Abstract: Poverty is one of the common problems facing the world, hindering the Chinese economic development, social stability and environmental protection. In recent years, poverty alleviation Chinese achieved remarkable results, but for a long time in poor areas that the lack of scientific and reasonable identification method, poverty alleviation funds and the project is no problem is still more prominent. Therefore in poor areas, effective targeting and identification of poverty alleviation and development in the new period is of great significance. This paper takes 12 counties 30 economic poverty counties in Shandong province and the county economy in 30 as a sample. Firstly, through to the impoverished counties County Almanac inquiry, to determine the per capita net income of farmers as the poverty standard, Compare yearbooks to screen the indicators for poor counties and compare them in different years, selected from the marine distance, the highway mileage and the per capita grain area, new construction land area remote sensing index, determine the index weight, and then construct the evaluation model of remote sensing of poverty. The results show that the model decision coefficient is 0.5934, both significantly correlated. Evaluation of impoverished county that data analysis and remote sensing image contrast standard and evaluation analysis of poverty county were obtained correspond well with the existing poverty county based on consistent with distribution of the poor county of Shandong Province, the comprehensive consideration of poverty status and potential evaluation, a more comprehensive and in-depth.Therefore, the identification and evaluation of county poverty degree based on remote sensing is feasible. This study can provide reference for the evaluation and dynamic monitoring of the county poverty degree.