The Woods Hole Research Center, 149 Woods Hole Road, Falmouth, MA, 02540-1644, USA.
Glob Chang Biol. 2014 Oct;20(10):3147-58. doi: 10.1111/gcb.12647. Epub 2014 Jul 21.
Satellite-derived indices of photosynthetic activity are the primary data source used to study changes in global vegetation productivity over recent decades. Creating coherent, long-term records of vegetation activity from legacy satellite data sets requires addressing many factors that introduce uncertainties into vegetation index time series. We compared long-term changes in vegetation productivity at high northern latitudes (>50°N), estimated as trends in growing season NDVI derived from the most widely used global NDVI data sets. The comparison included the AVHRR-based GIMMS-NDVI version G (GIMMSg ) series, and its recent successor version 3g (GIMMS3g ), as well as the shorter NDVI records generated from the more modern sensors, SeaWiFS, SPOT-VGT, and MODIS. The data sets from the latter two sensors were provided in a form that reduces the effects of surface reflectance associated with solar and view angles. Our analysis revealed large geographic areas, totaling 40% of the study area, where all data sets indicated similar changes in vegetation productivity over their common temporal record, as well as areas where data sets showed conflicting patterns. The newer, GIMMS3g data set showed statistically significant (α = 0.05) increases in vegetation productivity (greening) in over 15% of the study area, not seen in its predecessor (GIMMSg ), whereas the reverse was rare (<3%). The latter has implications for earlier reports on changes in vegetation activity based on GIMMSg , particularly in Eurasia where greening is especially pronounced in the GIMMS3g data. Our findings highlight both critical uncertainties and areas of confidence in the assessment of ecosystem-response to climate change using satellite-derived indices of photosynthetic activity. Broader efforts are required to evaluate NDVI time series against field measurements of vegetation growth, primary productivity, recruitment, mortality, and other biological processes in order to better understand ecosystem responses to environmental change over large areas.
卫星衍生的光合活性指数是研究最近几十年全球植被生产力变化的主要数据来源。为了从遗留卫星数据集创建连贯的、长期的植被活动记录，需要解决许多因素，这些因素会给植被指数时间序列带来不确定性。我们比较了高纬度地区（>50°N）植被生产力的长期变化，这些变化是通过最广泛使用的全球 NDVI 数据集（GIMMS3g）中的生长季 NDVI 趋势来估计的。该比较包括基于 AVHRR 的 GIMMS-NDVI 版本 G（GIMMSg）系列及其最近的后继版本 3g（GIMMS3g），以及来自更现代传感器的较短 NDVI 记录，如 SeaWiFS、SPOT-VGT 和 MODIS。后两个传感器的数据以一种减少与太阳和视角相关的地表反射影响的形式提供。我们的分析揭示了大片地理区域，总面积占研究区域的 40%，在这些区域中，所有数据集都表明在其共同的时间记录中植被生产力发生了类似的变化，而在其他区域中，数据集则显示出相互矛盾的模式。较新的 GIMMS3g 数据集显示，在研究区域的 15%以上地区，植被生产力（绿化）呈统计上显著（α=0.05）增加，而其前身（GIMMSg）则没有这种情况，而相反的情况则很少见（<3%）。这对基于 GIMMSg 的植被活动变化的早期报告具有重要影响，特别是在欧亚大陆，GIMMS3g 数据中绿化现象尤为明显。我们的研究结果突出了使用卫星衍生的光合活性指数评估生态系统对气候变化的响应存在的关键不确定性和信心领域。需要进行更广泛的努力，根据实地测量的植被生长、初级生产力、繁殖、死亡和其他生物过程来评估 NDVI 时间序列，以便更好地了解大面积生态系统对环境变化的响应。
