C , Hu L B , Jiao J N , Zhang M W and Liu Y X . 2019 . Uncertainty in the optical remote estimation of the biomass of Ulva prolifera macroalgae using MODIS imagery in the Yellow Sea . Optics Express , 27 ( 13 ): 18620 - 18627 [ DOI: 10.1364/OE.27.018620 http://dx.doi.org/10.1364/OE.27.018620 ]

Qi L , Hu C M , Xing Q G and Shang S L . 2016 . Long-term trend of Ulva prolifera blooms in the western Yellow Sea . Harmful Algae , 58 : 35 - 44 [ DOI: 10.1016/j.hal.2016.07.004 http://dx.doi.org/10.1016/j.hal.2016.07.004 ]

Shi W and Wang M H . 2009 . Green macroalgae blooms in the Yellow Sea during the spring and summer of 2008 . Journal of Geophysical Research: Oceans , 114 ( C12 ): C 12010 [ DOI: 10.1029/2009jc005513 http://dx.doi.org/10.1029/2009jc005513 ]

Wang M Q and Hu C M . 2016 . Mapping and quantifying Sargassum distribution and coverage in the Central West Atlantic using MODIS observations . Remote Sensing of Environment , 183 : 350 - 367 [ DOI: 10.1016/j.rse.2016.04.019 http://dx.doi.org/10.1016/j.rse.2016.04.019 ]

Wang X H , Liu H L , Xing Q G , Liu J Q , Ding J and Jin S . 2023 . Application of HY-1 CZI satellite images in monitoring of green tide in Yellow Sea . National Remote Sensing Bulletin , 27 ( 1 ): 146 - 156

王鑫华 , 刘海龙 , 邢前国 , 刘建强 , 丁静 , 金松 . 2023 . HY-1卫星CZI影像在黄海绿潮监测的应用 . 遥感学报 , 27 ( 1 ): 146 - 156 [ DOI: 10.11834/jrs.20235003 http://dx.doi.org/10.11834/jrs.20235003 ]

Wang X H , Li L , Bao X and Zhao L D . 2009 . Economic cost of an algae bloom cleanup in China’s 2008 Olympic sailing venue . Eos, Transactions American Geophysical Union , 90 ( 28 ): 238 - 239 [ DOI: 10.1029/2009eo280002 http://dx.doi.org/10.1029/2009eo280002 ]

Xing Q G and Hu C M . 2016 . Mapping macroalgal blooms in the Yellow Sea and East China Sea using HJ-1 and Landsat data: application of a virtual baseline reflectance height technique . Remote sensing of Environment , 178 : 113 - 126 [ DOI: 10.1016/j.rse.2016.02.065 http://dx.doi.org/10.1016/j.rse.2016.02.065 ]

Xing Q G , Hu C M , Tang D L , Tian L Q , Tang S L , Wang X H , Lou M J and Gao X L . 2015 . World’s largest macroalgal blooms altered phytoplankton biomass in summer in the Yellow Sea: satellite observations . Remote Sensing , 7 ( 9 ): 12297 - 12313 [ DOI: 10.3390/rs70912297 http://dx.doi.org/10.3390/rs70912297 ]

Xu Q , Zhang H Y , Ju L and Chen M X . 2014 . Interannual variability of Ulva prolifera blooms in the Yellow Sea . International Journal of Remote Sensing , 35 ( 11/12 ): 4099 - 4113 [ DOI: 10.1080/01431161.2014.916052 http://dx.doi.org/10.1080/01431161.2014.916052 ]

文章被引用时，请邮件提醒。

提交

海洋白帽的高空间分辨率光学遥感估算分析

基于时序Sentinel-2和Landsat 8影像的入侵植物互花米草治理方式识别与动态监测

多源光学遥感数据对近海溢油的监测效能分析