Sensitivity Analysis of Remote Sensing Vegetation Index to Phenological Characteristics of Northern Vegetation: A Case Study in the Northern Foothills of Qinling Mountains (China)

Vegetation plays an important role in the exchange of heat and moisture in the earth-atmosphere system, and the vegetation index can not only better measure the growth and changes of vegetation, but also provides required data for meteorological, hydrological, ecological and other studies. Therefore, in-depth study of the spatial and temporal changes in regional vegetation index is of great significance for guiding eco-logical environment protection and governance. This paper takes the northern foot-hills of the Qinling Mountains and its north area in Shaanxi as the research object, an-alyzes the sensitivity of normalized vegetation index (NDVI) acquired from Sentinel-2, Landsat and MODIS data to the phenological characteristics of vegetation, and uses the linear regression slope method and partial correlation coefficient method to ana-lyze and discuss the spatiotemporal distribution characteristics and influencing factors of NDVI at different time scales. The results show that: 1) Sentinel-2 images and MODIS images have better spatiotemporal consistency in obtaining monthly NDVI data and refining vegetation phenological characteristics in the study area than Landsat images; 2) NDVI at different time scales in the study area showed a signifi-cant upward trend during 2001-2023, with a large NDVI increase mainly concentrated in the eastern part of the study area, especially in the Lishan Mountain area, while the areas with a decrease or no significant change in NDVI are mainly urban areas where human life and production are relatively frequent; 3) The NDVI in most areas of the study area showed an increasing trend from 2019 to 2023, especially in the Lishan Mountain area within the ecological protection and restoration project area, but there was a large area of NDVI decrease in the western part of the Qinling mountain front flood plain; 4) The lagging effects of precipitation and air temperature on monthly NDVI are both positive in a short period of time. Meanwhile, in spring and monthly scales, precipitation and air temperature have a positive correlation with vegetation growth in the study area, and the influence of air temperature is more significant.