Variation Characteristic of NDVI and its Response to Climate Change in the Middle and Upper Reaches of Yellow River Basin, China

Observing vegetation normalized difference vegetation index (NDVI) changes, climate change characteristics, and their response relationship have a great significance to the ecosystem's regulation and improvement the human settlements. Based on GIMMS AVHRR NDVI and MODIS NDVI datasets as well as temperature, precipitation, and sunshine duration data, this study used unitary linear trend analysis, correlation analysis, RS, and GIS data to analyze the spatiotemporal variation characteristics of vegetation NDVI in the middle and upper reaches of the Yellow River between 1989 and 2018. It also analyzed the spatiotemporal response between vegetation NDVI and climate factors (temperature, precipitation, and sunshine duration). The results showed that the vegetation NDVI in the study area had an increasing trend over the past 30 years, growing by 31.28%, and the NDVI change in 81.83% of the pixels was positive, the highest being 0.025. The temperature in the middle and upper reaches of the Yellow River showed an obvious upward trend, showing an overall distribution pattern of low temperature in the southwest and high temperature in the southeast. The precipitation showed a gentle upward trend and a spatial distribution pattern of a gradual decrease from southeast to northwest. The sunshine duration showed an obvious decreasing trend and a spatial distribution pattern of gradually increasing from southeast to northwest. In the past 30 years, the annual mean NDVI in the study area had a positive correlation with temperature and precipitation and a negative correlation with sunshine duration.

Automated summary

The study analyzed the spatiotemporal variation characteristics of vegetation NDVI in the middle and upper reaches of the Yellow River from 1989 to 2018, and the relationship between vegetation NDVI and climate factors. The results showed an increasing trend in vegetation NDVI over the past 30 years, with positive NDVI changes in 81.83% of the pixels, while temperature, precipitation, and sunshine duration also exhibited specific trends and spatial distributions. In addition, the annual mean NDVI in the study area was found to have a positive correlation with temperature and precipitation, and a negative correlation with sunshine duration.