摘要
太阳诱导叶绿素荧光(Solar-Induced Chlorophyll Fluorescence,SIF)是光合作用的副产品,能够提供直观反映与植被光合作用相关的信息,同时也为光合作用和GPP的研究提供了新的手段。近年来,许多基于通量塔的荧光观测系统用于SIF和GPP的关系研究。定量估算SIF对陆地生态系统碳循环、初级生产力(Gross Primary Productionty,GPP)和干旱监测的研究具有重要的意义。综述了现有的卫星遥感SIF反演方法,并依据使用通道的位置将SIF反演方法分为基于夫琅禾费暗线法和基于大气吸收波段法两类;分析了SIF卫星遥感反演与应用存在的问题,主要包括传感器性能误差、云覆盖影响、角度效应影响、真实性检验、降尺度以及日尺度转换等;最后,对今后SIF卫星遥感反演的研究方向进行了展望。
Solar-Induced Chlorophyll Fluorescence (SIF) is a by-product of photosynthesis that provides direct information about vegetation photosynthesis and provides a new way to track photosynthesis and gross primary production.In recent years,there are many tower-based long-term fluorescence observation systems have been installed for studying the relationship between SIF and GPP.The quantitative remote sensing estimation of SIF is critical for terrestrial ecosystem carbon cycling,GPP .and drought monitoring.This paper systematically reviews the current status of satellite-derived SIF methods.Those methods are roughly grouped into two categories:fraunhofer line based method and atmospheric absorption band based method,according to the channels used for SIF retrieval;The problems of satellite SIF retrieval and application are discussed,including the instrumental effect,the daily variation of cloud effect,directional effects,the approaches of accuracy assessment,downscaling and the instantaneous to daily scale conversion;Finally,directions for future research to improve the accuracy of satellite-derived SIF are suggested.
作者
纪梦豪
唐伯惠
李召良
Ji Menghao;Tang Bohui;Li Zhaoliang(State Key Laboratory of Resources and Environment Information System,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China;College of Resources and Environment,University of Chinese Academy of Sciences,Beijing 100049 China;Key Laboratory of Agricultural Remote Sensing,Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning,Chinese Academy of Agricultural Sciences,Beijing 100081,China)
出处
《遥感技术与应用》
CSCD
北大核心
2019年第3期455-466,共12页
Remote Sensing Technology and Application
基金
国家自然科学基金项目(41571353、41871244)资助
