Contiguous Poverty-stricken Areas Research Articles

Dynamic Changes in Ecosystem Service Value and Ecological Compensation in Original Continuous Poverty-Stricken Areas of China

The original contiguous poverty-stricken areas of China (OCPSAC) are a regional complex with natural and human attributes. Their ecosystem services are highly complex in their contribution to human well-being. The region’s ecosystem is unstable and socio-economic development is unbalanced, making it a key area for research and the implementation of the United Nations Sustainable Development Goals. Therefore, it has become the focus of social attention. This study obtained satellite remote sensing images of the Landsat8 based on the Google Earth Engine. The dynamic characteristics of the spatial and temporal distribution of the OCPSAC’s land use changes in 2015 and 2022 were analyzed. The characteristics of the changes in ecosystem service value (ESV) were quantitatively evaluated through the revised ESV equivalent scale, and the ecological compensation (EC) standards and EC priority level suitable for the region were explored. The research results showed that: (1) the OCPSAC land use types were mainly grassland, forests, and deserts, accounting for more than 80% of the research area; (2) the OCPSAC’s ESV reached CNY 115.578 billion, and the Tibet Region (TR) and Tibetan Region of Four Provinces (TRFP) had the highest ESVs, accounting for 32.28% and 19.64%, respectively. Among individual ESVs, hydrological regulation (HR) and climate regulation (CR) had the highest values, accounting for 55.23% of the research area; (3) the ESV of the research area presented the characteristics of being high in the middle and low at both ends. From the terrain perspective, the areas with a higher ESV per unit area were distributed in the second altitude gradient, followed by China’s third altitude gradient, and the first altitude gradient was the lowest; (4) in the period of 2015–2022, the ESV increased by CNY 21.39 billion, of which TR’s ESV increased by CNY 17.44 billion. From the perspective of a single ESV, the value of waste treatment (WT), HR, nutrient cycle (NC), and provide aesthetic landscape (PAL) increased by CNY 24.38 billion; and (5) in 2022, the EC standard of the OCPSAC was CNY 917.14 billion. High-EC-value areas were mainly distributed in TR and TRFP, accounting for 72.79% of the total compensation amount, of which only TR’s EC amount exceeded a GDP of 2022, accounting for 4.77% of the total compensation. The purpose of this study was to provide a reference for ecosystem sustainability and EC.

Spatial Identification and Distribution Pattern of the Complexity of Rural Poverty in China Using Multisource Spatial Data

Regional poverty is one of the most serious challenges facing the world today. Poverty, antipoverty, and poverty alleviation are the focus of the attention of scholars and the public. This paper takes China’s counties as the research unit, selects the influencing factors of poverty from natural and socio-economic factors, establishes an evaluation index system, simulates the natural poverty index and socio-economic poverty eradication index of each county, and clarifies the distribution characteristics of spatial poverty using GIS spatial analysis and BP artificial neural network. The results indicate that natural factors are the main cause of poverty in Chinese counties, with 710 counties having a high natural poverty index, accounting for nearly 30% of the total number of counties in the country. The national county-level natural poverty index shows a clear strip distribution pattern along latitude and longitude, with a strip distribution from north to south and from west to east; socio-economic factors have played a certain role in poverty alleviation, with as many as 1521 counties with low socio-economic poverty alleviation indices, accounting for approximately 64% of the total number of counties in the country. The spatial distribution of the county-level socio-economic poverty alleviation index is relatively fragmented. Through spatial scanning statistics, a total of 44 county poverty pressure index risk clusters reached a statistical significance level, involving 243 counties and districts. In poverty reduction practice, the internal counties and districts of contiguous poverty-stricken areas should strengthen cooperation and exchange. In the process of poverty alleviation and development, targeted poverty alleviation and economic development should be carried out based on the poverty-dominant type and self-development ability of the county, in order to improve efficiency. Regions that are relatively prosperous and have taken the lead in poverty reduction should play a leading and exemplary role in strengthening the radiation power of regional central cities. The prominent feature of this study is the comprehensive utilization of multisource data and the use of new spatial analysis methods (flexible spatial scanning method is widely used in the field of infectious disease prevention and control research). By constructing a multidimensional poverty measurement system that includes natural and social factors, it distinguishes the differences between the factors that cause poverty and the factors that eliminate poverty in regional poverty. At the same time, the flexible spatial scanning detection method was used to detect the differentiation mechanism of poverty spatial patterns.

The impact of poverty alleviation policy on the industrial structure: Evidence from the Qinba Mountain contiguous poverty-stricken areas

In 2015, the Chinese government issued the Decision on Poverty Alleviation(DPA), requiring poverty-stricken areas to develop local characteristic industries based on their resource endowments, to promote industrial structure diversification and industrial structure upgrading through industry-driven poverty alleviation. However, existing research lacks empirical analysis to evaluate it. Therefore, this paper takes poor counties in the Qinba Mountain contiguous poverty-stricken areas(QMCPA) as an example, using the difference in difference model and boundary effect model to evaluate whether DPA has promoted industrial structure upgrading and industrial structure diversification in poor counties. The results show that the DPA has promoted industrial structure upgrading and improved industrial structure diversification in the QMCPA. However, the effectiveness of it is not sufficient. Poor counties have failed to maintain the policy requirement of developing characteristic industries based on local natural resource endowments, leading to a decline in the degree of industrial structure diversification in the later period of the policy. This study indicates that local governments should strive to develop advantageous industries and form a division of labor and cooperation with neighboring areas, strengthen inter-regional cooperation and contact, and enhance anti-risk capabilities to avoid homogenized competition. Studying the changes in industrial structure in the QMCPA has important significance for the long-term stable development and poverty elimination of various poor areas.

Does opportunity co-creation help the poor entrepreneurs? Evidence from China.

Extreme poverty can be alleviated through entrepreneurship, but starting a business can be elusive among impoverished people, partly due to a lack of access to entrepreneurial opportunities. In the current literature, the source of entrepreneurial opportunity for the poor remains unclear. To address this knowledge gap, we used the opportunity co-creation perspective to examine the impact of opportunity co-creation on the entrepreneurial performance of the poor and its various influence pathways. We developed a chain multiple mediation model and surveyed 330 poor entrepreneurs from the Wuling Mountain Region, which used to be one of the 14 contiguous poverty-stricken areas in China until the end of 2020 when the country announced the eradication of extreme poverty. Data analysis was done using structural equation modeling (SEM). The results suggest that opportunity co-creation has a direct positive effect on the entrepreneurial performance of the poor and an indirect positive effect through the chain mediating effect of opportunity beliefs and entrepreneurial behavior. The findings confirm that opportunity co-creation is a critical factor for entrepreneurs in poor areas to overcome the lack of entrepreneurial opportunities and can also contribute to a better understanding of opportunity beliefs and entrepreneurial behavior. Furthermore, these results have important implications for poor entrepreneurs and provide opportunity co-creation solutions for poverty reduction through entrepreneurship.

How to break the environment-economic trap in rocky desertification contiguous poverty-stricken areas: the mediating effect of industrial structure upgrading

ABSTRACT The vicious cycle between economy and environment is a key issue affecting the sustainable development of poverty-stricken areas, and how to break the environment-economic trap in poverty-stricken areas is a hot topic concerned globally. Therefore, this study uses county data from 2011–2019 of Yunnan-Guizhou-Guangxi rocky desertification contiguous poverty-stricken areas, and investigates the correlation and mechanism among industrial structure, ecological environment and economic growth in poverty-stricken areas based on the fixed effect model and the mediating effect model. The results show that there is a significant contradictory relationship between environmental protection and economic growth in the Yunnan-Guizhou-Guangxi rocky desertification contiguous poverty-stricken areas, while the industrial structure upgrading can alleviate the contradictory relationship. The mode of developing characteristic industries based on ecological resource endowment and then promoting economic growth can more effectively solve the contradiction between environmental protection and economic growth, which is conducive to breaking the environment-economic trap in poverty-stricken areas. This study provides a reference for the development of other poverty-stricken areas in the world, and also provides experience for promoting poverty reduction and sustainable development in the world.

Spatiotemporal Evolution and Socioeconomic Impacts of Rainstorms and Droughts in Contiguous Poverty-Stricken Areas of China

To consolidate the achievements in the elimination of absolute poverty in China and prevent rural populations from returning to poverty as a result of meteorological disasters, this study analyzed the spatiotemporal characteristics of rainstorms and droughts and their socioeconomic impacts on China’s contiguous poverty-stricken areas (CPSAs) from 1984 to 2019. The annual number of rainstorms and drought days in CPSAs of China reached approximately 1.9 days/year and 44.6 days/year, respectively. It gradually decreased from southeast to northwest. Rainstorms showed a significant increasing trend of 0.075 days/decade, while there is no significant trend in drought days. Due to rainstorms and droughts, the average annual number of people affected and direct economic losses in CPSAs reached 34 million people/year and 29 billion Chinese yuan/year, accounting for 22.9% and 12.6% of China’s total amounts, respectively. The average annual loss rate due to disasters in this region reached 1.6%, which is 0.6% higher than the national level. Furthermore, the distinct features and socioeconomic impacts of rainstorms and droughts were identified on the southeastern and northwestern sides of the population density line (PDL) along Tengchong-Aihui in China. Droughts have often impacted the regions located along the PDL, while rainstorms and droughts have occurred more frequently in the regions to the southeast of the PDL than in the regions to the northwest of the PDL. As a result, the affected population and direct economic losses due to rainstorms and droughts in the regions to the southeast of the PDL were 8.8 and 9.2 times and 3.3 and 7.4 times higher, respectively, than those in the regions on the other side of the PDL. Although the losses were greater, the disaster resistance capabilities were significantly improved in these regions. In contrast, the regions to the northwest side of the PDL exhibited a significant increasing trend in losses with a relatively low disaster resistance capabilities. This study revealed that it is necessary to improve the capability of meteorological disaster prevention and reduction in China’s CPSAs, especially in the regions to the west of the PDL, which could further contribute to the realization of United Nations Sustainable Development Goals.

Spatial Differentiation and Influencing Factors of Poverty Alleviation Performance Under the Background of Sustainable Development: A Case Study of Contiguous Destitute Areas in Hunan Province, China.

Poverty eradication is a realistic requirement for the addressing of the urban-rural development imbalance. It consolidates the achievements of the poverty alleviation, and accelerates the realization of the United Nations Sustainable Development Goals. In research that deals with poverty, qualitative analysis is often used to study the connection between a single influencing factor and poverty reduction, and to solve regional poverty through government measures. However, these studies usually ignore the multidimensional nature of poverty, and the fact that poverty alleviation also needs to be approached from multiple perspectives. By constructing a theoretical framework of poverty alleviation performance from the perspective of sustainable development, this study selects contiguous poverty-stricken areas in the Hunan Province, China as the empirical study area, constructs an evaluation index system from the three dimensions of economic development, infrastructure and people’s livelihood security, and selects influencing factors from three aspects of ‘population’, ‘land’ and ‘industry’. The spatial differentiation characteristics and influencing factors of poverty alleviation performance in poverty-stricken areas were studied by using the methods of entropy weight method and geodetector. The results show: firstly, in the concentrated and contiguous poverty-stricken areas of the Hunan Province, the performance of poverty alleviation in the economic development makes little difference, showing a ‘high-medium-low’ cross-distribution pattern. The poverty alleviation performance of the infrastructure presents a distribution pattern of ‘low in the middle and high on both sides. The poverty alleviation performance of people’s livelihood security has significant spatial differentiation characteristics, which all present a reunion distribution. The overall poverty alleviation performance varies greatly, showing a funnel-shaped distribution in space. Secondly, the spatial differentiation of poverty alleviation performance in the concentrated and contiguous poverty-stricken areas of the Hunan Province is the result of the combined effects of multiple factors. ‘Population’ is the dominant factor affecting the performance of poverty alleviation, ‘land’ is the basic factor that causes the spatial differentiation of poverty alleviation performance, and ‘industry’ is the key factor for the improvement of the poverty alleviation ability.

Research on the Impact of Green Development on Poverty Alleviation：Based on the Comparative Analysis of Concentrated and Contiguous Poverty-stricken Areas and Non-concentrated and Non-contiguous Poverty-stricken Areas in China

Concentrated and contiguous poverty-stricken areas（CCPAs）are the main battlefield of poverty alleviation in China. Green development is an important measure of targeted poverty alleviation in China. How green development can promote poverty alleviation in CCPAs is related to the policy trend of China’s future modernization.This paper provides a comparative analysis for the CCPA group and the non-concentrated and non-contiguous poverty-stricken area（NNPA）group based on the 2001-2007 panel data of 284 prefectural-level cities constituted by CCPAs and NNPAs. And we refer the sustainable development livelihood framework to study the poverty alleviation effect and mechanism of green development. Furthermore, this paper chooses two variables, the air ventilation coefficient and the word frequency of green development in the government working report, as the instrumental variable（IV）for green development, which in turn allows us to estimate the influence of green development on poverty alleviation in the econometric framework of two-stage OLS（2SLS）.The results indicate that: （1）The impact of green development on poverty alleviation in both CCPAs and NNPAs is marked by an inverted U-shaped curve. However, compared with NNPAs, both the effect of green poverty alleviation and the effect of transformation are more significant in CCPAs.（2）Green development affects poverty alleviation mainly through the knowledge spillover effect in both CCPAs and NNPAs, indicating that the green-led education poverty alleviation can directly affect the poor, which is an important measure to promote poverty alleviation.（3）We find a significantly diminishing marginal effect between knowledge spillover effect and poverty alleviation, but the diminishing marginal effect in CCPAs is more obvious than that in NNPAs. The results imply that the government should continue to increase investment in education in CCPAs and NNPAs, and connect green poverty alleviation with the strategy of rural vitalization efficiently in the post-poverty alleviation period, leading to the modernization of China. This paper contributes to the literature in the following two ways. First, this paper focuses the research objects of poverty alleviation on CCPAs, highlighting the uniqueness of China’s poverty problem. Second, we take the air ventilation coefficient and the word frequency of green development in government working report as instrumental variables of green development to further control for the endogeneity problem and obtain robust results．

Identification of Poverty Areas by Remote Sensing and Machine Learning: A Case Study in Guizhou, Southwest China

As an objective social phenomenon, poverty has accompanied the vicissitudes of human society, which is a chronic dilemma hindering human civilization. Remote sensing data, such as nighttime lights imagery, provides abundant poverty-related information that can be related to poverty. However, it may be insufficient to rely merely on nighttime lights data, because poverty is a comprehensive problem, and poverty identification may be affected by topography, especially in some developing countries or regions where agriculture accounts for a large proportion. Therefore, some geographical features may be necessary for supplements. With the support of the random forest machine learning method, we extracted 23 spatial features base on remote sensing including nighttime lights data and geographical data, and carried out the poverty identification in Guizhou Province, China, since 2012. Compared with the identifications using support vector machines and the artificial neural network, random forest showed a better accuracy. The results supported that nighttime lights and geographical features are better than those only by nighttime lights features. From 2012 to 2019, the identified poor counties in Guizhou Province showed obvious dynamic spatiotemporal characteristics. The number of poor counties has decreased consistently and contiguous poverty-stricken areas have fragmented; the number of poor counties in the northeast and southwest regions decreased faster than other areas. The reduction in poverty probability exhibited a pattern of spreading from the central and northern regions to the periphery parts. The poverty reduction was relatively slow in areas with large slope and large topographic relief. When poor counties are adjacent to more non-poor counties, they can get rid of poverty easier. This study provides a method for feature selection and recognition of poor counties by remote sensing images and offers new insights into poverty identification and regional sustainable development for other developing countries and areas.

The Coupling Relationship Between Economic Poverty Alleviation and Ecological Poverty Alleviation in Concentrated and Contiguous Poverty-stricken Areas: Take Yunnan Province as an Example

The coupling and coordinated development of economic poverty alleviation and ecological poverty alleviation is an important strategy for poverty alleviation development in the new era. It is the basis for achieving the goal that all people get rid of poverty in 2020 and entering a well-off society together. Taking concentrated and contiguous poverty-stricken areas in Yunnan Province of China as the target research objective, the Entropy Method is used to evaluate the performance of economic, social, human settlement and ecological poverty alleviation. Then, the coupling harmonious degree model is selected to explore the correlation, consistency and coordination between economic poverty alleviation and ecological poverty alleviation. The results shows that: (1) The overall poverty alleviation performance is at a low-middle level, and the poverty alleviation performance in Tibetan inhabited area is the only one that ranks in the upper middle level, among the four regions of Yunnan. (2) The degree of coupling in Yunnan and the 4 regions is relatively high, basically in a highly coupled stage, but the degree of coupling harmonious is low, especially in the Wumeng Mountainous area. According to the conclusion, it is proposed to promote regional development and the economic and ecological coupling development through the optimization of the utilization and allocation of poverty alleviation resources, the appropriate tilt of poverty alleviation policies to areas with low performance and coupling harmonious, and the enhancement of the value of ecological services in Tibetan inhabited area.

Rural households’ livelihood responses to industry-based poverty alleviation as a sustainable route out of poverty

Industrialization is one way to achieve a sustainable route out of poverty. During the implementation of industry-based poverty alleviation projects, rural households’ livelihood responses to change are crucial. A stronger livelihood response is conducive to multidimensional poverty relief due to industry-based poverty alleviation projects. Effective poverty alleviation can also stimulate stronger household responses. There is a positive cycle between livelihood response and multidimensional poverty relief effects that can help achieve sustainable poverty alleviation goals. Using a synergistic perspective on the relationship between “people–industry–land”, this paper explains the poverty alleviation logic connecting livelihood response, multidimensional poverty relief, and sustainable routes out of poverty by constructing a four-dimensional livelihood response measurement system with three elements of intensity. We analyzed survey data collected from 2363 households from 4 sample counties in 4 contiguous poverty-stricken areas, and measured and compared the characteristics of rural households’ livelihood responses and the factors influencing poverty alleviation projects. Rural households’ livelihood responses in four sample counties were moderate. The four dimensions of responses were ranked as livelihood strategy response, livelihood space response, livelihood output response, and livelihood capital response. The three intensities indicated that the perception and willingness elements of livelihood response were very similar, but there was a big gap between those elements and livelihood response actions. At the group level, poor households had higher and more consistent livelihood response than non-poor households. External environment factors (such as location, industry type, village organizational ability, and village atmosphere) and internal family factors (such as resource endowment, income sources, health, education, labor quantity, policy trust, credit availability, and social networks) had a significant impact on households’ livelihood response. However, this impact varied across different dimensions and had different intensities. This paper proposes a multidimensional poverty relief mechanism and suggests sustainable routes out of poverty.

Sizing Up Transport Poverty Alleviation: A Structural Equation Modeling Empirical Analysis

The aim of this paper was to systematically obtain the poverty reduction effects and diversified poverty alleviation paths of road infrastructure, to assist in the planning of transport poverty alleviation and rural revitalization in the concentrated contiguous poverty-stricken areas. The measurement methods for impact effects and paths of transport poverty alleviation have been scientifically proposed based on methods of transportation economics and transportation geography. Firstly, an overview of the interactive mechanism and processes by which road infrastructure investment influences poverty reduction has been offered, and the characteristics of poverty space and spatial coupling result of road infrastructure have been systematically obtained. The results show that about 70% of the district counties’ road infrastructure and poverty rate are in a state of spatial coupling imbalance; the coordinated synchronous type is mainly distributed along the road network. Secondly, the structural equation model system has been formulated with variables that reflect transportation input in adjacent geographical units to consider spatial spillover effects. The results show that the direct poverty reduction effect of road infrastructure (0.105) is much lower than the indirect poverty reduction effect (0.830). Thirdly, empirical analysis at regional level of the concentrated contiguous poverty-stricken areas in China has been conducted. As a result, while addressing the limitations of previous studies, the poverty alleviation path that has been proposed also aims to catalyze actions to reduce the transport-related exclusion in poverty-stricken areas caused by the lack of access to basic facilities.

Comprehensive evaluation of modern agricultural development level in contiguous destitute area of Lvliang Mountain, Shanxi Province

<p class="NOTENormal">An evaluation model was established using a combination of AHP and multi-objective linear weighted function methods to comprehensively evaluate the development level of modern agriculture in the contiguous poverty-stricken areas of Lvliang Mountain in Shanxi Province. The results show that: (1) As a whole, the contiguous poverty-stricken areas have a low degree of agricultural modernization and are in the initial stage of development. The degree of modernization of agricultural production conditions, agricultural production results, and farmers’ living standards is gradually decreasing; at the municipal level, the degree of agricultural modernization in the three cities is the same. Not high, the order is Xinzhou City > Linfen City > Lvliang City; at the county level, the degree of agricultural modernization varies greatly. The counties in Xinzhou City are in the high-level sub-stage of the initial stage, and the counties in Lvliang City are in the low-level sub-stage of the initial stage. The overall degree of agricultural modernization in counties shows a spatial pattern of low in the middle and high in the north and south; (2) The contributions of agricultural production conditions, production results and farmers’ living standards to modern agriculture are 16.4%, 29.7% and 53.9% respectively. The low level of agricultural electrification and mechanization and backward production conditions are bottlenecks in the development of modern agriculture. The backward agricultural production conditions lead to inefficient production results, low disposable income of farmers, and low living standards of farmers, which are the root causes of the slow development of modern agriculture in the region.</p>

Measurement of economic resilience of contiguous poverty-stricken areas in China and influencing factor analysis

Measurement of economic resilience of contiguous poverty-stricken areas in China and influencing factor analysis

Can Government Financial Inflows Effectively Reduce Poverty in Poverty-Stricken Areas? Evidence from China

ABSTRACT Financial assistance has been found to be an important way to help lift people out of poverty, both theoretically and empirically. However, its effective functioning depends on certain basic conditions. Currently, contiguous poverty-stricken areas, the main areas where impoverished communities live in China, are the main battlefield for poverty alleviation. The Chinese government attaches great importance to the effective functioning of rural finance as a tool to combat poverty in these areas and has invested sizable financial resources. However, the actual impact on rural households of financial infusions has not been analyzed. This article sheds empirical light on the issue using data from a survey of rural households in such areas. The results show that the formal financial transfers from the government and informal finance do not effectively reduce poverty there. Rather, they increase income inequality among households. Nonetheless, cultivation of the human capital, material resources, and social capital of rural households plays a positive role in reducing poverty. Thus, our conclusions may be helpful for adjusting rural financial policies in these areas so as to reduce poverty among those who live there.

Monitoring the spatiotemporal dynamics of poor counties in China: Implications for global sustainable development goals

Poverty remains one of the long-term chronic dilemmas facing the sustainable development of human society during the 21st century. The spatiotemporal dynamics of poor regions, particularly in developing countries, is crucial for realizing fundamental sustainable development goals (SDGs). For decades, many scholars have sought to accurately measure, identify and alleviate poverty at different geographical scales. However, reliable data about the estimation of poverty remain scarce for developing countries, hindering efforts to accurately identify poverty. This paper utilizes the Defense Meteorological Satellite Program Operational Linescan System (DMSP/OLS) sensor nighttime light imagery to identify poor counties in China from 1992 to 2013. Using 16 statistical and spatial features extracted from this nighttime light imagery and using 96 poor counties and 96 nonpoor counties from 2010 as the classification sample, we describe the spatiotemporal dynamics of poor counties based on a random forests approach. Our study finds that the number of poor counties is decreasing in a fluctuating pattern and that contiguous poverty-stricken areas are becoming fragmented. The reduction in poor counties exhibits a manner of moving horizontally from the eastern regions to the central and western parts of China, while the number of poor counties in the central and western regions has decreased around the central cities or areas. The Aihui-Tengchong Line is not the dividing line in the distribution of poor counties in China, which means that China's poor can also be found in areas with relatively high population density. Together, the findings reveal that the key to reducing regional poverty is the development of regional economies and the implementation of national macro policies. This paper provides references for formulating antipoverty strategies for each county and offers new insights into poverty estimation and regional sustainable development for other developing countries.

Village-level multidimensional poverty measurement in China: Where and how

Village is an important implementation unit of national poverty alleviation and development strategies of rural China, and identifying the poverty degree, poverty type and poverty contributing factors of each poverty-stricken village is the precondition and guarantee of taking targeted measures in poverty alleviation strategies of China. To respond it, we construct a village-level multidimensional poverty measuring model, and use indicator contribution degree indices and linear regression method to explore poverty factors, while adopting Least Square Error (LSE) model and spatial econometric analysis model to identify the villages’ poverty types and poverty difference. The case study shows that: (1) Spatially, there is obvious territoriality in the distribution of poverty-stricken villages, and the poverty-stricken villages are concentrated in contiguous poverty-stricken areas. The areas with the highest VPI, in a descending order, are Gansu, Yunnan, Guizhou, Guangxi, Hunan, Qinghai, Sichuan, and Xinjiang. (2) The main factors contributing to the poverty of poverty-stricken villages in rural China include road construction, terrain type, frequency of natural disasters, per capita net income, labor force ratio, and cultural quality of labor force. The main causes of poverty include underdeveloped road construction conditions, frequent natural disasters, low level of income, and labor conditions. (3) Chinese poverty-stricken villages include six main subtypes, and most poverty-stricken villages are affected by multiple poverty-forming factors, reflected by a relatively high proportion of the three-factor dominant type, four-factor coordinative type, and five-factor combinative type. (4) There exist significant poverty differences in terms of geographical location and policy support, and the governments still need to carry out targeted poverty alleviation measures according to local conditions. The research can not only draw a macro overall poverty-reduction outline of impoverished villages in China, but also depict the specific poverty characteristics of each village, helping the government departments of poverty alleviation at all levels to mobilize all kinds of anti-poverty resources.

Assessment of Sustainable Livelihood and Geographic Detection of Settlement Sites in Ethnically Contiguous Poverty-Stricken Areas in the Aba Prefecture, China

The Chinese government aims to deal with poverty by 2020 for people living in ethnic and rural regions, including mountainous ethnic regions with the highest concentration of poverty and chronic poverty. Based on a sustainable livelihood Framework, five capitals and 33 evaluation indices of livelihood were built, and 13 counties’ resources of the Aba Tibetan and Qiang Autonomous Prefecture were compared in order to calculate the degree of poverty. Topographic factors index of settlement sites (TFIS) were constructed by eight topographic factors, and diagnoses of the dominant factors of differentiation of 2699 settlements were calculated by using the geographical detector model to establish the poverty alleviation policies and models for different regions. The results showed that the livelihood capital evaluation indices were different (0.56–1.88), and natural capitals (mean value 1.56) had obvious advantages, but physical (mean value 0.56), financial (mean value 0.78), and human capital were lower (mean value 0.93), limiting the rate of transforming the ecological resources advantage into the economy. In the TFIS, the settlement points indicate topographic factors of natural breakpoint classification superposition, including elevation, slope, relief amplitude, surface incision, variance coefficient in elevation, surface roughness, distance to roads, and distance to rivers. These are within the 8–34 range, and their power determinant value to TFIS are 0.02, 0.70, 0.77, 0.76, 0.51, 0.66, 0.06, and 0.09. Livelihood capital evaluation indices and TFIS classification one (8–14) are positively correlated, and negative correlation (22–26 and 27–34) is at the 0.05 level. The county's poverty alleviation measures and development under different livelihood indices and TFIS indicate that the ecotourism industry has become the inevitable choice for promoting rapid and coordinated development of economy, society, and the environment in ethnic regions.

Research on the Integration Mode, Problems and Solutions of Educational and Knowledge Poverty Alleviation in Contiguous Poverty - Stricken Areas ─ A Case Study of Lvliang Mountain Area

Education poverty alleviation is an endogenous mechanism to explore poverty alleviation in contiguous poverty-stricken areas, which is an important support for the implementation of precision poverty alleviation strategy, and it is the key path to change “blood transfusion poverty alleviation” as “hematopoietic poverty alleviation”. It is of great significance to solve employment, stimulate economic growth and promote the income of poor households. Lvliang mountain area is the famous old revolutionary base in China, and it is one of the fourteen contiguous poverty-stricken areas that the country focus on poverty alleviation during the 13th five-year plan, accounting for one-third of the total number of poor people in Shanxi. To promote education and knowledge poverty alleviation and get out of poverty, it not only need to make full use of the power of culture and the means of knowledge to implement the knowledge poverty alleviation project, achieving the goal of “taking the lead in poverty alleviation and taking the lead to get rich”. And it also need to work closely with governments at all levels and the people in the poverty-stricken areas to combine the top-level design and concrete measures.