YIC-IR
苏北浅滩海藻养殖区精细化遥感与筏架回收动态监测
Alternative TitleSeaweed cultivation region remote sensing and analysis on the dynamics in seaweed-facility recycling in northern Jiangsu shoal
魏振宁
Subtype硕士
Thesis Advisor邢前国
2019-05-11
Degree Grantor中国科学院大学
Place of Conferral北京
Degree Name工程硕士
Degree Discipline环境工程
Keyword苏北浅滩海藻养殖区,精细化提取,养殖活动特征,黄海绿潮,遥感
Abstract

2007 年起黄海每年暴发大规模绿潮,从遥感监测、实地调研以及生物学等多个方面研究发现,黄海绿潮起源为苏北浅滩海藻养殖区。本文以 GF-1 高分辨率遥感卫星影像为主,结合 Sentinel-2AHJ-1A/BLandsat 系列卫星光学影像,以及 Sentinel-1A 微波影像,对苏北浅滩养殖区进行精细化提取(基于高分辨率卫星影像、多元数据、分区域提取和统计),基于提取结果分析苏北浅滩养殖活动特征。

论文主要研究内容和成果如下:

1)选取海藻生长期的微波影像,发现通过阈值法可以较好地将海藻养殖区从微波影像上提取出来,从养殖区空间分布上看,基于微波影像提取出的养殖区与基于光学影像的提取结果一致。但是在养殖设备回收期间,微波和光学提取结果不同,基于此对在此期间的养殖区的光谱差异进行了分析。

2)基于不同分辨率光学遥感影像,提取的养殖区面积有差异,研究建立了不同分辨率影像提取养殖区面积结果的换算关系。

3)通过分析 2012-2018 年苏北浅滩养殖区总体变化情况发现苏北浅滩海藻养殖区面积在该时间段内较为稳定,没有明显的扩张。

4)分析苏北浅滩2012-2018年每年4月底至6月初的养殖区的提取结果,发现在养殖设备回收期间,每年养殖区面积变化不同,即养殖设备回收进程存在差异。2015 年和 2016 年的养殖设备回收较早,2017 年和 2018 年养殖设备回收较晚。

5)结合 2012-2018 年绿潮数据发现,较晚回收养殖设备的 2017 年和 2018 产生的早期绿潮量明显小于养殖设施回收较早的 2014 年、2015 年以及 2016 年。2017 年和 2018 年的绿潮暴发规模(绿潮最大日覆盖面积)同样远小于 2015 年和 2016 年。结果显示,调节苏北浅滩养殖区养殖设备的回收可控制浒苔暴发规模。

本研究通过对苏北浅滩养殖区的精细化提取和对养殖活动特征的分析,为绿潮规模控制提供参考。

Other Abstract

The world’s largest green tide caused by the green macroalge blooms of Ulva prolifera has occurred in the Yellow Sea every summer since 2007. From remote sensing monitoring, field investigation and biological studies, it is found that the green tides in the Yellow Sea originated from seaweed cultivation areas in the northern Jiangsu shoal. Based on the high-resolution optical remote sensing satellite images of GF-1, Sentinel-2A, HJ-1A/B, Landsat series and Sentinel-1A microwave data, the seaweed cultivation areas in the northern Jiangsu shoal were extracted. And the characteristics of seaweed cultivation activities in the northern Jiangsu shoal, mainly in the process of seaweed facility-recycling, were analyzed.

The main conclusions in this paper are listed as follows:

(1)The extraction results based on the microwave images in the period of algae growing by threshold method has consistent space distribution with that based on optical images. The spectral varies in the process of seaweed facility-recycling.

(2) Based on the area of seaweed cultivation areas extracted from different resolution remote sensing images, the conversion relationships were established.

(3) From the area results of seaweed cultivation areas in the northern Jiangsu shoal from 2012 to 2018, it was found that the areas of the seaweed cultivation regions in the northern Jiangsu shoal were relatively stable and didn’t expand significantly in the past seven years.

(4)From the extraction results of seaweed cultivation areas in North Jiangsu Shoal from the late April to the early June in 2012-2018, it was found that the areas of the seaweed cultivation regions varied differently in the process of seaweed facility-recycling. In 2015 and 2016, the recovery of farming facilites was earlier. In 2017 and 2018, the recoveries of farming facilites were relatively late.

(5)Combining the green tide information between 2012 and 2018, it is found that the scales of early green tide in 2017 and 2018 in which year the recoveries of farming facilities were late were significantly were smaller than that in 2014, 2015 and 2016 when the recoveries of farming facilities were earlier. The maximum daily coverage areas of green tide in 2017 and 2018 are much smaller than that in 2015 and 2016. The result shows that the scale of the green tide could be reduced to some extent by adjusting the seaweed facility-recycling in northern Jiangsu shoal.

The extraction results of seaweed cultivation areas and the characteristics of seaweed cultivation activities in the northern Jiangsu shoal could be a reference for decision-making of reducing green tide scale in the Yellow Sea.

Subject Area环境科学技术 ; 环境工程学 ; 环境工程学其他学科
MOST Discipline Catalogue工学 ; 工学::环境科学与工程(可授工学、理学、农学学位)
Table of Contents

1 引言

1.1 选题背景与意义

1.1.1 黄海绿潮的暴发及其影响

1.1.2 黄海绿潮起源于苏北浅滩海藻养殖区

1.1.3 苏北浅滩海藻养殖

1.2 国内外研究现状

1.2.1 国外海藻遥感提取研究现状

1.2.2 国内海藻遥感提取研究现状

1.3 研究内容和技术路线

1.3.1 研究内容

1.3.2 技术路线

2 研究区域概况与数据介绍

2.1 研究区概况

2.2 数据简介

2.2.1 Sentinel-2 Sentinel-1 影像

2.2.2 GF-1 影像

2.2.3 HJ-1 影像

2.2.4 Landsat 系列影像

2.3 数据处理软件

2.3.1 ENVI

2.3.2 ArcGIS

2.3.3 SNAP

2.4 主要的数据预处理

2.4.1 影像裁剪

2.4.2 辐射定标

2.4.3 大气校正

2.4.4 重投影

2.4.5 影像配准

3 光学遥感和微波遥感提取养殖区的原理与方法研究

3.1 光学遥感提取海藻养殖区

3.1.1 提取原理

3.1.2 不同分辨率影像提取面积换算关系的建立

3.2 微波数据提取原理与方法

3.2.1 Sentinel-1 卫星获取养殖区信息原理

3.2.2 阈值分割法提取海藻养殖区

3.2.2.1 Sentinel-1 卫星 VH 极化方式下的养殖区提取

3.2.2.2 Sentinel-1 卫星 VV 极化方式下的养殖区提取

4 海藻养殖区提取结果

4.1 微波数据和光学数据提取结果空间分布情况对比

4.2 光学与微波准同步影像反映筏架回收进程

4.2.1 解译标志库建立

4.2.2 海藻养殖区在影像上存在的几种情况

4.3 苏北浅滩海藻养殖区面积提取结果与筏架回收进程

4.3.1 2012-2018 年苏北浅滩海藻养殖区面积提取结果

4.3.2 海藻养殖区季度提取结果

4.3.3 海藻养殖区养殖活动特征分析

5 苏北浅滩海藻养殖活动特征与黄海绿潮规模的讨论

5.1 海藻养殖区与 2012-2018 年黄海绿潮每年最大日覆盖面积

5.2 海藻养殖区与 2012-2018 年早期绿藻分布

5.3 小结

6 结论与展望

6.1 本文结论

6.2 本文创新点

6.3 展望

参考文献

作者简历及攻读学位期间发表的学术论文与研究成果

Pages80
Language中文
Document Type学位论文
Identifierhttp://ir.yic.ac.cn/handle/133337/24089
Collection中国科学院烟台海岸带研究所
Recommended Citation
GB/T 7714
魏振宁. 苏北浅滩海藻养殖区精细化遥感与筏架回收动态监测[D]. 北京. 中国科学院大学,2019.
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