植被在陆地碳循环和气候系统中发挥着重要作用, 近几十年来众多研究集中于分析植被生长状况的动态变化。 拥有大面积高海拔区域的青藏高原是“世界的第三极”, 其植被生长状况对全球变暖现象十分敏感。 而由光谱的可见光红波段和近红外波段反演产生的NDVI, 则是监测植被生长状况的最有效工具之一。 通过一元线性回归模型, 在青藏高原地区利用2000年到2014年的MODIS资料将GIMMS NDVI数据集从1982到2006年的时间序列扩展至2014年。 相比已有的研究, 因考虑了尺度变化引起的残差, NDVI扩展数据集的精度得到进一步提高。 该方法可以为今后不同NDVI数据集耦合提供一种新的思路。 利用1982年到2014年的NDVI新数据集可以发现以下结果: 青藏高原植被生长季的生长存在明显的增长趋势（0.000 4 yr-1, r2=0.585 9, p<0.001）, 春、 夏和秋季的增长率分别为0.000 5（r2=0.295 4, p=0.001）, 0.000 3（r2=0.105 3, p=0.065）和0.000 6（r2=0.436 7, p<0.001）。 因高原植被生长, 促进该区域碳积累效应, 故青藏高原植被在1982到2014年间是一个稳定的碳吸收区。 结合高原温度和降水资料分析植被生长状况增长的原因, 虽二者都具有增长趋势, 不过生长季及春、 夏和秋季的NDVI变化状况同温度的相关性显著高于降水。 在空间分布上, 各区域植被增长趋势同温度、 降水变化都具有明显的空间异质性。

Recently considerable researches have focused on monitoring vegetation changes because of its important role in regulating the terrestrial carbon cycle and the climate system. There were the largest areas with high-altitudes in the Qinghai-Tibet Plateau (QTP), which is often referred to as the third pole of the world. And vegetation in this region is significantly sensitive to the global warming. Meanwhile NDVI dataset was one of the most useful tools to monitor the vegetation activity with high spatial and temporal resolution, which is a normalized transform of the near-infrared radiation (NIR) to red reflectance ratio. Therefore, an extended GIMMS NDVI dataset from 1982—2006 to 1982—2014 was presented using a unary linear regression by MODIS dataset from 2000 to 2014 in QTP. Compared with previous researches, the accuracy of the extended NDVI dataset was improved again with consideration the residuals derived from scale transformation. So the model of extend NDVI dataset could be a new method to integrate different NDVI products. With the extended NDVI dataset, we found that in growing season there was a statistically significant increase (0.000 4 yr-1, r2=0.585 9, p<0.001) in QTP from 1982 to 2014. During the study period, the trends of NDVI were significantly increased in spring (0.000 5 yr-1, r2=0.295 4, p=0.001), summer (0.000 3 yr-1, r2=0.105 3, p=0.065) and autumn respectively (0.000 6 yr-1, r2=0.436 7, p<0.001). Due to the increased vegetation activity in Qinghai-Tibet Plateau from 1982 to 2014, the magnitude of carbon sink was accumulated in this region also at this same period. Then the data of temperature and precipitation was used to explore the reason of vegetation changed. Although the trends of them are both increased, the correlation between NDVI and temperature is higher than precipitation in vegetation growing season, spring, summer and autumn. Furthermore, there is significant spatial heterogeneity of the changing trends for NDVI, temperature and precipitation at Qinghai-Tibet Plateau scale.