• 关键词：植被生物量  Sentinel-2A  江苏  遥感反演

• 基金项目：国家自然科学基金（No.41871097，41471078）； 江苏省农业科技自主创新资金项目（No.CX（18）2026）；江苏高校优势学科建设工程资助项目（No.PAPD）

• 闫丹丹
• 南京林业大学生物与环境学院，南京 210037;南京林业大学南方现代林业协同创新中心，南京 210037

• 李静泰
• 南京林业大学生物与环境学院，南京 210037;南京林业大学南方现代林业协同创新中心，南京 210037

• 薛媛媛
• 南京林业大学生物与环境学院，南京 210037;南京林业大学南方现代林业协同创新中心，南京 210037

• 戚丽萍
• 南京林业大学生物与环境学院，南京 210037;南京林业大学南方现代林业协同创新中心，南京 210037

• 栾兆擎
• 南京林业大学生物与环境学院，南京 210037;南京林业大学南方现代林业协同创新中心，南京 210037

• 摘要：Sentinel-2作为新型独特的光学对地观测遥感卫星，因拥有对植被生物监测的红光边缘波段而备受关注.植被生物物理特征对监测植被生长状况及研究全球碳氮循环过程等都具有重要意义.然而，在小尺度上利用统计模型方法进行植被理化参数反演的研究比较多，在大尺度上利用生物物理参数快速、高精度反演的研究较少.因此，本文以江苏省为研究区，对2019—2020年Sentinel-2A/B数据进行预处理和分析，利用SNAP中的生物物理量处理器模块，快速、高精度反演江苏省5类生物物理指标（叶面积指数、光合有效辐射吸收率、叶绿素含量、冠层含水量和植被覆盖度）.结果表明：①江苏省北部、中部及沿海地区的叶面积指数、光合有效辐射吸收率、叶绿素含量、植被覆盖度和植被冠层含水量均较高，而西南地区植被长势较差；②徐州、连云港、盐城、南通4个市的5类生物量指标均明显高于其他城市.以上分析表明植被生长状况主要受到区域温度、水源及地势的影响，除此之外还会受到城市化水平、国家政策的影响.本研究结果与江苏省土地利用程度和植被分布结果相吻合，该研究思路与方法可为区域大尺度植被生态环境特征研究提供技术参考和解决思路.

• Abstract：Sentinel-2 provides images with high spatial， spectral and temporal resolution. It covers 13 bands， incorporating two new spectral bands covering so-called red-edge region， which are very important for retrieval of vegetation biomass information of the regional vegetation ecological environment. Vegetation biophysical characteristics are of great significance for monitoring vegetation growth and studying the global carbon and nitrogen cycle process. However， most of the researches used statistical model methods to retrieve physical and chemical parameters of vegetation at a small scale. There are only few studies on the rapid and high-precision inversion of using biophysical parameters at a large scale. This paper presents a case study in Jiangsu Province. Based on sentinel-2A from 2019 to 2020， five vegetation biophysical characteristics including leaf area index （LAI）， the fraction of absorbed photo synthetically active radiation （FAPAR）， chlorophyll content in the leaf （LAI_CAB）， fraction of Vegetation Cover （FCOVER）， canopy Water Content （LAI_CW） were calculated quickly and accurately by using the biophysical parameter processing module in the SNAP software. Through the analysis of image characteristics and spatial location changes of these biomass indicators， it is concluded that the biomass in northern， central and coastal areas of Jiangsu Province are relatively high， while the southwestern region is low. From the perspective of administrative division， the five types of biomass indicators in Xuzhou， Lianyungang， Yancheng and Nantong are significantly higher than those of other cities. The above analyses showed that the growth of vegetation was mainly affected by regional temperature， water source and terrain. In addition， it is also affected by the level of urbanization and national policies. Our results are consistent with the results of land use in Jiangsu Province. The research ideas and methods provide technical reference and solutions for large-scale vegetation ecological environment characteristics researches.

• Key words：vegetation biophysical characteristics  Sentinel-2  Jiangsu  remote sensing retrieval

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