首页|基于Sentinel-2数据的苏州消夏湾生态安全缓冲区植被生长状况遥感监测评估

基于Sentinel-2数据的苏州消夏湾生态安全缓冲区植被生长状况遥感监测评估

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利用2021-2022年Sentinel-2卫星搭载的多光谱成像仪(MSI)遥感数据,通过SNAP遥感软件提供的植被生物物理参数处理模块(Biophysical Processor),反演了苏州消夏湾生态安全缓冲区的5种植被生物物理参数,包括植被吸收光合有效辐射比例(FAPAR)、植被覆盖度(FVC)、叶面积指数(LAI)、冠层叶绿素含量(CCC)和冠层含水量(CWC),开展植被生态环境监测评估研究.结果表明,该生态安全缓冲区2021年建成并投入运行后,植被覆盖度和生物量有所增加,区域植被冠层结构有所改善,植被生物物理参数从一定的角度反映了消夏湾生态安全缓冲区发挥了生态涵养成效.该研究方法能在大尺度上快捷、高效地反演植被生物物理参数,可为通过植被遥感动态监测评估生态安全缓冲区的生态功能提供有益的借鉴.
Remote Sensing Monitoring and Assessment of Vegetation Growth of Ecological Safety Buffer Zone in Suzhou Xiaoxia Bay Using Sentinel-2 Data
In the study,the Sentinel-2 MSI satellite data for year 2021 and 2022 were used to retrieve five vegetation biophysical indicators:FAPAR(Fraction of Absorbed Photosynthetically Active Radiation),FVC(Fraction of Vegetation Cover),LAI(Leaf Area Index),CCC(Canopy Chlorophyll Content),and CWC(Canopy Water Content)in the ecological security buffer zone of Xiaoxia Bay in Suzhou.The five vegetation biophysical indicators were retrieved from Biophysical Processor module provided by SNAP based on the combination of vegetation canopy radiative transfer model and machine learning.The results showed that after the completion and operation of the ecological safety buffer zone since 2021,the vegetation canopy structure,cover,biomass,and ecological environment have been improved.The vegetation biophysical indicators can reflect the ecological conservation effectiveness of the ecological safety buffer zone from a certain perspective.The methodology of this study can quickly and efficiently invert vegetation biophysical parameters on a large scale and provide useful reference for dynamic monitoring and assessment of ecological function of ecological safety buffer zone using remote sensing.

Ecological safety buffer zoneSentinel-2Vegetation biophysical indicatorRemote sensing retrievalSuzhou Xiaoxia Bay

单阳、钱晓瑾、姜晟、王甜甜、张悦、余悠然、纪轩禹、郭金金、魏玉强、王茹、李旭文

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江苏省环境监测中心,江苏 南京 210019

南京邮电大学,地理与生物信息学院,江苏 南京 210023

生态安全缓冲区 Sentinel-2 植被生物物理量 遥感反演 苏州消夏湾

江苏省环境监测科研基金项目江苏省环境监测科研基金项目江苏省环境监测科研基金项目

221622072203

2024

环境监控与预警
江苏省环境监测中心

环境监控与预警

CSTPCD
影响因子:0.788
ISSN:1674-6732
年,卷(期):2024.16(1)
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