Abstract: It is very important to assess degree and area of crop loss accurately and quickly for a variety of purposes. In this paper, a method is designed as to evaluate crop losses by combining remote sensing and statistical sampling techniques. We conducted a simulation experiment to evaluate the losses of water-logging disaster for a summer maize field, by Landsat-8 and GF-1 remote sensing imagery, in Changqing district, Jinan City in 2013. Results indicate that the total affected areas is above 90% and the estimation accuracy of affected areas at different disaster degree is above 80%, which demonstrated that it is available for assessing the areas affected by disaster. And the proposal method reduces the cost of investigation and improves the survey efficiency by estimating the disaster degree and affected areas at the same time. However, assessment accuracy of the proposal method would be affected by imagery data, inversion index, sampling method and estimator. Thus, the practical performance using this method need to be studied in future experiments.