Spatio-temporal distribution of NDVI and its influencing factors in China

• The main factor that affects NDVI in most areas of China is surface soil moisture (SSM), followed by temperature, while arid root zone (RZSM) and profile (PSM) are the influencing factors. climate zones can be roughly divided into northern, southern northwestern inland areas, there transitional between different zones. Deep learning simulate well, Nash efficiency coefficients during training verification periods 0.893 0.833, respectively. It shows these selected factors predict changes well. environmental drift discovered concept detection mainly Heilongjiang River Basin Northeastern China, Yunnan, Sichuan, Southern Tibet Southwestern Gansu, Qinghai Xinjiang Northwestern China. Normalized Difference Vegetation Index (NDVI) an important indicator reflecting state regional environment, which affected precipitation, water content, so on. This study analyzed influence on through spearman correlation coefficient (SCC) standard regression (SRC), carried out zoning principal component analysis (PCA) cluster analysis, simulated value deep algorithm, spatial mutation positions detection. research results show algorithm very (NSE) However, details some rough. impact basically determine status NDVI, used to NDVI. provides reference for zoning, change simulation.