Interannual variation in the start of vegetation growing season and its response to climate change in the Qinghai–Tibet Plateau derived from MODIS data during 2001 to 2016

Abstract

In recent years, remote sensing of phenology has become a useful tool to reveal the response and feedback of vegetation dynamics to global climate change due to its multitemporal phase, wide-coverage, continuous space coverage, and long-time series. Based on the Moderate Resolution Imaging Spectroradiometer data product MOD09A1, enhanced vegetation index (EVI) was calculated, and the time series EVI of the growing season in the Qinghai–Tibet Plateau (QTP) from 2001 to 2016 was reconstructed in light of the double logistic function filter. A dynamic threshold method was used to extract the starting date of the growing season (SOG) of vegetation. The characteristics of temporal–spatial variation of SOG of vegetation in QTP were analyzed, and the irregularity of the vegetation SOG in response to climate change was explored. The results show that: (1) the vegetation SOG in QTP varied between day of year (DOY) 110 and DOY 170 between 2001 and 2016. Affected by the spatial difference of hydrothermal conditions, the vegetation SOG is gradually delayed from the southeast to the northwest in the plateau, the latest of which in the southwest of Tibet. The SOG of vegetation in the east of QTP is in advance while it is delayed in the west. (2) the SOG of vegetation has the characteristics of vertical differentiation as well, especially in the range of 3600 to 5000 m, and the delaying rate of the SOG with increasing elevation is 10.7 day / km. (3) The time lag analysis between climatic factors and the vegetation SOG in QTP indicates that the SOG has a time lag of 0 to 15 days behind the air temperature and 15 to 30 days behind precipitation. The SOG of vegetation in southern Tibet and southern Qinghai is more sensitive to air temperature changes than precipitation, whereas the vegetation SOG in southwestern Tibet and southwestern Qinghai is more sensitive to precipitation changes than air temperature changes.