生长季植被聚集指数的长时序变化特征探究 ^*

Long-term variation trend in vegetation clumping index in the growing season

摘要

植被聚集指数（clumping index，CI）是反映植被冠层空间分布聚集特征的关键结构参数，对植被冠层的辐射截获及全球碳、水循环具有重要作用. 由于 CI 在生长季体现植被叶片聚集结构信息，本文选取了 20 a（2001-2020 年）MODIS CI 月产品数据，基于 MODIS 物候产品（MCD12Q2），在前人研究的基础上，筛选得到生长季 CI 月产品的代表值，并针对 CI 产品的物候波动和潜在异常值的问题，改进了 Theil-Sen Median 趋势分析方法，探究了生长季 CI 的长时序变化特征及其与叶面积指数（leaf area index，LAI）、植被覆盖度（fractional vegetation coverage，FVC）之间的关系. 结果表明：数据质量相对于年均值和生长季均值均有所提高，30% 左右的生长季 CI 代表值存在有意义的年际变化，但变化率较小，多集中在-0.005~0.005 a^-1；CI 与 LAI、FVC 的变化趋势呈不同程度相关性，且在变化趋势相反时相关性更显著. 本研究可为 CI 产品数据优化提供参考，对理解 MODIS CI 产品的时空变化特征，以及进一步促进 CI 产品在全球碳、水循环的应用有重要参考价值.

Abstract

Clumping Index (CI), a key structural parameter characterizing spatial aggregation of vegetation foliage, plays an important role in regulating canopy radiation interception, global carbon and water cycles. Long-term CI products have been operationally generated from the MODIS BRDF/albedo product. In this study, we selected 20-year (2001–2020) MODIS monthly CI products to explore the long-term variations in vegetation CI in the growing season, because CI can capture leaf clumping structures more effectively. The MODIS phenology product (MCD12Q2) was used to mask full-year monthly CI data, acquiring representative CI values for the growing season. To address potential outliers in the CI product, we improved Theil–Sen Median trend analysis method that was probably more appropriate to examine long-term CI variations trend. We explored the relationships between CI and leaf area index (LAI) and fractional vegetation coverage (FVC), respectively. The CI data quality in the growing season is improved compared to CI yearly means. Thirty percent (30%) of selected representative CIs show significant long-term variation trend, mostly falling within -0.005 per year to 0.005 per year. Such a trend is related to the trends of LAI and FVC to varying degrees, particularly when CIs present negative correlations with LAI and FVC. This study helps potential users to optimize CI product data, improves understanding of long-term trend of MODIS CI products, thereby supports potential applications in relation to CIs as input in global carbon and water cycle.

关键词

聚集指数 / 叶面积指数 / 时间序列 / 长时序分析 / 变化特征

Key words

clumping index (CI) / leaf area index (LAI) / time series / long-term analysis / change features

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基金资助

国家自然科学基金资助项目(42471352)

北京市自然科学基金资助项目(QY25315)

国家自然科学基金重大资助项目(42090013)