| 山东地区NDVI与气象因子持续性分析 |
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| 引用本文： | 刘亚龙,王庆,张明明,衣华鹏.山东地区NDVI与气象因子持续性分析[J].资源科学,2010,32(9):1777-1782. |
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| 作者姓名： | 刘亚龙 王庆 张明明 衣华鹏 |
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| 作者单位： | 鲁东大学海岸研究所,烟台,264025 |
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| 基金项目： | 山东省自然科学基金重点项目(编号：Z2008E03);山东省高等学校科技计划项目(编号：J09LE07);烟台市科技攻关项目(编号：2008323);教育部重点项目(编号：210122)。 |
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| 摘 要： | 探究植被的长期波动规律，对其持续性做出准确判断，是当前LUCC研究的重要课题。本文运用R/S
(重标极差分析)分析了1998年到2008年旬值NDVI序列和与之对应的旬值气温、降水、日照数等气象因子序列的
长程相关性，结果显示：NDVI序列和各个气象因子序列均存在长程相关性，并且Hurst指数存在突变点，气温、降
水、NDVI序列的突变点分布大致相同，分布约在55旬左右。在1~55旬时间尺度上，气温、NDVI序列的Hurst指数
大小很相近，呈很强烈的长程相关性。分析得出气温、降水序列的长程相关性影响NDVI的长程相关性，日照时间
对NDVI其持续性影响甚小。NDVI时间序列在时间分布上具有分形特征,植被演变存在状态持续性及其内在的周
期循环长度,从而为植被的非线性和复杂性研究提供了新的研究视角和实证结论。
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| 关 键 词： | NDVI Hurst指数 长程相关性 气象因子 山东省 |
Analysis of the Persistence of NDVI and Climatic Factors in the Shandong Peninsular |
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| LIU Yalong,WANG Qing,ZHANG Mingming and YI Huapeng.Analysis of the Persistence of NDVI and Climatic Factors in the Shandong Peninsular[J].Resources Science,2010,32(9):1777-1782. |
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| Authors: | LIU Yalong WANG Qing ZHANG Mingming and YI Huapeng |
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| Abstract: | Global change has been receiving much attention from the geosciences community in
that the core of land cover change, vegetation, is one of the most sensitive factors in global change.
Variations in vegetation can reflect the influence of meteorological factors as well as human
activities in global change at short-term scales. It is an important issue for Land Use and Land
Cover Change (LUCC) studies to explore fluctuation mechanisms and therefore to make
reasonable estimation of the persistence of vegetation. To explore long-term correlation of
vegetation with meteorological factors, i.e., temperature, precipitation, and sunshine duration,
Normalized Difference Vegetation Index (NDVI) time series data were employed in this work to
represent meteorological and vegetation factors respectively. Rescaled range analysis (R/S) was
employed to analyze the persistence of the NDVI time series and three corresponding
meteorological factors. The most obvious advantage of this method is that it is unnecessary to
presume a specific distribution characteristic when analyzing time series data, i.e., the stability of
the R/S-based results can reflect the time series data following other types of distributions. The
point-based time series data are frequently unavailable in studying NDVI because of the
discontinuity of remote sensing data. The SPOT/VEGETATION NDVI time series used in this
study can, however, circumvent the problem. Meteorological data used were from the China
Meteorological Administration. This study was conducted over Shandong Province with a long
shoreline affected by Land Ocean Interactions in the Coastal Zone (LOICZ). In addition to rapid
economic and societal development recent years, urbanization and industrialization have been
speeded up during the past decade. Six meteorological stations generally representing the
meteorological and climatic characteristics of the Shandong area were selected for this analysis.
The R/S was used to unravel the long-term correlation on the basis of NDVI time series and
corresponding meteorological observations from 1998 to 2008, particularly analyzing the Hurst
index of the meteorological factors and NDVI time series for all the selected stations. Results
showed that the temperature, precipitation and NDVI data essentially display the same distribution
characteristics. The long-term correlation exists for all factors. Each of the long-term correlation
can be divided into two phases, showing a stronger long-term correlation in the first phase, and a
stronger short-term correlation in the second phase. The persistence of those factors was found to
be very close. Except for the sunshine duration, positions of the turning points of the Hurst index
were close in all factors, indicating roughly 550 d or 560 d. This demonstrates that the long-term
correlation of NDVI is primarily affected by the persistence of temperature and precipitation, but
less by sunshine duration. The time series of NDVI was of fractal characteristics in temporal
distribution. There is a state persistence and its intrinsic cycle during processes of vegetation
evolution. These findings would be helpful for further examining the nonlinearity and complexity
of vegetation in the future. |
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| Keywords: | NDVI Hurst index Long-range correlation Limiting factors Shandong Province |
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