[Spatiotemporal variation and driving factors of growing season NDVI in the Tibetan Pla-teau, China.] / 青藏高原植被生长季NDVIæ—¶ç©ºå˜åŒ–ä¸Žå½±å“å› ç´ .

It is important to understand the response of vegetation to climate change in Tibetan Pla-teau (TP), an ecological barrier for China and Asia. The spatiotemporal variation of the normalized difference vegetation index (NDVI) of vegetation growing season were analyzed based on the gro-wing season NDVI retrieved from MOD09A1. The relationship between NDVI and climate factors was analyzed by combining the data of meteorological stations in TP from 2001 to 2018. The results showed that NDVI in the growing season showed a slow upward trend during the study period. There was substantial interannual variation of NDVI in different climate regions. The fluctuation magnitude of NDVI value was plateau humid climate region>semi-humid climate region>semi-arid climate region>arid climate region. The proportion of area with increasing and decreasing NDVI in humid climate region, semi-humid climate region, arid climate region, semi-arid climate region on TP were 1.4% and 1.9%, 4.9% and 1.5%, 16.4% and 0.8%, 7.0% and 2.0%, respectively. The areas of increasing NDVI in arid and semi-arid climate region was significantly larger than humid and semi-humid region. Temperature was the leading factor affecting the change of NDVI in humid and semi-humid region. The impact of precipitation on NDVI was significantly stronger than that of other climate factors in arid region. The impact of air temperature in growing season on NDVI was stronger than that of precipitation and relative humidity.

[Spatio-temporal Variation Characteristics Monitored by Remotely Sensed Technique of PM2.5 Concentration and Its Influencing Factor Analysis in Sichuan Basin, China].

The spread of atmospheric pollutants in the Sichuan Basin is difficult because of its unique topography, static wind, high humidity, and other meteorological conditions. Owing to the acceleration of urbanization and industrialization, PM2.5 pollution in the region is becoming increasingly severe, and the Sichuan Basin has become one of the key areas of national air pollution prevention and control. In this study, based on the remote sensing inversion product of PM2.5 concentration, spatial autocorrelation and gray correlation analyses are used to evaluate the spatial and temporal distribution characteristics and influencing factors of PM2.5 concentration in the Sichuan Basin. The results show that PM2.5 concentration has significant spatial aggregation; the high-high aggregation types are concentrated, low-low aggregation types are more dispersed, and coniferous forest has a significantly higher inhibitory effect on the absorption of PM2.5 than the shrub, grassland, and other vegetation types. The main meteorological factors affecting PM2.5 concentration in the Sichuan Basin are wind speed and temperature; population density and economic scale are the main human-activity factors affecting PM2.5 concentration in the Sichuan Basin, and the change in the industrial structure and scale also has a certain influence on the PM2.5 concentration.