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自然资源遥感  2022, Vol. 34 Issue (4): 68-75    DOI: 10.6046/zrzyyg.2022182
  海岸带空间资源及生态健康遥感监测专栏 本期目录 | 过刊浏览 | 高级检索 |
基于最大值合成和最大类间方差法莱州湾滨海滩涂变化研究
李毅1,2(), 程丽娜2,3(), 鲁莹莹2,4, 张博淳1,2, 于森1,2, 贾明明2
1.吉林建筑大学测绘与勘查工程学院,长春 130118
2.中国科学院东北地理与农业生态研究所湿地生态与环境重点实验室,长春 130102
3.吉林大学地球科学学院,长春 130061
4.长春新区北湖英才学校,长春 130000
A study on the changes in coastal tidal flats in the Laizhou Bay based on MSIC and OTSU
LI Yi1,2(), CHENG Lina2,3(), LU Yingying2,4, ZHANG Bochun1,2, YU Sen1,2, JIA Mingming2
1. School of Surveying, Mapping and Exploration Engineering, Jilin Jianzhu University, Changchun 130118, China
2. Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China
3. College of Earth Science, Jilin University, Changchun 130061, China
4. Changchun New District Beihu Yingcai School, Changchun 130000, China
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摘要 

滨海滩涂是一种重要的滨海湿地类型,在维护生物多样性、影响全球气候和环境变化等方面具有重要的生态价值。由于滨海滩涂只在最低潮时期短暂全部呈现,先前的遥感解译结果中,滩涂信息存在明显的漏分和误分现象。基于Google Earth Engine(GEE)平台和Landsat系列卫星数据,构建1990年、2000年、2010年和2020年4个时间段的高质量密集时间序列影像堆栈,结合最大光谱指数合成算法(maximum spectral index composite, MSIC)和最大类间方差算法(Otsu algorithm, OTSU),对我国莱州湾滨海滩涂资源进行快速、自动提取。基于面向对象分析技术和模糊逻辑分析方法(fuzzy-based segmentation parameter, FbSP)最优尺度对滨海滩涂周边土地覆被进行解译,分析滨海滩涂的时空演变规律。结果表明: 1990—2020年间莱州湾滨海滩涂呈现持续减少的趋势,2020年莱州湾滨海滩涂面积为822.38 km2,相较于1990年减少了约40%,其中,2000—2010年缩减幅度最大,为304.78 km2; 除黄河口区域滨海滩涂向海迁移,莱州湾其他区域的滨海滩涂斑块整体呈向陆迁移趋势; 人类活动是近30 a间莱州湾滩涂变化的主导因素,其中,养殖池/盐田的扩张直接侵占了414.20 km2的滨海滩涂。

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李毅
程丽娜
鲁莹莹
张博淳
于森
贾明明
关键词 滨海滩涂Landsat影像MSICOTSU算法Google Earth Engine(GEE)    
Abstract

Coastal tidal flats, as a major type of coastal wetlands, have significant ecological value in maintaining biodiversity and influencing global climate and environmental change. Since they are only exposed in their entirety at the lowest tide, the previous remote sensing interpretation results showed significant omissions and misclassifications of the tidal flats. Based on the Google Earth Engine (GEE) platform and the Landsat series satellite data, this study constructed high-quality dense time series image stacks for four time periods, i.e., 1990, 2000, 2010, and 2020. Then, these image stacks were combined with the maximum spectral index composite (MSIC) algorithm and the Otsu algorithm (OTSU) for rapid and automatic extraction of coastal tidal flats resources in Laizhou Bay of China. Furthermore, the land cover around the coastal tidal flats was delineated based on the object-oriented analysis technology and the fuzzy-based segmentation parameter (FbSP) optimal scale. Finally, the spatial and temporal evolution patterns of the coastal tidal flats were analyzed. The results are shown as follows. During 1990—2020, the coastal tidal flats in Laizhou Bay gradually decreased, with an area of 822.38 km2 in 2020, a reduction of about 40% compared with that in 1990. The largest reduction was 304.78 km2 during 2000—2010. The coastal tidal flats near the Yellow River estuary showed a seaward migration, while the coast tidal flat patches in other regions of Laizhou Bay showed a landward migration. Human activities were the dominant factors in the changes in tidal flats in Laizhou Bay in the past 30 years. Among them, the expansion of aquaculture ponds/salt fields directly encroached on 414.20 km2 of coastal tidal flats.

Key wordscoastal tidal flat    Landsat imagery    MSIC    OTSU    Google Earth Engine (GEE)
收稿日期: 2022-05-09      出版日期: 2022-12-27
ZTFLH:  TP79  
基金资助:科技基础资源调查专项项目“中国主要沼泽植物种质资源数据库和信息共享平台建设”(2019FY100607);中国科学院青年创新促进会项目“中国滨海生态系统遥感”(2021227)
通讯作者: 程丽娜(1996-),女,硕士研究生,研究方向为滨海湿地遥感。Email: chengln20@mails.jlu.edu.cn
作者简介: 李 毅(2002-),男,本科生,研究方向为滨海湿地遥感。Email: liyi@iga.ac.cn
引用本文:   
李毅, 程丽娜, 鲁莹莹, 张博淳, 于森, 贾明明. 基于最大值合成和最大类间方差法莱州湾滨海滩涂变化研究[J]. 自然资源遥感, 2022, 34(4): 68-75.
LI Yi, CHENG Lina, LU Yingying, ZHANG Bochun, YU Sen, JIA Mingming. A study on the changes in coastal tidal flats in the Laizhou Bay based on MSIC and OTSU. Remote Sensing for Natural Resources, 2022, 34(4): 68-75.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/zrzyyg.2022182      或      https://www.gtzyyg.com/CN/Y2022/V34/I4/68
Fig.1  研究区地理位置
Fig.2  研究区域目标年份有效观测数量空间分布及比例
Fig.3  技术流程
类别 海水 养殖池/盐田 滨海植被 农田 内陆植被 滩涂 人工表面 内陆水体 裸地 总计
海水 105 0 0 0 0 7 0 1 0 113
养殖池/盐田 1 224 0 2 0 0 0 4 0 231
滨海植被 0 2 65 0 0 2 0 0 0 69
农田 0 4 0 222 1 0 2 0 1 230
内陆植被 0 0 4 0 17 0 0 0 0 21
滩涂 7 5 6 0 0 220 0 2 0 240
人工表面 0 0 1 9 1 0 110 0 1 122
内陆水体 2 0 0 0 0 2 0 31 0 35
裸地 0 0 0 0 0 0 0 0 7 7
总计 115 235 76 233 19 231 112 38 9 1 068
Tab.1  2020年滩涂及周边地物土地覆被分类结果的混淆矩阵
Fig.4  1990—2020年莱州湾地区潮间带土地覆被
Fig.5  1990—2020年滩涂与周边地物相互转化
土地利用类型 2020年
内陆植被 滨海植被 海水 裸地 内陆水体 农田 人工表面 滩涂 养殖池/盐田 总计
1990
内陆植被 49.03 1.51 0.00 0.16 0.69 45.67 20.80 0.00 7.53 125.39
滨海植被 1.66 219.78 6.39 1.81 8.53 73.29 12.56 9.75 227.43 561.20
海水 0.00 0.01 2 716.50 0.00 17.62 0.00 29.12 155.58 54.19 2 973.02
裸地 0.00 0.00 0.00 3.40 0.00 0.11 0.19 0.00 0.92 4.62
内陆水体 0.09 18.42 4.74 0.07 85.93 8.98 1.20 10.17 8.92 138.52
农田 9.78 14.22 0.00 0.65 5.84 1 137.57 87.21 0.23 79.62 1 335.12
人工表面 0.12 0.43 0.82 0.41 0.22 15.53 334.53 0.37 5.98 358.41
滩涂 3.67 100.30 129.08 0.00 46.06 2.58 24.68 645.27 414.20 1 365.84
养殖池/盐田 2.02 2.70 0.91 0.73 2.32 16.61 100.21 1.02 694.39 820.91
总计 66.37 357.37 2 858.44 7.23 167.21 1 300.34 610.50 822.39 1 493.18 7 683.03
Tab.2  1990—2020年土地利用转移矩阵
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