Rapid spatial evaluation of earthquake-hit population after earthquake occurrence is required in the disaster emergency rescue management, due to its significant support for decreasing casualties and property losses. The correlation between earthquake-hit population and influencing factors are analyzed using the data from the 2013 Ms7.0 Lushan earthquake. Ten influencing factors including elevation, slope angle, population density, per capita GDP, distance to fault, distance to river, NDVI, PGA, PGV and distance to epicenter, are classified into environmental factors and seismic factors. The correlation analysis reveals characteristics that there is a nonlinear relationship between the earthquake-hit population and various factors, and per capita GDP and PGA factor have a stronger correlation with earthquake-hit population. Moreover, the spatial variability of influencing factors would affect the distribution of earthquake-hit population. The earthquake-hit population is evaluated using BP neural network with optimizing training samples based on the spatial characteristics of per capita GDP and PGA factors. Different number of sample points are generated in areas with different value intervals of influencing factors, instead of the random distribution of sample points. The minimum value of RMSE (Root Mean Square Error) from testing set is 18 people/km2, showing good accuracy in the spatial evaluation of earthquake-hit population. Meanwhile, the optimizing samples considering spatial characteristics could improve the convergence speed and generalization capability comparing to random samples. The trained network was generalized to the 2017 Ms7.0 Jiuzhaigou earthquake to verify the prediction accuracy. The mean absolute error of earthquake-hit population evaluation results in different counties under the Jiuzhaigou earthquake were 18357 people and 26121 people for optimizing samples and random samples, respectively. The evaluation results indicate that BP neural network considering the correlation characteristics of factors has the capability to evaluate the earthquake-hit population in space, providing more detailed information for emergency service and rescue operation.