Fire is an important disturbance factor in forest and grassland ecology. The study of the subfactors of fire occurrence can help analyze the law of occurrence of forest and grassland fires and predict the trend of fire development. The software Matlab 2009a was used to carry out the wavelet analysis of statistical data of China's forest and grassland fires. Daubechies 10 was used as a wavelet base to decompose and reconstruct the wavelets. The effects of subsequences of different time scales on forest and grassland fires under various fire influence factors were discussed. The results showed that,on the time scale of 2-5 years,forest and grassland fires were quite different,and their periodicity was not obvious. Grassland fires occurred frequently in about 3-5 years,indicating that human factors were the main causes of grassland fires except for a few other factors. On the time scale of more than 10 years,the fluctuation of fuels and vegetation had slight effect on the number of forest and grassland fires in recent years. Although the longterm climate could have a greater impact,the number of forest and grassland fires has remained at a relatively low level, and the areas of forest fires showed a slight increase trend in 1993-2003,and the areas of forest fires showed a slight decline trend in 2004-2016. The areas of grassland fires showed an increase trend in 1994-2004,and the areas of grassland fires showed a steady decline trend in 2005-2016. It was expected that the areas of forest and grassland fires in China would continue to decrease slightly in the future. The occurrence times of forest and grassland fires generally showed decline trends,but the occurrence times of forest fires were still in the wavelet trough,expecting that the occurrence times of grassland fires would continue to decrease steadily. Although the occurrence times of forest fires would fluctuate at a relatively low level,the frequency of fire may be higher than that in 2016,so the occurrence of forest fires would also be in a relatively active state in the future.