It is of great significance to clarify the spatiotemporal pattern of population distribution and its influential mechanism.This can improve the understanding of the humanearth relationship.Moreover, the sustainable development of population, resources and environment can be realized.QinlingBashan Mountain areas, one of the concentrated contiguous destitute areas announced by the state, was taken as an example.On the basic unit of county, the degree of influence of transport elements on the spatial distribution of population was quantitatively revealed by virtue of spatial analysis technology and spatial panel Durbin model. The results show that the population of QinlingBashan Mountain areas has obvious characteristics of spatial differentiation, showing an overall pattern of “large outside and small inside, more in the south and less in the north”. In addition, the number of permanent residents in QinlingBashan Mountain areas from 2000 to 2015 shows an overall decrease tread, especially in peripheral areas. The spatiotemporal pattern of population distribution in QinlingBashan Mountain areas is jointly affected by temperature, terrain fluctuation, distance to the provincial capital and other mega cities, county financial expenditure, county fixed assets investment, GDP and other factors. Both highway accessibility and railway accessibility have obvious positive direct effects on population distribution. For every 1% increase in road accessibility and railway accessibility in the study area, the population will increase by 1.96% and 1.91%, respectively.Highway accessibility also has an indirect spatial spillover effect on population distribution. Every 1% increase in highway accessibility in neighboring counties will increase the local population by 1.58%.

Based on the perspective of evolution with road transport, the influence mechanism of economic growth in povertystricken counties of Fujian province is analyzed. Firstly,the evolution of connectivity degree and transport superiority degree of povertystricken counties in Fujian province are measured, then the production function model containing transport superiority degree is built to explore the influences of transport superiority degree on economic growth from 2000 to 2016. The results show that the transport superiority degree of designated poor counties in Fujian province is at an overall disadvantage, and the transport superiority degree of most povertystricken counties is inferior than the provincial average.The effect of transport superiority degree of povertystricken counties in Fujian province on economic growth is very slight and insignificant.The growth of fixed asset investment and total population are beneficial to the economic growth, and the influence of degree of topographic relief is small, with changing from negative significance to insignificance.

As an important battlefield of national poverty alleviation, QinlingBashan Mountain is a representative area among the contiguous destitute areas in China. In the new stage of solving the problem of relative poverty, it is of great theoretical and practical significance to explore the temporal and spatial characteristics and influencing factors of nonagricultural employment in QinlingBashan Mountain areas. Results show that the spatial distribution of nonagricultural employment in QinlingBashan Mountain areas was extremely uneven. Since the implementation of the targeted poverty alleviation strategy, the overall employment growth of QinlingBashan Mountain areas has been obviously faster than the average level of contiguous destitute areas in China, but the growth trend of counties varies greatly. The border area between Henan, Shaanxi and Hubei province was the hot spot for the increase of nonfarm employment. There was a strong spatial dependence among counties in QinlingBashan Mountain areas, and the nonagricultural employment growth of neighboring counties had a positive spillover effect on the nonagricultural employment growth of the county. Initial employment scale, economic growth, social development, geographical and market location factors all affected the nonagricultural employment growth in QinlingBashan Mountain areas. Initial nonfarm payrolls suppressed nonfarm employment growth. Local government expenditure, health care, accessibility to cities and flat terrain conditions significantly contributed to nonfarm employment growth. Finally, from the perspective of promoting the growth of nonagricultural employment in contiguous destitute areas, the corresponding policy recommendations were put forward.

Rural housing construction is an important measure for rural development and rural revitalization. Clarifying the relationship between rural housing costs and farmers′ poverty, and exploring the poverty reduction effect and path of farmers′ housing costs are helpful to the smooth progress of rural development and rural revitalization strategies. Based on the survey data of households in Hanyin county, Qinba Mountain area in 2019, using Probit model, the impact of rural housing cost on household poverty and the poverty reduction effect of housing cost were discussed. The research found that: (1) The cost of rural housing construction in Hanyin county is about 110 000 yuan/household, of which the average government subsidy for rural housing construction is about 90 000 yuan/household, and the average outofpocket housing expenditure of farmers is 20 000 yuan/household. (2) The incidence of absolute poverty in rural areas has been greatly reduced, but the phenomenon of relative poverty is still serious. Lack of funds and poor transportation conditions are the main causes of poverty among farmers in poor mountainous areas. (3) Farmers′ housing cost affects family poverty, and farmers′ outofpocket housing expenditure has a significant impact on family poverty. Reducing farmers′ housing costs and increasing government subsidies for rural housing construction will help reduce the incidence and depth of rural poverty.

Revealing the relationship between health care and poverty is an important content to explore the phenomenon of poverty and returning to poverty caused by illness. The medical resources index and medical facility accessibility of 677 counties in concentrated contiguous severe poverty areas from 2008 to 2017 were measured. Based on the analysis of spatiotemporal evolution characteristics of poverty and health care accessibility, the impact of health care accessibility on poverty was analyzed by using spatial error model. The results showed that the poverty in the concentrated contiguous severe poverty areas presented a fluctuant increasing characteristic, and it had significant spatial agglomeration. The spatial difference of poverty showed a phased characteristic of basically stable in the early stage and rapid increased in the late stage.The pattern of medical resources index changed from low in whole to high in the southeast and low in the northwest of Hu Line, and the medical facility accessibility has changed from a relatively balanced distribution to the pattern of low value.Health care accessibility can effectively reduce the level of poverty. Every 1% increase in medical resources index of counties in the povertystricken areas will produce a poverty reduction of 0.006%. Every 1% increase in medical facility accessibility will produce a poverty reduction of 0.133%.The impact of health care accessibility on different levels of poverty is heterogeneous. Compared to low poverty, the medical resources index has better propoverty. By 2017, every 1% increase in medical resources index will produce a poverty reduction of 0.047% in low poverty areas, and 0.353% in high poverty areas. Medical facility accessibility only has a certain poverty reduction effect on low poverty. By 2017, every 1% increase in medical facility accessibility will produce a poverty reduction of 0.083%. By increasing the number of health technical personnel to improve the medical resources index, the poverty reduction effect of counties in the povertystricken areas can be improved, especially in high poverty areas. Moreover, improving the convenience of treatment has a greater effect on poverty reduction than medical resources index, but it is limited in low poverty areas.