Journal of Geographical Sciences ›› 2018, Vol. 28 ›› Issue (12): 1810-1824.doi: 10.1007/s11442-018-1580-z
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Yuanzhi GUO1,2,3(), Yang ZHOU1,2, Zhi CAO1,2,*(
)
Received:
2018-05-10
Accepted:
2018-08-01
Online:
2018-12-20
Published:
2018-12-20
Contact:
Zhi CAO
E-mail:guoyz.16b@igsnrr.ac.cn;caoz.14b@igsnrr.ac.cn
About author:
Author: Guo Yuanzhi (1990-), PhD, specialized in urban-rural development and poverty geography. E-mail:
Supported by:
Yuanzhi GUO, Yang ZHOU, Zhi CAO. Geographical patterns and anti-poverty targeting post-2020 in China[J].Journal of Geographical Sciences, 2018, 28(12): 1810-1824.
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Table 1
An indicator system for comprehensive poverty level in rural China"
Dimension | Indicator | Description |
---|---|---|
HDA | A1: Educational attainment | Average educational attainment of people aged six and above |
A2: Labor force | Proportion of population aged 15-64 / Total population | |
A3: Minority nationality | Proportion of the population of national minorities / Total population | |
SED | B1: Per capita gross domestic product (GDP) | GDP / Total population |
B2: Per capita public budget revenue | General public budget revenue / Total population | |
B3: Per capita disposable income of rural residents | Income of rural households after initial distribution and redistribution | |
B4: Number of beds in health institutions | Including individually-run clinics | |
B5: Child survival | Number of live babies / Total live births | |
B6: Urbanization rate | Urban population / Total population | |
B7: Per capita living space | The average residential area owned by each person | |
B8: Road density | Total road length / Total area | |
NRE | C1: Altitude | The average raster value in each county |
C2: Slope | Proportion of areas at more than 15 degrees of slope | |
C3: Degree of fragmentation | Standard deviation (SD) of county raster value | |
C4: Annual rainfall | Annual rainfall across counties in 2015 | |
C5: Per capita arable land | Including paddy fields and dryland | |
C6: Net primary productivity (NPP) | Obtained using a GLO_PEM model ( | |
C7: Farmland production potential (FPP) | Calculated using a GAEZ model ( |
Table 2
Pearson correlation coefficient analysis of selected indicators and incidence of poverty"
Indicator | Correlation | Sig. | Indicator | Correlation | Sig. | Indicator | Correlation | Sig. |
---|---|---|---|---|---|---|---|---|
A1 | -0.194 | 0.000 | B4 | -0.277 | 0.000 | C2 | 0.261 | 0.000 |
A2 | -0.173 | 0.006 | B5 | -0.158 | 0.000 | C3 | 0.230 | 0.000 |
A3 | 0.227 | 0.000 | B6 | -0.345 | 0.000 | C4 | -0.059 | 0.150 |
B1 | -0.362 | 0.000 | B7 | -0.226 | 0.000 | C5 | -0.124 | 0.003 |
B2 | -0.075 | 0.069 | B8 | -0.149 | 0.000 | C6 | -0.131 | 0.001 |
B3 | -0.644 | 0.000 | C1 | 0.272 | 0.000 | C7 | -0.359 | 0.000 |
Table 3
CPLs in contiguous poor areas with difficulties"
DBMA | SGKR | RDA | BMA | LPMA | LXMA | LLMA | QBMA | |
---|---|---|---|---|---|---|---|---|
HDI | 8.96 | 11.8 | 3.52 | 7.78 | 9.95 | 8.24 | 13.02 | 11.68 |
REI | 11.23 | 9.06 | 9.74 | 7.87 | 7.22 | 10.52 | 8.16 | 6.82 |
SEI | 8.43 | 7.45 | 6.50 | 5.19 | 5.38 | 8.14 | 6.52 | 7.76 |
CPL | 28.62 | 28.31 | 19.76 | 20.84 | 22.55 | 26.89 | 27.7 | 26.26 |
TAFP | TPSX | YTMA | WMMA | WLMA | Tibet | CPADs | China | |
HDI | 5.96 | 4.39 | 10.75 | 4.66 | 5.57 | 4.87 | 7.38 | 11.04 |
REI | 4.00 | 5.76 | 7.76 | 6.66 | 9.72 | 3.78 | 7.39 | 9.56 |
SEI | 6.85 | 3.83 | 6.83 | 5.04 | 7.84 | 5.18 | 6.48 | 10.07 |
CPL | 16.81 | 13.98 | 25.33 | 16.36 | 23.13 | 13.83 | 21.24 | 30.68 |
Table 5
Classification and characteristics of CRNPSs"
Type | Number | Main features |
---|---|---|
Type I | 208 | HDI, SEI, and REI values are 4.00, 5.00, and 4.41, respectively. They are deeply poverty-stricken counties distributed within high-arid and remote areas, including the Tibetan Plateau, TPSX, and WMMA. These areas are mainly ethnic enclaves and encapsulate numerous restrictive conditions and extremely fragile ecosystems. |
Type II | 87 | HDI, SEI, and REI values are 2.48, 10.73, and 7.28, respectively. These counties are distributed in karst areas of southwest China. The development level of these areas is low due to low population quality caused by backward education and cultural differences of minorities. |
Type III | 142 | HDI, SEI, and REI values are 10.16, 5.74, and 6.65, respectively. These countries are concentrated on the eastern side of the Tibetan Plateau as well as in the BMA and Taihang mountainous area. Educational attainment in these regions is relatively high, but they are nevertheless influenced by fragile ecosystems, complex terrain, and inadequate infrastructure. The development levels of these counties are therefore backward. |
Type IV | 279 | HDI, SEI, and REI values are 7.42, 8.41, and 7.79, respectively. These counties are distributed in Xinjiang and southwest China, exhibiting shortcomings in personal abilities and social economy, but have better social and natural conditions, which create a foundation for development. |
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