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摘要:
NDVI（Normalized Difference Vegetation Index，归一化植被指数）能有效反映地表植被覆盖程度，研究其时空分布及驱动因子，对生态文明建设具有重要意义。本文利用武汉市2000—2022年MODIS影像计算的NDVI数据，进行时空及相关性分析，结果表明：（1）武汉市NDVI整体呈现增长趋势，市中心城区相对较低，市北部、南部植被覆盖较好；（2）武汉市NDVI在2000—2005年基本稳定，2005—2022年呈现增长，NDVI月度均值呈现负偏态，1-8月为增长趋势，8-12月为降低趋势；（3）武汉市NDVI在2004—2005、2017—2018年呈现明显增长，2007—2008年呈现明显降低，相比2000年，2022年增长明显；（4）时序预测结果显示2021—2025年武汉市NDVI呈现增长趋势，4月-10月NDVI增长对NDVI年度增长贡献明显；（5）NDVI与年降水量存在中等强度正相关，与武汉市绿化资金投入存在较强正相关，绿化资金投入是武汉市NDVI增加的重要原因。
Abstract:NDVI (Normalized Difference Vegetation Index) can effectively reflect vegetation coverage, and can be used to study its spatial and temporal distribution and driving factors, which is of great significance for the construction of ecological civilization. This paper utilizes NDVI data calculated from MODIS images of Wuhan City from 2000 to 2022 to conduct spatial-temporal and correlation analysis. The results show that: 1) The overall NDVI in Wuhan City shows a growing trend, with relatively lower values in the central urban area and better vegetation coverage in the northern and southern parts of the city. 2) The NDVI in Wuhan City remained stable from 2000 to 2005, and increased from 2005 to 2022, with the monthly mean NDVI showing a negative skew, an increasing trend from January to August, and a decreasing trend from August to December. 3) There were significant increases in NDVI in Wuhan City during 2004—2005 and 2017—2018, and a significant decrease during 2007—2008. Compared to 2000, there was a noticeable increase in 2022.4) The time series prediction results indicate that the NDVI in Wuhan City will show a growing trend from 2021 to 2025, with the increase in NDVI from April to October contributing significantly to the annual NDVI growth. 5) There is a moderate positive correlation between NDVI and annual precipitation, and a strong positive correlation between NDVI and the city's greening fund investment which is an important reason for the increase in NDVI in Wuhan City.
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Key words:
- Wuhan City /
- NDVI /
- spatiotemporal analysis /
- Time Series Forecasting Model /
- correlation analysis
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表 1 皮尔逊相关系数对照表
Table 1. Pearson correlation coefficient comparison table Translation
相关性 负值 正值 无相关性 −0.1~0.0 0.0~0.1 弱相关性 −0.3~−0.1 0.1~0.3 中相关性 −0.5~−0.3 0.3~0.5 强相关性 −1.0~−0.5 0.5~1.0 
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