## 1 Introduction
These methods mainly focus on the assessment of the number of casualties after the earthquake, and most of the assessment units are at the municipal level, which cannot effectively reflect the regional differences in the distribution of buried personnel and the identification of key areas. So, the assessment method based on the population kilometer grid is widely used. [PERSON] [18] gave a preliminary method for calculating the number of trapped people in a kilometer grid by fully considering the factors affecting the buried people. [PERSON] et al. [19] programmed and optimized [PERSON]'s equation, and the evaluation results analyzed by arithmetic cases can identify where the key areas of buried people are. [PERSON] et al. [20] combined the kilometer grid data of the Gansu Province with localized parameter improvement for the earthquake formula. The applicability of the pressure buried personnel distribution assessment method for Gansu area was improved. [PERSON] et al. [21] established a model for the number of people buried by earthquakes based on the grid and high-precision house data for the Ludian and Yiliang earthquakes in the Yunnan Province as an example. [PERSON] et al. [22] proposed a method to assess the number of buried people due to building collapse in an earthquake disaster by combining the estimation model of earthquake casualties with the assessment unit of township residential land. [PERSON] et al. [23] established an assessment model for the number of people trapped in collapsed buildings in an earthquake to show the distribution in a kilometer grid distribution as an example of the Ludian earthquake and verified the accuracy of the assessment results. There have been many studies related to people who are trapped in Table 1, but the existing studies have limitations: (1) The requirement of data in most methods involve a wide range of information and data. These data are costly to obtain and slow to update. Moreover, the lack of such basic data in the currently available emergency database makes the applicability of existing methods insufficient. (2) Existing models that can be used directly are more conducive to estimating the overall casualty situation in the region. Although the km grid method is more refined for personnel buried pressure prediction,with the development of sensors in aerospace technology and the increasing demand for emergency efficiency, a more refined personnel buried pressure model can be attempted to be constructed, forming the rough prediction of the overall number of people buried pressure in a large range, the prediction of personnel buried pressure in km grid scale, and then the prediction of personnel buried pressure in fine individual buildings. Therefore, this paper proposes an evaluation model of earthquake-trapped personnel using remote sensing images, UAV images, and multi-source geographic data through the simulation of population distribution, the construction of personnel in the indoor population rate, and the degree of building damage after the earthquake to analyze the key rescue areas for emergency rescue work. Finally, this paper uses the town of Moxi, the epicenter of the recent earthquake in Luding, Sichuan, as a case study for experiment and analysis.