Temporal and spatial evolution of vegetation cover in Chengde based ontime series NDVI data

Chengde is a very important water conservation area and sand prevention area in Beijing-Tianjin-Hebei region. It is also an important part of the ecological environment support area. Its vegetation status will directly affect the improvement of regional ecological environment quality. Based on the NDVI data of MOD13Q1, linear regression analysis, pixel dichotomy and stability analysis were used to measure the spatiotemporal evolution characteristics of vegetation cover in Chengde from 2000 to 2018, and analyzed the impact of climate, terrain and other factors on vegetation coverage. The results showed that:(1) the interannual change of vegetation in Chengde has been improved. The NDVI value in summer is the highest in vegetation growing season, and the NDVI value in July is the largest in monthly change, and the annual average value is 0.775 2. (2) The results showed that there were spatial differences in the annual variation trend of vegetation. The area with extremely significant increase in vegetation index was the largest, accounting for 59.08%, while the area with extremely significant decrease and significant decrease accounted for 0.76% and 0.58% of the whole area, respectively. They mainly distribute in the central and southern areas in Chengde. (3) The vegetation coverage of each district and county in Chengde is mainly high coverage, with an area of 45 585.69 km². In the pattern of vegetation coverage stability, the northwest fluctuates greatly, and the rest areas have good stability and low fluctuation. (4) The NDVI of Chengde is greatly affected by the precipitation and monthly average temperature from May to July, and the growth of vegetation may be affected by the lag effect of the previous meteorological conditions. In general, the NDVI value of low-lying areas in Chengde is relatively low. The research results can provide reference for Chengde to strengthen the ecological protection of critical regions, optimize the spatial development pattern of land and scientifically formulate ecological restoration measures.