基于多时间序列Landsat-8遥感影像的珊瑚礁白化监测

吴柯; 杨帆; 徐莹

doi:10.19509/j.cnki.dzkq.2022.0242

基于多时间序列Landsat-8遥感影像的珊瑚礁白化监测

doi: 10.19509/j.cnki.dzkq.2022.0242

吴柯^1,,
杨帆¹,
徐莹²

1.
中国地质大学(武汉)地球物理与空间信息学院, 武汉 430074
2.
国家卫星海洋应用中心, 北京 100081

基金项目:

国家自然科学基金区域联合基金重点项目 U21A2013

"全球变化与海气相互作用(二期)"专项 GASI-01-DLYG-WIND01

中央高校基本科研业务费专项资金资助项目 2642022009

详细信息

作者简介:
吴柯(1981-)，男，教授，博士生导师，主要从事遥感影像分析。E-Mail：tingke2000@126.com

中图分类号: P627
计量
- 文章访问数: 780
- PDF下载量: 44
- 被引次数: 0
出版历程
- 收稿日期: 2022-09-14
- 网络出版日期: 2022-11-10

Coral reef bleaching monitoring based on multitime Landsat-8 remote sensing image series

Wu Ke^1
,,
Yang Fan¹,
Xu Ying²

1.
Institute of Geophysics and Geomatics, China University of Geoscience(Wuhan), Wuhan 430074, China
2.
National Satellite Ocean Application Service, Beijing 100081, China

摘要

摘要:
近年来, 受人类活动和全球变暖的双重影响, 我国南海区域珊瑚礁生态系统退化, 发生白化现象。利用遥感技术监测和掌握珊瑚礁的白化情况, 对南海生态环境的保护和治理具有重大价值。首先通过多期海表温度数据获取珊瑚礁白化预警的区域, 选定西沙群岛永乐环礁中的羚羊礁作为研究对象; 然后, 提出了一种新型的珊瑚礁白化监测模型, 分别采取水深校正、珊瑚礁分类、反射率调整以及阈值选择等方式对2013-2018年的Landsat-8遥感影像开展了多时间序列的珊瑚礁白化监测研究。最终的结果显示, 该模型能够较为准确地获取珊瑚礁白化区域, 为南海珊瑚礁白化现象的长时间序列监测提供依据。
- Landsat-8 /
- 珊瑚礁白化 /
- 水深校正 /
- 支持向量机 /
- 高斯混合模型 /
- 多时间序列
Abstract:
In recent years, due to the influence of human activities and global warming, the coral reef ecosystem in the South China Sea (SCS) has degraded, and bleaching occurs. Utilizing the remote sensing method to monitor and understand the bleaching status of coral reefs is of great value to the protection and management of the ecological environment in the SCS. This study first obtains coral reef bleaching alert areas (BAAs) through multiperiod sea surface temperature data (SST) and selects the Antelope Reef in the Yongle Atoll of the Paracel Islands as the research area. Then, a new coral reef bleaching monitoring model is proposed, which uses water depth correction, coral reef classification, reflectance adjustment and threshold selection to carry out multitime series coral reef bleaching monitoring research with Landsat-8 remote sensing images from 2013 to 2018. The results show that the model can effectively obtain coral reef bleaching areas and provide a feasible approach for the monitoring of coral reef bleaching in the South China Sea.
- Landsat-8 /
- coral reef bleaching /
- water depth correction /
- support vector machine /
- Gaussian mixture model /
- multitime series

HTML全文

图 1 2013-2018年(7-8月)珊瑚礁白化预警区域

Figure 1. Coral reef bleaching warning areas from 2013 to 2018 (July-August)

下载: 全尺寸图片幻灯片

图 2 研究区示意图

a.研究区位置示意图; b.羚羊礁典型地貌类型

Figure 2. Schematic diagram of the study area

下载: 全尺寸图片幻灯片

图 3 光学数据珊瑚礁白化提取流程

Figure 3. Optical data coral reef bleaching extraction process

下载: 全尺寸图片幻灯片

图 4 羚羊礁原始影像彩色合成图与水深校正后最佳波段组合图对比

Figure 4. Color composite map of the original image of Antelope Reef compared with the best combination of wavebands after water column correction

下载: 全尺寸图片幻灯片

图 5 羚羊礁典型地貌光谱曲线

Figure 5. Spectral curve of typical substrates of Antelope Reef

下载: 全尺寸图片幻灯片

图 6 2013-2018年羚羊礁分类结果图

Figure 6. Classification chart of Antelope Reef from 2013 to 2018

下载: 全尺寸图片幻灯片

图 7 2013-2018年羚羊礁白化提取图

Figure 7. Bleaching extraction map Antelope Reef from 2013 to 2018

下载: 全尺寸图片幻灯片

图 8 2014-2018年羚羊礁白化率变化趋势图

Figure 8. Trend of bleaching rate in Antelope Reef from 2013 to 2018

下载: 全尺寸图片幻灯片

表 1 珊瑚礁白化预警分级

Table 1. Coral reef bleaching warning classification

珊瑚礁白化预警级别	预警标准	影响
无危险(1)	HS≤0	—
白化监视(2)	0＜HS＜1	—
白化警告(3)	HS≥1且0＜DHW＜4	有可能发生白化
白化警报级别1(4)	HS≥1且4≤DHW＜8	很可能发生白化
白化警报级别2(5)	HS≥1且DHW≥8	可能出现死亡

下载: 导出CSV

表 2 2013-2018年羚羊礁区域地物分类结果

Table 2. Substrate classification results of the Antelope Reef area from 2013 to 2018

类型	2013年分类结果		2014年分类结果		2015年分类结果		2016年分类结果		2017年分类结果		2018年分类结果
类型	像元数	百分比/%	像元数	百分比/%	像元数	百分比/%	像元数	百分比/%	像元数	百分比/%	像元数	百分比/%
海洋	44 165	70.66 40	43 690	69.904 0	43 725	69.96	43 711	69.937 6	43 730	69.968 0	43 899	70.238 4
珊瑚礁	8 555	13.688 0	7 981	12.769 6	7 991	12.785 6	9 153	14.644 8	8 788	14.060 8	8 382	13.411 2
沙地	3 197	5.115 2	4 246	6.793 6	4 212	6.739 2	3 501	5.601 6	4 101	6.561 6	3 885	6.216 0
泻湖	6 583	10.532 8	6 583	10.532 8	6 572	10.515 2	6 135	9.816 0	5 881	9.409 6	6 334	10.134 4

下载: 导出CSV

表 3 2013-2018年珊瑚礁白化结果

Table 3. Results of coral reef bleaching from 2013 to 2018

类型	2013-2014年白化检测		2014-2015年白化检测		2015-2016年白化检测		2016-2017年白化检测		2017-2018年白化检测
类型	像元数	百分比/%	像元数	百分比/%	像元数	百分比/%	像元数	百分比/%	像元数	百分比/%
海洋	43 690	69.904 0	43 725	69.960 0	43 711	69.937 6	43 730	69.968 0	43 899	70.238 4
珊瑚礁	7 482	11.971 2	4 988	7.980 8	4 375	7.000 0	7 485	11.976 0	7 359	11.774 4
沙地	4 246	6.793 6	4 212	6.739 2	3 501	5.601 6	4 101	6.561 6	3 885	6.216 0
泻湖	6 583	10.532 8	6 572	10.515 2	6 135	9.816 0	5 881	9.409 6	6 334	10.134 4
白化	499	0.798 4	3 003	4.804 8	4 778	7.644 8	1 303	2.084 8	1 023	1.636 8

下载: 导出CSV

参考文献(16)

[1]	黄荣永, 余克服, 王英辉, 等. 珊瑚礁遥感研究进展[J]. 遥感学报, 2019, 23(6): 1091-1112. https://www.cnki.com.cn/Article/CJFDTOTAL-YGXB201906008.htm Huang R Y, Yu K F, Wang Y H, et al. Progress of the study on coral reef remote sensing[J]. Journal of Remote Sensing, 2019, 23(6): 1091-1112(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-YGXB201906008.htm
[2]	Liu G, Heron S, Eakin C, et al. Reef-scale thermal stress monitoring of coral ecosystems: New 5 km global products from NOAA coral reef watch[J]. Remote Sensing, 2014, 6(11): 11579-11606. doi: 10.3390/rs61111579
[3]	Eakin C M, Lough J M, Heron S F. Climate variability and change: Monitoring data andevidence for increased coral bleaching stress[C]//Lough J, van Oppen M. Coralbleaching: Partterns, processes, causes and consequences. Berlin: Springer, 2009.
[4]	孙旋, 蔡玉林, 索琳琳, 等. 基于SST的珊瑚礁白化监测技术综述[J]. 国土资源遥感, 2018, 30(2): 21-28. https://www.cnki.com.cn/Article/CJFDTOTAL-GTYG201802003.htm Sun X, Cai Y L, Suo L L, et al. Review of coral reef bleaching monitoring technology based on SST[J]. Remote Sensing for Land and Resources, 2018, 30(2): 21-28(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-GTYG201802003.htm
[5]	Andréfouët S, Mumby P, McField M, et al. Revisiting coral reef connectivity[J]. Coral Reefs, 2002, 21(1): 43-48. doi: 10.1007/s00338-001-0199-0
[6]	Yamano H, Tamura M. Detection limits of coral reef bleaching by satellite remote sensing: Simulation and data analysis[J]. Remote Sensing of Environment, 2003, 90(1): 86-103.
[7]	Kabiri K, Pradhan B, Shafri H Z M, et al. A novel approach to estimate diffuse attenuation coefficients for Quick Bird satellite Images: A case study at Kish Island, the Persian Gulf[J]. Journal of the Indian Society of Remote Sensing, 2013, 41(4): 797-806. doi: 10.1007/s12524-013-0293-0
[8]	王雪丽, 蔡玉林, 索琳琳, 等. 基于Landsat-8数据的珊瑚礁白化变化监测[J]. 遥感信息, 2019, 34(6): 119-124. doi: 10.3969/j.issn.1000-3177.2019.06.019 Wang X L, Cai Y L, Suo L L, et al. Monitoring of coral reef bleaching based on Landsat-8 data[J]. Remote Sensing Information, 2019, 34(6): 119-124(in Chinese with English abstract). doi: 10.3969/j.issn.1000-3177.2019.06.019
[9]	潘艳丽, 唐丹玲. 卫星遥感珊瑚礁白化概述[J]. 生态学报, 2009, 29(9): 5076-5080. doi: 10.3321/j.issn:1000-0933.2009.09.057 Pan Y L, Tang D L. General introduction to satellite remote sensing of coral reef bleaching[J]. Journal of Ecology, 2009, 29(9): 5076-5080(in Chinese with English abstract). doi: 10.3321/j.issn:1000-0933.2009.09.057
[10]	Lyzenga D R. Remote sensing of bottom reflectance and water attenuation parameters in shallow water using aircraft and landsat data[J]. International Journal of Remote Sensing, 1981, 2: 71-82. doi: 10.1080/01431168108948342
[11]	索琳琳, 蔡玉林, 孙旋, 等. 基于Landsat-8数据的西沙群岛珊瑚礁信息提取[J]. 中国科技论文, 2019, 14(3): 347-352. doi: 10.3969/j.issn.2095-2783.2019.03.019 Suo L L, Cai Y L, Sun X, et al. Mapping coral reefs at Xisha Islands using Landsat-8[J]. China Sciencepaper, 2019, 14(3): 347-352(in Chinese with English abstract). doi: 10.3969/j.issn.2095-2783.2019.03.019
[12]	吴柯, 牛瑞卿, 王毅, 等. 基于PCA与EM算法的多光谱遥感影像变化检测研究[J]. 计算机科学, 2010, 37(3): 282-284, 296. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJA201003074.htm Wu K, Niu R Q, Wang Y, et al. Change detection of mul ti-spectral remote sensed images based on PCA and EM algorithm[J]. Computer Science, 2010, 37(3): 282-284, 296(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-JSJA201003074.htm
[13]	徐京萍, 李方, 孟庆辉, 等. 基于野外实测数据的珊瑚礁不同底质光谱可分性及珊瑚色素影响分析[J]. 光谱学与光谱分析, 2019, 39(8): 2462-2469. https://www.cnki.com.cn/Article/CJFDTOTAL-GUAN201908028.htm Xu J P, Li F, Meng Q H, et al. The analysis of spectral separability of different coral reef benthos and the influence of pigments on coral spectra based on in-situ data[J]. Spectroscopy and Spectral Analysis, 2019, 39(8): 2462-2469(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-GUAN201908028.htm
[14]	王伟, 许兆林, 李维振, 等. 基于高斯过程回归和高压压汞测定致密砂岩渗透率: 以鄂尔多斯盆地长7段致密砂岩为例[J]. 地质科技通报, 2022, 41(4): 30-37. doi: 10.19509/j.cnki.dzkq.2022.0117 Wang W, Xu Z L, Li W Z, et al. Determination of permeability in tight sandstone reservoirs using Gaussian process regression and high-pressure porosimetry: A case study of the Member-7 of Yanchang Formation in the Jiyuan area of Ordos Basin[J]. Bulletin of Geological Science and Technology, 2022, 41(4): 30-37(in Chinese with English abstract). doi: 10.19509/j.cnki.dzkq.2022.0117
[15]	李元超, 吴钟解, 梁计林, 等. 近15年西沙群岛长棘海星暴发周期及暴发原因分析[J]. 科学通报, 2019, 64(33): 3478-3484. Li Y C, Wu Z X, Liang J L, et al. Analysis on the outbreak period and cause of Acanthaster planci in Xisha Islands in recent 15 years[J]. China Science Bulletin, 2019, 64(33): 3478-3484(in Chinese with English abstract).
[16]	张振冬, 邵魁双, 杨正先, 等. 西沙珊瑚礁生态承载状况评价研究[J]. 海洋环境科学, 2018, 37(4): 487-492. https://www.cnki.com.cn/Article/CJFDTOTAL-HYHJ201804003.htm Zhang Z D, Shao K S, Yang Z X, et al. Evaluation of the Xisha coral reef ecosystem carrying capacity[J]. Marine Environmental Science, 2018, 37(4): 487-492(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-HYHJ201804003.htm