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引用本文:

DOI:

10.11834/jrs.20221647

收稿日期:

2021-10-09

修改日期:

2022-01-09

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数字半球摄影法获取植被表观聚集指数(ACI)采样尺度效应研究
摘要:

植被聚集指数(Clumping Index, CI)表征植被冠层叶片的聚集程度,是影响冠层内辐射传输的重要植被结构参数,对更好地理解冠层的辐射传输具有重要意义。数字半球摄影法(Digital Hemispherical Photography, DHP)与有限长度平均方法的结合被广泛应用于地面CI估算,研究表明,有限长度平均法应用于DHP图像时所划分的采样单元大小与CI测量结果密切相关,即CI随图像采样尺度的变化会表现出有意义的变化,植被表观聚集指数(Apparent Clumping Index, ACI)故应运而生,ACI的提出有助于加深对植被聚集效应的理解,拓展植被CI的地面间接测量,同时也对CI星载遥感产品的验证提出了新的挑战。目前,应用有限长度平均法估算ACI时,DHP图像中划分的采样单元的大小对ACI估算的影响规律,及其随不同植被类型的变化规律有待进一步探索。针对上述问题,本研究基于DHP图像,分别以一系列逐级增大的角度采样尺度对观测天顶角和方位角进行划分,共得到30种采样方法、17级角度采样分辨率,并将其分别应用于林、灌、草和农作物四种地类,探究了ACI在不同植被类型下随17级角度采样分辨率变化而变化的规律;同时,探讨了ACI的角度采样尺度效应与植被在空间中的分布形态,以及农作物生长阶段之间的密切联系。结果表明,在四种地类下,随17级角度采样分辨率的降低ACI从约0.5变化至0.8,平均增幅分别达到26%、29%、14%和35%;在大豆作物的不同生长阶段,随17级角度采样分辨率由高到低的变化,ACI的增长存在一定差异,增幅最大可达60%。本研究针对CI地面测量的不一致性问题展开研究,揭示了ACI角度采样尺度效应的方向依赖性规律,总结了不同植被类型下角度采样尺度对ACI估算结果影响的统一性和差异性,有望为CI遥感产品验证的不确定性分析提供地面测量数据变化的精细分析支撑。

Sampling scale effects of vegetation apparent clumping index (ACI) obtained by digital hemispherical photography
Abstract:

Objective:The clumping index (CI) represents the degree of leaf aggregation in the canopy, which is an important vegetation structural parameter affecting the radiative transport and is of great significance to better understand the radiative transport in the canopy. The apparent clumping index (ACI) was proposed to deepen the understanding of clumping effect and expand the field indirect measurement of CI. Studies showed that ACI is closely related to the sampling scale, and even the ACI measured by the same instrument changes significantly with the sampling scale, which presents a new challenge to the verification of CI products. The combination of digital hemispherical photography (DHP) and LX methods is widely used in the field ACI estimation, and one of the key steps of the combination of the two methods is the determination of sampling resolution. At present, the influence of sampling resolution on ACI estimation and its variation with different vegetation types need to be further explored. Method:When using LX method based on DHP measurement data, the sampling resolution is jointly determined by two factors: view zenith angle sampling scale (?θ) and view azimuth angle sampling scale (?φ). To solve the above problems, based on DHP images, this study divided the view zenith angle and view azimuth angle with a series of progressively increasing sampling scales, and obtained a total of 30 sampling methods and 17 levels of sampling resolutions, which were applied to forest, shrub, grass and crops respectively. The variation of ACI under different vegetation types was investigated with the decrease of the resolution of 17 levels of sampling. At the same time, the relationship between the sampling scale effect of ACI and the spatial distribution of vegetation and the growth stage of crops was discussed. Result:The results showed that the ACI varied from 0.5 to 0.8 in the four vegetation types with the decrease of the 17-level sampling resolution, with an average increase of 26%, 29%, 14% and 35%, respectively. At different growth stages of soybean crops, ACI increased with the decrease of 17-level sampling resolution, which was up to 60%. In general, ACI is directionally dependent with the change of sampling scale, and this characteristic is affected by the spatial distribution of observed objects. When the observed objects were randomly distributed (forest, shrub and grass), ACI generally showed a linear growth trend with the increase of VZA and VAA sampling scale; when the observed object is regular distribution (soybean crop), ACI is still affected by VZA and VAA sampling scale, and the influence of VZA sampling scale on ACI is very significant. Conclusion:The results of this study showed that ACI increased with the increase of sampling scale, that is, with the increase of sampling scale, vegetation aggregation weakened and gradually tended to random distribution. This study further explored the directional dependence of ACI on the change of sampling scale for different vegetation types and at present, how to select the optimal sampling scale for different vegetation types will be the focus of the future research. Detailed analysis of ACI field measurement and in-depth discussion of the possible uncertainties in the measurement process are the prerequisite for carrying out the authenticity inspection of CI products. This also has certain significance for improving the accuracy of CI estimation and CI products verification.

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