摘要
遥感技术是大尺度上估算地表碳、水和能量等通量的重要信息来源。全球涡度通量观测数据集已广泛用于遥感通量数据产品的生产和评价,因此,科学评估遥感像元尺度上通量足迹的空间代表性对于遥感通量产品建模、验证和生产尤为重要。本文选择中国西南典型山地生态系统—王朗山地遥感四川省野外观测研究站(简称王朗站)区域为研究对象,使用二维参数化足迹模型刻画了通量观测足迹的时空变化特征,同时解析了通量观测足迹在多个遥感像元尺度(30 m、60 m、120 m、250 m、500 m、1000 m、1500 m和2000 m)上的空间代表性。结果表明:在通量足迹的空间变化上,王朗站内不同观测塔通量足迹范围跨度较大(10—103 m)且对称性较低(通常在40%以下),因此在山地生态系统进行遥感模型及产品验证时需要更加关注通量足迹的空间代表性差异;在通量足迹的时序变化上,王朗站内日尺度上的足迹重叠性差异明显(0%—88%),结合时序变化的足迹特征可进一步提升高时间分辨率下的模型验证和产品精度;王朗研究区内落叶阔叶灌丛站点、落叶阔叶林站点和常绿针叶林站点等3个观测塔的高度为10 m、30 m和75 m,其分别在30 m、60 m和1000 m像元尺度取得对通量足迹的最佳空间代表性。总之,由于山区通量观测的高空间代表性局限于高空间分辨率(观测高度较低时)和中低空间分辨率(观测高度较高时)的遥感像元,认知通量足迹在不同遥感像元尺度上空间代表性的差异,结合多尺度遥感观测数据和时空尺度扩展方法,可促进山区生态系统参量估算和通量研究。本研究可为站点观测尺度扩展、山地生态系统遥感数据产品生产和地球系统模型验证提供参考。
With the availability of remote sensing images since the 1970s,the spatial-temporal continuum observations of the land surface can be obtained at the global scale.In this manner,remote sensing is an important information source for the large-scale estimation of land surface carbon,water,and energy fluxes.Global eddy covariance flux datasets are widely used to evaluate and produce remote sensing flux products.Given that tower-based fluxes can only represent the small areas around the tower,a mismatch usually occurs between the tower-based fluxes and multiscale pixels of remote sensing.Thus,the spatial representativeness of flux footprints must be evaluated at multiscale pixels.In this study,we choose the Wanglang Mountain Remote Sensing Field Observation and Research Station of Sichuan Province,a typical mountainous ecosystem of Southwest China,as the study area.This study used a two-dimensional parametric footprint model(flux footprint prediction,FFP)to characterize the spatiotemporal variations and analyze the spatial representativeness of flux footprints at multiscale pixels(i.e.,30,60,120,250,500,1000,1500,and 2000 m).In this work,the land cover types and normalized difference vegetation index were used to characterize the spatial representativeness of footprint among vegetation types and vegetation density at multiscale pixels,respectively.At the same time,two site-level simple representativeness indices for land cover type and vegetation density were proposed to evaluate the footprint-to-pixel representativeness across flux towers at Wanglang station.Results showed that the footprint fetch varied across flux towers at Wanglang station(10—103 m),and the footprints at multiple temporal resolutions had a low symmetry(usually less than 40%).For the temporal variations of footprints,the overlap of footprints had evident changes at the daily scale(0%—88%),and the variations were reduced at the monthly scale(usually larger than 83%).As for the three flux towers around Wanglang station,results showed that the station of deciduous broadleaf shrub(with observed height at 10 m),deciduous broadleaf forest(with observed height at 30 m),and evergreen needleleaf forest(with observed height at 75 m)had the optimal spatial representativeness at the pixel scales of 30,60,and 1000 m,respectively.Moreover,compared with vegetation density,the discrepancies of spatial representativeness were more evident for vegetation cover.The spatial representativeness differences of footprints must be paid attention to while validating remote sensing models and producing flux datasets around mountainous ecosystems.Moreover,the corresponding footprints must be combined with tower-based observations to characterize the temporal variations of fluxes when modeling and producing flux products at high temporal resolution(e.g.,daily scale).Given that the high spatial representativeness of footprints was limited to the pixels at high(a lower tower)and medium-low(a higher tower)spatial resolution,the estimation of ecosystem parameters and flux research over mountainous areas could be promoted by cognizing the spatial representativeness of footprint at pixel scales and combining the multiscale remote sensing observations with the spatial and temporal scaling method.
作者
邬昌林
谢馨瑶
李爱农
WU Changlin;XIE Xinyao;LI Ainong(Research Center for Digital Mountain and Remote Sensing Application,Institute of Mountain Hazards and Environment,Chinese Academy of Sciences,Chengdu 610041,China;Wanglang Mountain Remote Sensing Field Observation and Research Station of Sichuan Province,Mianyang 621000,China)
出处
《遥感学报》
EI
CSCD
北大核心
2024年第10期2632-2650,共19页
NATIONAL REMOTE SENSING BULLETIN
基金
国家重点研发计划(编号:2020YFA0608702)
国家自然科学基金(编号:42201418)
中国博士后面上项目(编号:2021M700139)
中国科学院特别研究助理项目
中国科学院青年促进会项目。
关键词
遥感像元
空间代表性
涡动技术
通量足迹模型
山地生态系统
pixel
spatial representativeness
eddy covariance
flux footprint model
mountainous ecosystem