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日光诱导叶绿素荧光遥感及其在陆地生态系统监测中的应用

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  • 南京大学国际地球系统科学研究所, 南京大学地理与海洋科学学院, 自然资源部国土卫星遥感应用重点实验室, 江苏省地理信息技术重点实验室, 南京, 210023

收稿日期: 2022-06-06

  录用日期: 2022-09-05

  网络出版日期: 2022-09-16

基金资助

国家自然科学基金(42125105);国家自然科学基金(42071388)

Remote sensing of solar-induced chlorophyll fluorescence and its applications in terrestrial ecosystem monitoring

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  • International Institute for Earth System Sciences, School of Geography and Ocean Science, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China

Received date: 2022-06-06

  Accepted date: 2022-09-05

  Online published: 2022-09-16

Supported by

National Natural Science Foundation of China(42125105);National Natural Science Foundation of China(42071388)

摘要

日光诱导叶绿素荧光(SIF)是近十年来迅速发展的新型植被遥感技术, 可以弥补以“绿度”为基础的植被指数等传统光学遥感观测的不足, 为大尺度植被光合作用监测提供了新方法。随着塔基、无人机、机载和星载SIF观测技术的快速发展以及SIF机理研究的推进, SIF遥感为陆地生态系统生理生化参数和生产力反演、非生物胁迫早期探测、光合物候提取和植被蒸腾作用监测等研究提供了重要技术支撑。该文首先系统阐述了SIF遥感的基本原理、观测技术和反演算法, 进而回顾了SIF遥感在陆地生态系统监测中的应用现状, 最后对天空地一体化SIF观测、SIF机理研究、新兴生态学应用等领域进行展望。

本文引用格式

吴霖升, 张永光, 章钊颖, 张小康, 吴云飞 . 日光诱导叶绿素荧光遥感及其在陆地生态系统监测中的应用[J]. 植物生态学报, 2022 , 46(10) : 1167 -1199 . DOI: 10.17521/cjpe.2022.0233

Abstract

Recent advances in solar-induced chlorophyll fluorescence (SIF), which is a complement to optical remote sensing based on greenness observation, have made it possible to monitor the photosynthesis of plants in terrestrial ecosystems using state-of-the-art technologies. With the rapid development of tower-based, unmanned aerial vehicle (UAV), airborne and space-borne SIF observation technology and improving understanding of SIF mechanism, SIF is providing essential data support and mechanism understanding for the estimation of biological traits and gross primary production of terrestrial ecosystem, early detection of abiotic stress, extraction of photosynthetic phenology and monitoring of transpiration. In this review, we first introduce the fundamental theory, the observation systems and technologies and the retrieval method of SIF. Then, we review the applications of SIF in terrestrial ecosystem monitoring. Finally, we propose a roadmap of activities to facilitate future directions and discuss critical emerging applications of SIF in terrestrial ecosystem monitoring that can benefit from cross-disciplinary expertise.

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