鄂尔多斯植被的NDVI 3g动态及气候响应

[目的]研究鄂尔多斯地区生态格局以及在全球变化下的自然演变规律,揭示中国西部矿区人工扰动生态环境的时空变化。[方法]利用1982—2012年GIMMS NDVI 3g数据集和年均气温、降水量等气象数据,分别进行最大值合成、反距离加权法插值、线性回归与变化率分析、相关性分析等处理,揭示植被覆盖的时空变化趋势下蕴含的植物生理学机理,及其对气温和降水变化趋势的响应特征。[结果]鄂尔多斯地区植被返青期(start of season,SOS)始于4月下旬,枯黄期(end of season,EOS)结束于11月上旬,植被生长期(duration of season,DOS)NDVI初始阈值为0.12,平均生长期为198d;31a间鄂尔多斯地区植被绿度变化率(slope)为0.0023,植被变化趋势逐像元回归分析表明研究区80.8%的植被有轻微改善;31a间鄂尔多斯地区NDVI变化与年均气温和降水量的相关性分别为0.054和0.400。[结论]31a间鄂尔多斯地区植被返青期有提前趋势,枯黄期有滞后趋势,生长期有延长趋势;研究区大部分区域植被均有轻微改善;年均气温与降水量均呈现升高趋势,NDVI变化受温度和降水的共同作用,且NDVI最大值增高与年均降水量增加相关性较高,与年均气温升高相关性较低。

NDVI 3g Trend and Its Response to Climate Change in Ordos During Period from 1982 to 2012

[Objective] To study the ecological pattern and the natural evolution law under global change in Ordos region in order to reveal the temporal and spatial variation of ecological environment by artificial disturbance in the mining area in Western China.[Methods] GIMMS(global inventory modeling and mapping studies) NDVI 3g datasets from 1982 to 2012 and meteorological data(temperature, precipitation, etc.) were used as data sources, and the maximum value composites(MVC) method, inverse distance weighted method, piecewise regression analysis method, correlation analysis method were employed to reveal the spatial-temporal changes of vegetation cover and uncover plants'' response to temperature and precipitation changes.[Results] The start of season(SOS) of vegetation began in late April, the end of season(EOS) ended in early November, and the average duration of season(DOS) last 198 days. The initial threshold of NDVI was 0.12. The vegetation green rate(slope) was 0.002 3, and the trend of vegetation change by regression analysis showed that there was a slight improvement in 80.8% area in past 31 years. The correlation between NDVI and temperature and precipitation were 0.054 and 0.400.[Conclusions] The SOS comes a little earlier, the EOS lagged, and the DOS extended. There was a slight improvement in most area. The average annual temperature and precipitation showed an increasing trend. The NDVI change was determined by the interaction of temperature and precipitation. The correlation between NDVI and precipitation was higher than that between NDVI and temperature.