The term of geopolitical environment refers to the combination of both natural and social environment. Geopolitical environment system is a gigantic and complex system which consists of physical element (e.g. topography, geomorphology, water and land resources, meteorological conditions, etc.) and social economic elements (society, ethic, culture, politics etc.). The research of the geopolitical environment system simulation is a scientific support to the understanding of the international geostrategic dynamics and successfully implement the national strategy. In recent years, the connotation and extension of the geopolitical environment system research have changed dramatically due to the international geo-strategic shift, the global economy and technical progress. This paper presents a review of the origin and development of the geopolitical theory, from classical geopolitics before World War Two to the geopolitics during the cold war period, and the geopolitical researches in post-cold war era. The integration of geopolitics and earth system sciences has brought new advances both in the disciplines and methodology in these areas. The key issues of the simulation of the geopolitical environment system include the dynamic changes of the geopolitical factors, the interaction and adaption of the multiple geopolitical environment factors, methods for establishing the geopolitical environment system and virtual geographical environment techniques. The results indicated that faced with these complicated nonlinear problems like "geopolitical environment system", the hierarchical, reasonable generalization of the model and the numerical approximation methods can achieve the results of quantitative analysis for specific geopolitical issues. Meanwhile, the big data technology is increasingly providing a new paradigm for the studies of geopolitical system. By the methods of heterogeneous data mining, machine learning and high-performance computing, it is expected to explore the associated relationships among the elements contained in the geopolitical environment system to forecast and intervene in the geopolitical environment system evolution, and to provide a new technical method for the solutions to geopolitical issues.
We collected and verified documentary records of the latest spring snowing dates (LSSD) in Hangzhou during the Southern Song Dynasty. Further, the statistical correlation between this proxy and February-April mean temperature in this region was examined, and samples later than the perennial mean of the LSSD during the study period were transformed into the decadal mean of LSSD by means of Boltzmann function. General characteristics of this reconstructed LSSD series with a 10-year temporal resolution were analyzed, compared with other documentary evidences and reconstructed climate series in China for 1131-1270 AD. The results suggested that: (1) Records of the LSSD in Hangzhou during the study period did not refer to ice pellets and graupels, which had an explicit climatic significance (-0.34 oC/10d, R2=0.37, P<0.001). However, when this proxy was used to reconstruct temperature changes, all dates should be converted in Gregorian style and meet the same criterion of "true Qi" as the Chinese traditional calendar after 1929 AD. (2) The decadal mean of LSSD can be effectively estimated by using the forefront of LSSD in the decade on the basis of Boltzmann function, whose extrapolation has a less uncertainty than that on the basis of linear models or polynomial models. (3) The spring in Hangzhou during 1131-1270 AD was almost as warm as the period 1951-1980 AD. At the centennial scale, this period can be divided into two phases: the cold 1131-1170 AD and the warm 1171-1270 AD. In the latter, 1181-1200 AD and 1221-1240 AD were two cold intervals at the multi-decadal scale. (4) The reconstructed LSSD series was well consistent with other documentary evidences and reconstructed climate series in China for 1131-1270 AD, which may reflect the mutual influence on the climate over most of China imposed by the Pacific Decadal Oscillation (PDO).
According to the Second Chinese Glacier Inventory (SCGI), Distribution of Glacier at Different Altitudes (DGDA), the Equilibrium Line Altitude (ELA) field and the Accumulation Area Ratio (AAR) in different mountains of western China were calculated and discussed systematically. The results show that: (1) The DGDA presents a pattern of normal distribution, the ratio of the percentage that the largest glacier area accounted for the total area to altitude difference of the glacier distribution can be used as the morphological parameters to delineate the character of the DGDA. (2) The ELA, affected by climate and topography, gradually decreases from south to north, and increases from east to west. Additionally, the ELA of the northwest and southern edges of the high mountains is more intensive than that of the Qinghai-Tibet Plateau. (3) The distribution of the AAR is related to the water vapor and topography. The AAR of the mountain exterior side and marine type glacier region is lower than 0.5, while that of the mountain interior side, the Tibetan Plateau inland and maximal continental glacier region is higher than 0.7.
The quantitative analysis of the effect of climate change on the fluctuation of farming-pastoral ecotone (FPE) boundary in northern China is a current focus in the field of response to climate change in ecological vulnerable regions. Previous studies have given profound descriptions about the effects of climate change on the boundary shifts of the ecotones qualitatively, but lacked quantitative analysis of the contribution of climate change on both spatial and temporal scales. Here, climate data from national meteorological stations and land use data interpreted from remote sensing images of the farming-pastoral ecotone (FPE) in northern China since 1970 were used to describe boundaries of the FPE based on both climate and land use in the 1970s, 1980s, 1990s and 2000s. Detection in horizontal and vertical directions method (FishNet) and Digital Shoreline Analysis System method (DSAS) were applied to detect the spatial pattern of the FPE boundaries and to examine how much of the boundaries shifts can be explained by climate change in different periods. The results showed that the spatial pattern of the FPE boundaries and contributions of climate varied in different regions and periods. The FPE boundaries moved slightly in the northwest part of the FPE and violently in the northeast part. The shift of climate and land use boundaries in northwest segment of the Greater Hinggan Mountains showed the most highly coupling relationship and the contribution rate of climate change reached 10.7%-44.4% in east-west direction and 4.7%-55.9% in north-south direction based on FishNet method and 1.1%-16.8% based on DSAS method from the 1970s to the 2000s. Most of the detections based on the two methods had consistent results. Moreover, DSAS method was better than FishNet method in overall accuracy and suitable for the precise detection in small range, while FishNet method was more appropriate for intuitive, rapid and low-precision analysis. Our findings highlight the importance of different adaption measures to climate change in the FPE of northern China in different regions and periods.
The impoundment of huge reservoirs deeply changes the water and sediment process in the downstream reaches and then influences the evolution of the downstream rivers. The meandering rivers sensitively responded to the variation of water and sediment process. That is why the meandering rivers are the important survey regions of river evolution, channels regulation and flood control projects. Based on the measured hydrological and morphological data from 1996 to 2016, the evolution law and its driving mechanism of the typical meandering river in the downstream reaches of Three Gorges Reservoir (TGR) are studied. By building the relationship between the cross-sections variation and the influencing factors, the mechanism is well examined. The results show that (1) before the establishment of the Three Gorges Reservoir, the meandering rivers have two types of evolution laws named "Convex banks deposition and concave banks erosion" and "Convex banks erosion and concave banks deposition". After the impoundment of the great project, the meandering rivers are featured only by the latter type. (2) After the retaining of water and sediment of TGR since 2003, the low flow channel and bankfull channel in Lower Jingjiang River have been continually eroded and the erosed areas are found in the low shoal of convex banks. The phenomenon is mainly resulted from the variation of water flow and sediment transportation and also influenced by the upstream river region, riverbed boundaries and branches. (3) The growing process of flow discharge from low water to bankfull discharge can lead to the increase of sediment transport capacity. When no big flood of discharge over 35000 m3/s is observed after the impoundment of TGR, the duration of bankfull discharge (22000-25000 m3/s) decides the erosion or deposition of convex banks after the impoundment. When the number of lasting days of bankfull discharge (22000-25000 m3/s) exceeds 20, the convex banks will be eroded. The concentration of coarse sand decrease contributes to the improvement of strength of water.
Soil erosion has become one of global environmental problems, especially in the Loess Plateau. Controlling soil erosion is of great significance to improve the ecosystem, and protect the ecological security and maintain the harmonious relationship between human beings and nature. We compare the effect of rainfall pattern and land use pattern on soil erosion in different watersheds to improve soil erosion models. Currently, the effect of rainfall and land use on soil erosion is the hot research topics. However, most of the studies are aimed at one single study area, and there is less comparative analysis of rainfall and land use pattern on soil erosion in different-scale watersheds. The neglect of comparative analysis of the effect of rainfall pattern and land use pattern on soil erosion would inevitably influence the further study of the mechanism of soil erosion. And it would affect the simulation accuracy of soil erosion models. The investigation of the effect of land use pattern and rainfall pattern on soil erosion would have great significance to soil erosion research and comprehensive governance of soil erosion problems. With reference to the concept of soil erosion evaluation index, this paper proposed the use of rainfall pattern index and land use pattern index for predicting soil erosion in different watersheds. Otherwise, this paper identified more important factors for soil erosion between rainfall patterns and land use pattern in different-scale watersheds. It has positive significance for carrying out the comprehensive management of soil erosion and land use pattern optimization design. The study areas of this paper are Qingjian River basin, Fenchuan River Basin, Yanhe River Basin and Dali River Basin. The main results are as follows. (1) From 2006 to 2012, the rainfall erosivity factor R in the study area showed an upward trend, while the vegetation cover and management factor C showed a downward trend. (2) When watershed area was small, the effect of rainfall pattern was greater than that of land use pattern on soil erosion. In contrast, when watershed area was large, the effect of land use pattern was greater than that of rainfall pattern on soil erosion. In other words, with the increase of the watershed area, the effect of rainfall pattern on soil erosion was gradually reduced while land use pattern indicated a contrasting effect. (3) With the increase of the watershed area, the proportion of woodland decreased and steep slope vegetation cover types tend to be homogenous, thus increasing the effect of land use pattern on soil erosion in larger-scale watersheds. With the increase of the watershed area, however, loose soil properties and craggy terrain increases the possibility of gravitational erosion, which enhances the effects of soil and topography.
In recent years, frequent urban waterlogging disasters have aroused great concern. Previous studies have mainly focused on the relationship between land use and waterlogging, but there is not enough information offered in these studies to explore the effects of urban landscape patterns on waterlogging. Taking Shenzhen as an example, this paper used correlation analysis and multiple stepwise regression analysis to explore the effects of landscape pattern on urban waterlogging. As urban waterlogging disaster is a systemic problem, which is related to the water circulation within the watershed, we divided Shenzhen into 56 sub-watersheds as the study units. Then we selected data of 278 waterlogging points during the rainstorm on May 11, 2014 and calculated the waterlogging point density of each sub-watershed to characterize the waterlogging degree. This paper considered 5 landscape pattern indexes to reflect the characteristics of landscape pattern, including LPI (Largest Patch Index), COHESION (Patch Cohesion Index), DIVISION (Landscape Division Index) at class-level, and CONTAG (Contagion Index), SHDI (Shannon's Diversity Index) at landscape-level. Furthermore, other data, including land use, impervious surface percentage, fractional vegetation coverage, precipitation, topography and storm drainage considered as factors influencing urban waterlogging, were also obtained. The results showed that: (1) Among land use types, the construction land, especially residential land, has the greatest impact on the urban waterlogging disaster, whose growth can significantly increase the disaster degree; (2) At class-level metrics, the higher level of construction patches' dominance and aggregation and the lower level of landscape division, would lead to more severe waterlogging disasters in a certain area, while the impacts of landscape pattern of greenspace are in reverse; (3) At landscape-level, the regions with more complex landscape are not prone to waterlogging disaster; (4) Impervious surface percentage and other human factors have greater impact on urban waterlogging than rainfall and other natural factors. This study demonstrated that landscape pattern had significant effect on waterlogging and could provide reference for control of waterlogging and planning management of landscape pattern.
The black soil region of Northeast China is an important national commodity grain base. The Wuyuer River Basin is a typical black soil region and agricultural area in Northeast China. In this paper, a SWIM (Soil and Water Integrated Model) was constructed to study the applicability in the middle and upper reaches of the Wuyuer River Basin. Based on observed daily runoff data from a local hydrologic station and evaporating dish weather data from 1961-1997, the model was validated using multiple criteria and sites. Special attention was paid to the use of both spatial information (potential evapotranspiration) and more commonly used observations of water discharge at the basin outlet to validate the model. The applicability of the SWIM is evaluated using the Nash-Sutcliffe efficiency coefficient and the relative error of runoff. Based on this analysis, the study discusses the applicability of the SWIM model in the black soil region of Northeast China, and the associated errors and causes. The study reached three key conclusions. First, the Nash-Sutcliffe efficiency coefficients of monthly runoff and daily runoff are greater than 0.71 and 0.55, respectively; the relative error of runoff is less than 6.0%. The simulation efficiency of the SWIM for both monthly runoff and daily runoff satisfies the assessment requirements, but the simulation efficiency of daily runoff is not ideal, and the simulation is more accurate for monthly runoff than daily runoff. The Nash-Sutcliffe efficiency coefficient of monthly evapotranspiration is more than 0.81. Second, the calibrated monthly SWIM model can be used to conduct different runoff simulations and analyses in the black soil region of Northeast China. Third, the study identified structural elements of the model that may limit some uses in the black soil region of Northeast China. The simulated values of spring flood runoff were less than the observed values; and the yearlong simulated results with spring and summer floods were poor. In years with a sudden increase in annual precipitation, the simulated results of the annual runoff were several times of the measured value. However, the model can fundamentally reproduce the flow change process during the flood season. The simulation results have an important reference value to study the impact of land-use change and climate change on hydrological processes at the regional scale. It can provide hydrological information to support the integrated management of the basin water environment, as well as other watersheds in the black soil region.
Land change has been a hot topic in geographical research. The overarching and convincing theories of land change science, however, have not emerged. Establishment of land use transition theory is of significance for the theory basis of land change science. This paper attempts to establish a research framework of land use transition based on summarizing the development and implications of land use transition research and clarifying the differences between land use transition and land use change. Results show that transition research of artificial ecosystems, such as cultivated land, rural housing land and urban land, is of significance. Land use transition is distinguished from land use change on several aspects, such as fundamental types, temporal scale, spatial scale, agents, driving forces, trajectory, and results or effects. Research framework of land use transition covers transition diagnosis, mechanism research and effects research. Key issues of transition diagnosis are the establishment of measuring indices and diagnosis principles of land use spatial and functional morphologies from the perspectives of quantity change, landscape pattern change and management pattern change, and of land use externality and land use policy development. Mechanism of land use transition behaves as cascading effects of underlying driving factors of land use change, including demographic, economic, technological, institutional, cultural, and location factors. Mechanism research should place emphasis on interaction between land use spatial transition and functional transition. Effects of land use transition covers at least 17 themes relating to social, economic and environmental dimensions. Cultivated land use transition in France in 1961-2011 confirms the research framework of land use transition and is beneficial to the innovation of cultivated land protection in China.
Human-induced land use/cover change (LUCC) has significant effects on the climatic and ecological processes at both global and regional scales. It is an important driving force of global environmental change and has been one of hot topics of international concerns. Since the industrial revolution, the expansion of built-up areas (construction land) has been profoundly changing the status of LUCC. Construction land expansion has been the most dominant feature in land use changes. People's lifestyles and ideas have changed a lot accordingly. It is urgent to to seek solutions to some global issues especially those in fields such as resources, environment and ecology. Historical LUCC research plays a key role in these fields. Confined by the data availability, reconstructing historical construction land confronts with some difficulties. Current research rarely targets at construction land along the historical timeline. There is room for research efforts in extending contents of such reconstructed dataset, quantifying key factors, and improving spatial analytical precision. Therefore, it is sensible to establish a method to reconstruct a more effective, comprehensive, and finer-precision dataset for construction land along the historical timeline. Based on historical records and contemporary statistics on natural resources, this study aims to reconstruct the spatial distribution of construction land (urban land and rural settlement land) for several selected time intersections in the past 200 years in Jiangsu Province with a resolution of 200 m×200 m. The results show that: (1) areas of construction land are estimated to be 963.46 km2 in 1820, 1043.46 km2 in 1911, 1672.40 km2 in 1936, 1980.34 km2 in 1952 and 10687.20 km2 in 1985; and (2) the spatial distribution of construction land are featured by a tendency to be close to water bodies and main roads as well as an effect of settlements’ polarization and diffusion. The validity of our research results has been proved indirectly by the trend test and the coordination analysis.
Central Asia is located in arid and semi-arid regions. This region contributes to dust aerosols because of desertification and land degradation. In order to better understand temporal variability, vertical distribution, and potential diffusion characteristics of salt dust and desert dust in Central Asia, we studied the intranasal changes in dust aerosol from the Aral Sea basin and Taklimakan Desert using MODIS aerosol data and CALIOP data, and analyzed its potential seasonal diffusion from 2005 to 2015 using the HYSPLIT model. Results showed that AOD of this region was high in spring and summer and low in autumn and winter. Over the 14 years, it showed an increasing trend. The mean values of the four seasons were: spring (0.412) > summer (0.258) > autumn (0.167) ≈ winter (0.159). The annual AOD high value areas were mainly concentrated in the Tarim Basin in southern Xinjiang and surrounding areas of Aral Sea. The annual average value of AOD in Aral Sea was 0.278, and annual amplification was 3.175%. It is indicated that the degradation of the Aral Sea had a direct impact on the AOD surrounding area. The annual average value of AOD in the Tarim Basin was 0.421, and annual amplification was 0.062%, which was mainly affected by temperature and wind speed, and the dominant factors were slightly different in different seasons. Dust aerosols were mainly concentrated in a range of 0-2 km. Aerosol depolarization ratio range in the desert (10%-45%) was slightly greater than that in the Aral Sea (15%-30%) and the aerosol color ratio range in the Aral Sea (0.3-0.8) was less than that of the desert (0.5-0.9). There were two high-frequency color ratios of 0.5 and 0.3 from the dust zone over 0-2 km and 4-6 km of salt dust. Compared to dust aerosols, salt dust aerosols had smaller irregularities and particle size, and higher impact of height range. As for the Aral Sea region, the potential distance and height of air parcel trajectories to the northeast were greater than to the west and south, whereas the air parcel trajectory proportion of the former was lower than that of the latter, which mainly affect Uzbekistan and Turkmenistan. Most of the dust in the Taklimakan Desert is still settling in the vicinity of the dust source region. The potential diffusion path to the eastern regions has impact on Qinghai, Gansu, Ningxia, Shaanxi and other regions.
The valley basins, the main grain output area and socio-economic center of Shaanxi Province, are experiencing population growth, rapid urbanization and industrialization. However, the eco-environment is suffering as a result of destructive human economic activities (forest and grassland clearance for farmland expansion, deforestation and vegetation damage) and is potentially facing a huge ecosystem crisis, from the likes of soil erosion and vegetation coverage reduction - all of which hinder local sustainable social and economic development. Because of complicated conditions and its significant location, the Guanzhong Basin, the economic center of Northwest China, and the Hanzhong Basin, an ecological preservation area in Shaanxi Province, were chosen for comparing and analyzing the spatial and temporal disparities between ecosystem services. In this study, we use several mathematical methods including the correlational analysis method, and the linear and power function regression methods to calculate the spatial and temporal differences between the two areas based on ecosystem services data from 1990 to 2010 (NPP, water conservation and food supply). From this, we find that NPP and water conservation have a synergistic relationship, and that there is also a trade-off between NPP and food supply, and between water conservation and food supply. In addition, between 1990 and 2010, this synergistic relationship shows a downward trend while the trade-off relationship demonstrates an upward trend. Furthermore, the rate of change in the Guanzhong Basin is faster than that in the Hanzhong Basin. In terms of the synergistic relationship between NPP and water conservation, the strongest evidence can be found in cultivated land in the east of the Guanzhong Basin and in the west of Ningqiang county and Lueyang county in the Hanzhong Basin; the lowest is observed in Tongchuan city and Xixiang city. When exploring the trade-off between NPP and food supply, we find that the strongest trade-off relationship is in Tongchuan city and the Qinling Mountains in Xi'an and the south of Xixiang county, while the weakest is in Baoji city and Lueyang county.
The inversion models applied in hyperspectral prediction of soil heavy metals include multiple linear regression, partial least squares regression, artificial neural network, and wavelet analysis. They are mostly based on the presumed homogeneous influence of heavy metal contents on spectral reflectance in different locations. This presumption, however, ignores the spatial heterogeneity of the correlation between heavy metal and spectral variables. In comparison, GWR model effectively reveals the spatial heterogeneity among different variables, which is well evidenced in the studies involving the spatial prediction of soil properties. But no publications can be found so far on the application of this model in hyperspectral prediction of soil heavy metals. In this paper, Cd, Cu, Pb, Cr, Zn and Ni were studied to establish GWR model for soil heavy metal prediction, with 132 soil samples taken from Fuzhou, a major city in southeastern China. Increasing soil pollution emerges in this area as a result of dense population and developed industrial and agricultural sectors. And the spatial distribution of soil heavy metals in the area features great heterogeneity because of complex and fragmented terrains. At first, metal concentrations of the samples were determined through inductively coupled plasma-mass spectrometry (ICP-MS) analysis, and reflectance was measured with an ASD (Analytical Spectral Devices) field spectrometer covering a spectral range of 350-2500 nm. Then a series of transformations were conducted to enhance the spectral features of heavy metals, such as derivative transformation, reciprocal transformation, absorbance transformation, and continuum removal. And then an analysis was made on the correlation between heavy metal contents and the transformed spectral data, and sensitive spectral bands were selected according to the highest correlation coefficient. With heavy metal contents as dependent variables, and sensitive spectral bands as independent variables, a stepwise regression analysis was conducted to select variables with low multi-collinearity, which were then used to establish prediction models. At last, the applicability and limitation of GWR model in the hyperspectral prediction of heavy metals was assessed by comparing the outcome of predictions based on GWR and OLS regression respectively. Some conclusions can be drawn as follows: (1) The applicability of GWR model is dependent on the spatial heterogeneity level of heavy metal influence on spectral variables: For Cr, Cu, Zn and Pb, whose influence on spectral variables features high-level spatial heterogeneity, GWR-based prediction performance was evidently better than that of OLS. It was shown in an obvious increase of adjusted R2 (by 2.69, 2.01, 1.87 and 1.53 times respectively) and an obvious decrease of AIC (by over 3 units) and RSS (by 74.67%, 69.91%, 52.78% and 13.16% respectively); For Cd and Ni, whose influence on spectral variables features low-level spatial heterogeneity, GWR-based prediction displayed an increase of adjusted R2 (by 0.015 and 0.007 respectively), a decrease of RSS (by 5.97% and 4.18% respectively) and a rise of AIC (by 2.737 and 2.762 respectively), with less significant improvement in prediction performance; (2) Heavy metal spectral properties are intensified by different spectral transformations, among which reciprocal transformation is most effective. And reciprocal transformation and its derivative patterns improve the performance of heavy metal prediction models; (3) With spatial non-stationarity as the prerequisite of application, GWR model is applicable in hyperspectral prediction of heavy metals that feature obvious spatial heterogeneity with soil spectral variables.
The innovation of spatial poverty measurement method is the key to precisely allocate poverty alleviation resources and improve the quality of rural poverty alleviation. This paper summarized the three-dimensional analysis framework of spatial poverty and constructed the spatial poverty index system at county scale and the method of geographical identification. With Jingyuan county as a study case, the geographical identification of spatial poverty was carried out. The results can be obtained as follows. (1) Spatial poverty index (SPI) in different geographical areas is listed in the order: Plain Area in Valleys Formed by Erosion and Deposition of Rivers (PAVFEDR) (mean value 1.571) > Denudation Structure in Hilly Regions (DSHR) (mean value -0.199) > Erosion Structure in Mountainous Regions (ESMR) (mean value -0.334), indicating that the highest poverty degree is in ESMR, which should be the main area of poverty alleviation. The common feature of spatial poverty in the three geographical areas is economic disadvantage (C4-C7, C17). The main differences are: for PAVFEDR, ecological disadvantage (C25, C16) > economic disadvantage (C5) > location disadvantage (C20) > political disadvantage (C8); for DSHR, economic disadvantage (C5-C7, C17) > location disadvantage > (C18-C20) > ecological disadvantage (C16, C23-C25) > political disadvantage (C8); for ESMR, economic disadvantage (C4-C7, C17) > political disadvantage (C8) > location disadvantage (C18-C20) > ecological disadvantage (C16, C21-C25). (2) The rank of SPI for different ethnic villages is as follows: Han villages (mean value 1.484) > Hui villages (mean value 1.262) > Hui-Han mixed villages (mean value 1.033), indicating that Hui-Han mixed villages at county scale should be the key villages for poverty alleviation. The common feature of spatial poverty in different ethnic villages is the economic disadvantage resulting from the long distance to the nearest market (C17), as well as the ecological disadvantage due to less arable land per capita (C23) and small crop area, especially economical crop area (C24). The main differences of spatial poverty in different ethnic villages are ecological disadvantage resulting from poor living conditions and high disaster loss rate in Han villages, as well as economic disadvantage caused by lack of loans (C5). For Hui villages, it is economic disadvantage caused mainly by low level of knowledge (C12, C13) that leads to the high opportunity cost in entering the market. In Hui-Han mixed villages the differences of production and lifestyle resulted in difficulties in allocation of poverty alleviation resources, consequently the satisfaction rate of poverty alleviation policies (C8) is the lowest for farmers, reflecting that the political disadvantage of spatial poverty is most significant. (3) There are significant differences in spatial poverty among different ethnic villages in the same physical geographical area. The mean values of SPI for Han, Hui, and Hui-Han mixed villages in PAVFEDR are 0.526, 2.557 and 1.644, respectively, which indicates that the Han villages have a high level of poverty and economic disadvantage (C5); the mean values of SPI for Hui and Hui-Han mixed villages in DSHR are 0.321 and -1.934, respectively, which indicates that the poverty level for Hui-Han mixed villages is high, and economic disadvantage (C2, C6, C7) and ecological disadvantage (C16) are both significant; the mean values of SPI in Han, Hui and Hui-Han mixed villages in ESMR are 1.031, -0.029 and -0.842, respectively, which indicates that the poverty level of Hui-Han mixed villages is high, and economic disadvantage (C5-C7, C17), political disadvantage (C8), location disadvantage (C18-C20) and ecological disadvantage (C16, C25) are all present. Therefore, the Han-villages in PAVFEDR, Hui-Han mixed villages in both DSHR and ESMR should be the key villages of poverty alleviation.
