The identification of poverty at the county level is the precondition for poverty alleviation by formulating accurate strategies that are targeted for a certain area.Yunnan Province has the largest number of poverty counties in China.The vast number of people living under the poverty-line,and the deep degree of poverty across a wide distribution range,pose major challenges.Based on the rural poverty incidence data,this paper describes the rural poverty patterns in Yunnan Province in 2010 and 2015,and then it explores the main factors which influence the incidence and changes in rural poverty at the county level in Yunnan Province using a stepwise regression analysis method.This study found that the rural poverty in counties of Yunnan Province was deeply affected by natural conditions and the geographical environment.In 2010 and 2015,the rural poverty situation in the middle region of Yunnan Province was relatively light,while it was more serious in the northwest,northeast and south regions.The pattern of county poverty is in good agreement with the topography and landforms of Yunnan Province and the poverty-stricken areas.There are strong correlations between the incidence of rural poverty in Yunnan Province with both the annual per capita net income of rural residents and the degree of agricultural mechanization.These factors are related to the living standards and agricultural production necessary for the peasantry to sustain their livelihood.The change in the incidence of rural poverty at the county level in Yunnan Province from 2010 to 2015 is significantly correlated with changes in the value-added of the primary industries and the degree of agricultural mechanization.These correlations indicate that the development of primary industry plays a key role in the process of lifting rural residents in Yunnan Province out of poverty so they can achieve prosperity.Therefore,improving the annual per capita net income of rural residents and the degree of agricultural mechanization for rural areas in Yunnan Province a
