气候变暖背景下安徽省月NDVI动态变化研究

Dynamic Changes of Monthly NDVI in Anhui Province Under Background of Climate Warming

地表植被覆盖时空动态变化能很好地反映气候变化。基于2000~2016年MODIS NDVI逐月数据及同期内格点降水和气温数据,探讨了安徽省NDVI时空变化及其与气象因子的关系,结果表明:(1)安徽省NDVI呈显著增加的趋势,全省平均增速为5.7~11.3×10^(-3)/a,其中,旱地增长较快,阔叶林和灌丛增长较缓。时间上,除水田外,10月至翌年3月具有显著增加趋势,6~9月增加趋势不明显。空间上,皖南山区、江淮之间大别山区和淮北平原增长较快;(2)各种植被类型月均NDVI与气温或降水具有相关性。且NDVI均为与前一个月的气温或降水相关性最高的时滞特点;(3)像元尺度NDVI与气温的偏相关系数较大,其中正相关达到0.01显著性水平的面积占92.2%。而与降水的偏相关性较小,其中正相关达到0.01显著性水平的面积仅占8.2%。月尺度NDVI的驱动类型分析结果表明,气温驱动型占75.0%,降水气温共同驱动型占15.3%。研究结果可为全球变暖背景下区域生态系统管理和保护提供理论参考。

The spatiotemporal dynamic change of vegetation cover can well reflect the climate change. Based on the monthly data of MODIS NDVI from 2000 to 2016 and the precipitation and temperature data of the grid within the same period, the spatial and temporal changes of NDVI in Anhui Province and its relationship with meteorological factors are explored in this paper. The results show that:(1)NDVI in Anhui Province shows a significant increase trend, with average growth rate of 5.7-11.3×10^(-3)/a in the whole province. Among which dryland grows faster, while broad-leaved forest and shrub grows slower. In terms of time, there is a pronounced tendency from October to next March except paddy field, but not obvious from June to September. Spatially, the mountain areas in southern Anhui, Dabie Mountain Areas and Huaibei Plain are growing rapidly.(2)Monthly average NDVI has correlation with temperature or precipitation in each vegetation type. Moreover, the correlation has a one-month lag. That is, NDVI had the strongest correlation with last month’s temperature or precipitation.(3)On pixel-scale, the partial correlation between NDVI and temperature is very strong. The area with positive correlation reaching 0.01 significance accounts for 92.2%. However, the partial correlation with precipitation is weak. The area with positive correlation reaching 0.01 level only accounts for 8.2%. Driving factors analysis of monthly NDVI show that 75.0% is temperature-driving type, and 15.3% is precipitation and temperature co-driving type. The results of this study can provide a theoretical reference for the management and protection of regional ecosystems under global warming of terrestrial ecosystems.