| 摘要: |
| 【目的】厘清近年来黄河源区植被覆盖变化及其对驱动因子的响应，为黄河源区生态环境可持续发展与科学预估气候变化对植被格局的影响提供理论依据。【方法】基于1999－2015年SPOT VGT NDVI数据集和中国区域高时空分辨率地面气象要素（ITPCAS）驱动数据集，运用趋势分析、Mann-Kendall非参数统计检验、R/S分析和相关分析等方法，分析了1999－2015年NDVI和气象因子的时空变化特征，并探讨温度、降水量、地表净辐射(Rn)等气象因子以及人类活动对植被覆盖变化的影响。【结果】（1）黄河源区多年平均NDVI空间分布呈东南高、西北低的格局，整体上NDVI呈增加趋势，每10年增速为1.6%，其中上升趋势的区域占研究区78.2%；NDVI在2003年附近存在突变；同时期温度和降水为振荡上升趋势，而Rn为振荡下降趋势，并且未来NDVI和各气象因子将持续这种变化趋势。（2）年平均NDVI与年平均温度呈显著正相关关系，与年平均降水量呈不显著正相关关系，而与年平均Rn呈不显著负相关关系；在偏相关分析中，NDVI与年平均温度的相关性最好。（3）NDVI对温度、降水量变化的响应滞后1个月左右，对Rn变化的响应滞后2个月左右。【结论】ITPCAS驱动数据集在黄河源区有较好的适用性；在年尺度和月尺度上，温度都是黄河源区植被生长影响最大的气象要素；黄河源区植被覆盖的增加主要归因于温度上升以及生态保护“综合性”工程的实施。 |
| 关键词: ITPCAS驱动数据集 时空变化 驱动因子 黄河源区 遥感影像 |
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| 基金项目:国家重点研发计划项目（2017YFC0403600）；国家自然科学基金项目（51509202，51679185） |
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| Relationship of vegetation cover change with climate factors in source region of the Yellow River based on ITPCAS forcing data |
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ZHANG Xiaolong,HUANG Lingmei,QUAN Quan,et al
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| Abstract: |
| 【Objective】The study aimed to clarify the relationship between vegetation cover and its driving factors to provide basis for the sustainable development of ecological environment and scientific estimation of climate change impacts on vegetation pattern in source areas of the Yellow River.【Method】Based on SPOT VGT NDVI (normalized difference vegetation index) data and the ITPCAS forcing dataset (reanalysis datasets),trend analysis,the Mann-Kendall statistical method,R/S analysis and correlation analysis were used to investigated the spatiotemporal changes of NDVI and climate factors during 1999-2015.The effects of temperature,precipitation and Rn (surface net radiation) and human activities on vegetation cover change were also analyzed.【Result】(1) The NDVI in source region of the Yellow River was high in the southeast and low in the northwest.The NDVI has been increasing with an average rate of 1.6% per 10 years from 1999 to 2015.The area with increasing trend accounted for 78.2% of the study area.There existed abrupt point in around 2003.Temperature and precipitation were on an upward oscillation trend during the same period,while Rn was opposite.The trend of NDVI and meteorological factors would continue in future.(2) The annual NDVI had significant positive correlation with temperature,insignificant positive correlation with precipitation,and insignificant negative correlation with Rn.The correlation between NDVI and annual temperature was best in partial correlation analysis.(3) The responses of NDVI to temperature and precipitation lagged by one month, while the response to Rn lagged by two months.【Conclusion】The ITPCAS forcing dataset had good applicability in source region of the Yellow River.In both annual and monthly scales,temperature was the most important meteorological factor influencing vegetation growth,and the increased NDVI was mainly attributed to climate warming and the implementation of comprehensive ecological protection project. |
| Key words: ITPCAS forcing data spatiotemporal change driving factors source region of the Yellow River remote sensing image |
