A study on the extraction of Red Beach Suaeda salsa and its change trends in recent 5 years based on HY-1C data
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摘要: 为掌握红海滩翅碱蓬(Suaeda salsa)群落分布现状及修复情况,本文采用2018−2022年HY-1C卫星海岸带成像仪(CZI)数据,基于现场实测光谱特征分析,构建翅碱蓬遥感提取模型,获得了5期翅碱蓬群落空间分布数据,提取精度优于87%;基于提取结果,开展了红海滩翅碱蓬群落时空分布及类型水平上景观格局的变化分析,结果显示:近5年来,翅碱蓬群落分布面积总体呈显著增加趋势,斑块类型面积(CA)、斑块所占景观面积比例(PLAND)、最大斑块指数(LPI)、有效网格大小(MESH)、平均斑块面积(AREA_MN)等指标呈先减小后上升趋势,破碎化指数(SPLIT)先增大后减小、聚集指数(AI)总体呈上升趋势,可见翅碱蓬群落在红海滩景观构成中占比逐年增大,景观形状复杂度提升,破碎化势头得到逆转,聚集性分布趋势较为明显,这说明自2019年开始实施的翅碱蓬规模化修复工程成效显著;另一方面,翅碱蓬群落生境在总体持续向好的同时又表现出恢复水平空间不均衡的特点,大致为中、东部好于西部,南部好于北部。本文结果可为修复工程的效果评估工作提供基础数据,并为今后修复施工的空间布局规划提供决策参考。Abstract: In order to master the current distribution and the restoration status of Suaeda salsa in the Red Beach, a remote sensing extraction model was constructed based on the HY-1C satellite CZI data and on-site measured spectral. Five periods of spatial distribution data of S. salsa were obtained in 2018−2022, with the extraction accuracy better than 87%; based on the extracted results, a change analysis on the spatio-temporal distribution and the class-level landscape pattern of S. salsa was conducted. The results show that: in the past 5 years, the overall distribution area of the S. salsa community has shown a significant increase trend, with indicators such as class area (CA), percentage of landscape (PLAND), largest patch index (LPI), effective mesh size (MESH), and mean patch size (AREA_MN) showing a first decreasing and then increasing trend, splitting index (SPLIT) first increasing and then decreasing, and aggregation index (AI) overall showing an upward trend. It can be seen that the proportion of S. salsa community in the landscape composition of Red Beach has been increasing year by year, the complexity of landscape shape has increased, the fragmentation trend has been reversed, and the trend of aggregation distribution is more obvious. This all indicates that the large-scale restoration project of S. salsa implemented since 2019 has achieved a significant result. The biotope of the Red Beach S. salsa continues to improve, but at the same time, it shows a spatial imbalance of the recovery level, which is generally better in the middle and east than in the west, and better in the south than in the north. The results of this paper can provide basic data for the evaluation of the effectiveness of the restoration project, and provide decision-making reference for the spatial planning in the future restoration work.
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Key words:
- Red Beach /
- HY-1C /
- Suaeda salsa /
- space distribution /
- landscape indices
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表 1 数据成像时间与潮位信息
Tab. 1 Data imaging time and tide level information
序号 日期 成像时间 卫星轨道号 潮位 1 2018年10月2日 10:46 359 中高潮位 2 2019年9月18日 10:50 5390 中高潮位 3 2020年9月30日 10:46 10808 中低潮位 4 2021年10月7日 10:34 16144 中低潮位 5 2022年9月19日 10:40 21118 中高潮位 注:表中潮位信息来自海事服务网(https://www.cnss.com.cn/html/tide.html)。 表 2 本文采用的景观格局指数列表
Tab. 2 List of landscape indices used in this article
景观指数(英文缩写) 单位 生态意义 斑块类型面积(CA) hm2 某一类型斑块的总面积 斑块所占景观面积比例(PLAND)
% 某一类型斑块总面积占整个景观面积的百分比,取值范围(0,100),值越小,表示景观中该类型越稀少 最大斑块指数(LPI)
% 某一类型中最大斑块占整个景观面积的百分比,直接体现了景观的优势类型,取值范围(0,100),值的变化反映了人类活动的方向和强弱 有效网格大小(MESH)
% 景观中斑块面积的平方和与景观总面积的比值,用于比较景观中斑块的平均面积,在景观总面积不变时,MESH变大,反映该类型面积增加,表明其在景观中的比重加大 斑块密度(PD) 个/(100 hm2) 表示每100 hm2土地范围内某一类型斑块数量 平均斑块面积(AREA_MN) hm2 某一类型斑块的平均大小,反映景观破碎程度 周长面积分维数(PAFRAC)
指景观不规则几何形状的非整数维数,反映景观形状复杂程度,能在一定程度上反映人类活动对景观格局的干扰程度,取值范围(1,2),指数越大景观越复杂,受人类活动干扰程度越高 破碎化指数(SPLIT)
表示景观空间被分割后的破碎化程度,一定程度上反映人类对景观的干扰程度,景观破碎化是生物多样性丧失的重要原因之一 聚集指数(AI) % 反映某一类型斑块间的连通性,取值范围(0,100),值越大,表示景观中同类斑块相互聚合,结构紧凑 表 3 已有文献中翅碱蓬提取方法及其结果精度
Tab. 3 Extraction methods and their accuracy in existing literatures
表 4 红海滩翅碱蓬群落类型水平上的景观格局指数
Tab. 4 Landscape indices at the level of community type of Red Beach Suaeda salsa
年份 CA/hm2 PLAND/% LPI/% MESH/% PD/(个·(100 hm2)−1) AREA_MN/hm2 PAFRAC SPLIT AI/% 2018 663.75 3.63 0.83 1.77 0.80 4.55 1.31 10 322.06 76.37 2019 481.13 1.19 0.41 0.89 0.14 8.75 1.23 45 552.91 84.67 2020 986.25 2.07 0.44 2.50 0.21 9.67 1.28 19 053.88 85.52 2021 2029.46 3.91 0.73 5.46 0.44 8.82 1.34 9 522.24 82.26 2022 2752.41 8.57 1.61 21.23 0.48 17.76 1.32 1 513.02 86.75 -
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