山地生态系统通量足迹遥感像元尺度空间代表性分析

邬昌林; 谢馨瑶; 李爱农

doi:10.11834/jrs.20232509

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山地生态系统通量足迹遥感像元尺度空间代表性分析
Spatial representativeness of flux footprints at pixel scales over mountainous ecosystems
2024年28卷第10期页码：2632-2650
纸质出版日期： 2024-10-07 ，
DOI： 10.11834/jrs.20232509
稿件说明：

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邬昌林，谢馨瑶，李爱农.2024.山地生态系统通量足迹遥感像元尺度空间代表性分析.遥感学报，28（10）： 2632-2650

Wu C L，Xie X Y and Li A N. 2024. Spatial representativeness of flux footprints at pixel scales over mountainous ecosystems. National Remote Sensing Bulletin， 28（10）：2632-2650
邬昌林，谢馨瑶，李爱农.2024.山地生态系统通量足迹遥感像元尺度空间代表性分析.遥感学报，28（10）： 2632-2650 DOI： 10.11834/jrs.20232509.

Wu C L，Xie X Y and Li A N. 2024. Spatial representativeness of flux footprints at pixel scales over mountainous ecosystems. National Remote Sensing Bulletin， 28（10）：2632-2650 DOI： 10.11834/jrs.20232509.

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—10

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。

Abstract

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.

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—10

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 representativenes

s at the pixel scales of 30

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.

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

Keywords

pixelspatial representativenesseddy covarianceflux footprint modelmountainous ecosystem

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