基于地理探测器的相对贫困地区矿产资源开发影响要素分析:以乌蒙山片区为例

2020年消除绝对贫困后,巩固脱贫攻坚成果、缓解相对贫困问题成为未来扶贫开发的核心任务.我国相对贫困地区蕴藏着丰富的矿产资源,但由于自然本底脆弱、产业基础薄弱等原因,其资源优势并未得到有效转化.本研究在系统分析影响相对贫困地区矿产资源开发各项要素的基础上,构建了包括矿产资源储量、资本投入、生态环境重要指数、交通优势度、...     

Income segregation,income inequality and mortality in North American metropolitan areas

There is a large sociological literature on racial- class-, and economically- based segregation in the United States and there is some evidence that residential segregation by income may have deleterious health consequences for residents of large U.S. cities. The health consequences of segregation in Canadian metropolitan areas, however, remain unknown and the comparison with the U.S. is always compelling. In this paper, we investigate the hypothesis that residential segregation by income may be associated with mortality in Canadian and U.S. metropolitan areas. Given the strong relationship between individual level socioeconomic status and health, it follows that metropolitan areas which isolate individuals economically could produce conditions that severely limit the life chances and therefore the health chances of the most vulnerable. To investigate the association between residential segregation by income and population health, we examined the relationship between working-age mortality and Jargowsky's (1996) neighbourhood sorting index (NSI) for a large group of North American metropolitan areas. We found a relationship between increased segregation and increased mortality for U.S. metropolitan areas but no such relationship for Canadian metropolitan areas. We also determined that income segregation could not be considered in isolation from income inequality – that, in effect, income inequality provides the propensity for meaningful segregation to occur. We further demonstrated the importance of considering both income inequality and income segregation together, especially when the analysis is intended to compare metropolitan areas. We conclude with a discussion of the need for an improved measure of segregation to better reflect the theoretical arguments for the relationship between concentration of poverty and affluence and population health.     

Changing poverty distribution in Bolivia: the role of rural–urban migration and urban services

Bolivia is a country with high levels of poverty and inequality among its peoples and regions. For the nation and its urban and rural areas, trends in the social and spatial distribution of poverty (and extreme poverty) are identified from 1976 to 2003 using UBN data with minor support where appropriate from poverty lines. The main survey between 1992 and 2001 uses composite and selected UBN to track detailed poverty change for the country’s nine departments, its ten largest cities and a selection of other smaller urban and rural municipalities. Because of rising background increases in population in the various surveyed administrative units, many instances of relative reductions in poverty are accompanied by rising absolute increases. Marked spatial variations in poverty and development in the country over the last several decades are identified as the main driver for the country’s quickening pace of rural–urban migration. As a result, the paper concludes by assessing two different but closely related views. One investigation tests the notion that because more poor people have been living in Bolivia’s cities than in its rural areas since the mid to late 1990s, rapid rural–urban migration has simply shifted the locus of poverty from the countryside to the cities in a process called, the ‘urbanisation of poverty.’ A second, more challenging, investigation assesses the view that the flow of poor rural people to the better serviced urban areas of Bolivia has actually acted to alleviate national poverty levels.     

Urban networks, community organising and race: an analysis of racial integration in a desegregated South African neighbourhood

The paper addresses the question of racial integration in Delft South, a desegregated low-income neighbourhood in Cape Town developed through the provision of state funded housing to families previously classified coloured and African. Through a qualitative analysis, the research examines the effect relocation has had on the racial character of economic and social networks around which resident families construct their everyday activities. In light of the importance of race in shaping these networks, the paper then examines the relationship between access to housing and practices of social and spatial integration, in particular organisation of and participation in street- and neighbourhood-level organisations. I demonstrate that in Delft South legacies of segregation persist in residents’ reliance on economic and social networks built on long, durable histories and geographies of racial segregation. Although physical relocation has not led to a lessening of the importance of racial identities, other identities built around issues such as neighbourhood norms, housing politics, and issues of criminality and legality manifest according to circumstances and residents’ interests. Context and situation therefore are significant for whether and to what degree race and place matter in the post-apartheid context.     

A spatial–temporal analysis of low birth weight prevalence in Georgia, USA

Low birth weight (LBW), defined as a live birth weighing <2,500 g, is a significant public health problem in the United States, especially a few states including Georgia. Although much work has been done to study the epidemiology of LBW in various regions, the spatial–temporal patterns of LBW prevalence in Georgia remain unclear to a large degree. This paper investigates the temporal trend of LBW rates over a time span of 11 years and the spatial clusters of LBW prevalence in the state of Georgia at the county level. Comparison is also made between race and gender groups, and between county groups of different socioeconomic statuses to uncover disparities. Results showed a steady and prevalent increase of LBW rate in the state over the study period. Three counties and two county clusters with significantly higher LBW rates than the state rate were detected for 1999–2001, while one more county and two more county clusters of high LBW rates were detected for 2007–2009. More urbanized counties were found to have a relatively lower LBW rate when compared with the less urbanized ones as groups. The findings from this paper are expected to provide valuable insights to better understanding the etiology of LBW and more effective allocating prenatal health care resources in the future.     

Measures of Parameter Uncertainty in Geostatistical Estimation and Geostatistical Optimal Design

Studies of site exploration, data assimilation, or geostatistical inversion measure parameter uncertainty in order to assess the optimality of a suggested scheme. This study reviews and discusses measures for parameter uncertainty in spatial estimation. Most measures originate from alphabetic criteria in optimal design and were transferred to geostatistical estimation. Further rather intuitive measures can be found in the geostatistical literature, and some new measures will be suggested in this study. It is shown how these measures relate to the optimality alphabet and to relative entropy. Issues of physical and statistical significance are addressed whenever they arise. Computational feasibility and efficient ways to evaluate the above measures are discussed in this paper, and an illustrative synthetic case study is provided. A major conclusion is that the mean estimation variance and the averaged conditional integral scale are a powerful duo for characterizing conditional parameter uncertainty, with direct correspondence to the well-understood optimality alphabet. This study is based on cokriging generalized to uncertain mean and trends because it is the most general representative of linear spatial estimation within the Bayesian framework. Generalization to kriging and quasi-linear schemes is straightforward. Options for application to non-Gaussian and non-linear problems are discussed.     

Linguistic segregation in urban South Africa, 1996

South Africa is a multi-lingual country with 11 official languages and a recent history where language was frequently used as a political instrument, notably in the urban areas. Although the cities were initially colonial foundations, as a consequence of rural-urban migration, the speakers of the various national languages have come into close contact with one another. However, as a result of the inheritance of apartheid town planning and its emphasis on racial zoning, residential segregation levels between some linguistic groups have been extremely high. An analysis of the 1996 census results reveals that the uniformly high segregation levels between the speakers of indigenous African languages and the speakers of Afrikaans and English are the direct outcome of apartheid era town planning. Nevertheless, segregation between the speakers of different African languages may also on occasion be relatively high where homeland political policies were pursued, although this was the exception rather than the rule. Similarly segregation between English and Afrikaans speakers was locally high where home language coincided with former racial classification. Few immediate significant changes are anticipated in the present patterns of linguistic segregation, as the inherited apartheid city structure is proving to be remarkably resistant to transformation.     

Stochastic Simulation Model for the Spatial Characterization of Lung Cancer Mortality Risk and Study of Environmental Factors

This paper presents a study in which the lung cancer risk in males was characterized based on a simulation model of mortality rates. Block sequential simulation of mortality rates, measured in counties of different sizes, was implemented and applied to a normal grid of continental Portugal with high spatial resolution. The uncertainty in the mortality rate measurements, directly related to differences in the population size of each county, was integrated in a block direct sequential simulation through Poisson kriging of local means and variances. Three age groups were examined: 50–59, 60–69, and 70–79 years. After the continuous geographic patterns of lung cancer risk were obtained, factors potentially associated with the main areas of risk were analyzed for southern Portugal. Thus, a defined class of land use and dry weather events, related to airborne particulate matter, were found to be associated with high-risk areas, resulting in high local spatial correlation patterns in all three age groups.     

Social geography,spatial structure and social structure

This paper adopts a positivist approach to social geography, which is viewed as a study of the two-way relationship between spatial structure and social structure. This relationship is examined in cities in contemporary Britain and the United States. The concept of social structure is discussed in the first section. It is suggested, after Blau, that social structure may be delineated by parameters which demarcate the lines of differentiation among people, created in their social interaction. Area of residence may be considered such a parameter. Social structure comprises a complex configuration of these parameters. In general, coinciding parameters limit social mobility and lead to an atomised society. The processes by which social structure takes on spatial expression are discussed in the second section. The salience of various parameters of social structure in a spatial setting is assessed first. Behaviouralist, managerialist and structuralist approaches to residential differentiation are reviewed. It is argued that most insight will come from studies of the interaction between groups of households and the major institutions of the housing market in the context of characteristics of the housing supply. The impact of neighbourhood on social structure is examined in the third section. The role of propinquity in social interaction is discussed along with the role of neighbourhood as a status symbol. Individuals may change their position along structural parameters as a consequence of their residential location. Residential segregation is also a means, through its role in circumscribing contacts, by which the continuation of the stratification system is ensured in the next generation. In conclusion, it is noted that the isolation of racial minorities in the disadvantaged parts of the city poses a danger to social stability.     

Signs of power: Fascist urban iconographies in Ethiopia (1930s–1940s)

The aim of the present paper is to compare two different patterns of urban iconographies in Ethiopia during 1930s: the one of the Amhara – the traditionally Ethiopian dominant ethnic group – and the one of the Italian fascism. The paper gives an historical account of the structure of the Amhara settlements, focusing on the ways the power of their politico-military chiefs, being they the Negus or the Ras, shaped the spatial order of these settlements. When the Italians conquered military Ethiopia in 1936, they started re-shaping this spatial order, erasing the signs of the previous power and imposing their new iconographic apparatus. This was mainly done through urban planning which was devised to `write' the Fascist concepts of progress, order, hierarchy, and racial segregation on the territory. Owing to the short duration of the occupation, the poor material conditions of the colony and the lack of financial resources, such town-planning projects turned out to be just a political rhetoric exercise.     

Bayesian Spatial Prediction for Discrete Closed Skew Gaussian Random Field

Most approaches in statistical spatial prediction assume that the spatial data are realizations of a Gaussian random field. However, this assumption is hard to justify for most applications. When the distribution of data is skewed but otherwise has similar properties to the normal distribution, a closed skew normal distribution can be used for modeling their skewness. Closed skew normal distribution is an extension of the multivariate skew normal distribution and has the advantage of being closed under marginalization and conditioning. In this paper, we generalize Bayesian prediction methods using closed skew normal distributions. A simulation study is performed to check the validity of the model and performance of the Bayesian spatial predictor. Finally, our prediction method is applied to Bayesian spatial prediction on the strain data near Semnan, Iran. The mean-square error of cross-validation is improved by the closed skew Gaussian model on the strain data.     

Signs of power: Fascist urban iconographies in Ethiopia (1930s–1940s)

The aim of the present paper is to compare two different patterns of urban iconographies in Ethiopia during 1930s: the one of the Amhara – the traditionally Ethiopian dominant ethnicgroup – and the one of the Italian fascism. The paper gives an historical account of the structure of the Amhara settlements, focusing on the ways the power of their politico-military chiefs, being they the Negus or the Ras, shaped the spatial order of these settlements. When the Italians conquered military Ethiopia in 1936, they started re-shaping this spatial order, erasing the signs of the previous power and imposing their new iconographic apparatus. This was mainly done through urban planning which was devised to `write' the Fascist concepts of progress, order, hierarchy, and racial segregation on the territory. Owing to the short duration of the occupation, the poor material conditions of the colony and the lack of financial resources, such town-planning projects turned out to be just a political rhetoric exercise.     

The green revolution and poverty: a theoretical and empirical examination of the relation between technology and society

The paper deals with the effects of the green revolution (GR) technology on poverty both conceptually and empirically. It provides a brief overview of the GR debate and then presents a `slice' of this debate in detail - in particular, Lipton's and others' views on the supposed positive and negative benefits of the GR for the poor. The paper then provides a provocative critique of this literature for its underlying neo-Malthusianism of a specific type, for ignoring class issues in the analysis of the GR-poverty relation, and for treating this relation as a necessary relation. It subsequently presents an alternative statement on the GR-poverty issue, arguing that it is class relations that set limit within which population and technology work and affect poverty and that the GR-poverty relation is a contingent one, rather than necessary. In the light of the paper's criticisms and the alternative view it provides, a statistical analysis of the relation between the GR and the population factor on the one hand and poverty level and poverty reduction on the other in India is performed. This analysis is generally consistent with the paper's critique of the Liptonian framework.     

Exploring the association between the occurrence of earthquakes and the geologic-tectonic variables in the Red Sea using logistic regression and GIS

Al-Ahmadi et al. (Arab J Geosci doi:10.1007/s12517-013-0974-6, 2013) applied spatial pattern analysis techniques to a seismic data catalogue of earthquakes beneath the Red Sea in order to explore and detect global and local spatial patterns in the occurrence of earthquakes over the years from 1900 to 2009 using a geographical information system (GIS). They found that the techniques of spatial pattern analysis that they applied could detect global and local clusters and broader spatial patterns in the occurrence of earthquakes and concluded that earthquakes with higher magnitudes were notably concentrated beneath the central and southern areas of the Red Sea, while earthquakes with low and moderate magnitudes were concentrated beneath the northern area of the Red Sea. The aim of this paper is to report on the application of logistic regression models to explore the associations between the likelihood of the occurrence of an earthquake beneath the Red Sea and four selected variables, namely: (1) proximity to the boundary of the African–Arabian plates, (2) proximity to transform faults, (3) proximity to the mid-Red Sea ridge and (4) the stage of rift evolution. The study was undertaken to evaluate the potential of logistic regression modelling for research exploring potential associations between earthquakes and geological and tectonic variables. The results revealed that none of the assumptions underpinning the logistic regression models had been violated for the three logistic regression models that were used in this research. The authors inferred that the occurrence of the earthquakes beneath the Red Sea was statistically significantly associated with the proximity to the African–Arabian plate boundary. We concluded that earthquakes of moderate magnitudes occurred in the zone which represents the late evolutionary stage of the Red Sea rift, including the transition zone beneath the central area and the late-stage continental rift zone beneath the northern area of the Red Sea. In contrast, earthquakes with high magnitudes tended to occur in close proximity to the mid-ridges of the Red Sea.     

After the war: Prospects for the health of the poor in Luanda,Angola

There is a dearth of published literature on health care systems in Angola. Like many Sub-Saharan African countries. Angola is experiencing rapid urbanization. An analysis of the health status, environmental health conditions and health-related behaviour of the urban poor in Luanda, Angola is provided.Although data are patchy and rarely disaggregated to reveal severe conditions in the shanty towns, a grave picture emerges. An average infant mortality rate of 104 per 1000 with malaria and intestinal infections the main causes of death in under ones reflects the poor environmental conditions which are worsening as urbanization continues at a rapid rate.Use of health services is limited with, for example of% of women giving birth at home, mainly unassisted, and only 28% of children covered by measles immunization (as validated by card).A discussion of existing health strategies, programmes and their constraints is set in the context of the future possibilities of the ending of the 15 year war and the introduction of structural adjustment policies.     

Bayesian updating revisited

Bayesian updating methods provide an alternate philosophy to the characterization of the input variables of a stochastic mathematical model. Here, a priori values of statistical parameters are assumed on subjective grounds or by analysis of a data base from a geologically similar area. As measurements become available during site investigations, updated estimates of parameters characterizing spatial variability are generated. However, in solving the traditional updating equations, an updated covariance matrix may be generated that is not positive-definite, particularly when observed data errors are small. In addition, measurements may indicate that initial estimates of the statistical parameters are poor. The traditional procedure does not have a facility to revise the parameter estimates before the update is carried out. alternatively, Bayesian updating can be viewed as a linear inverse problem that minimizes a weighted combination of solution simplicity and data misfit. Depending on the weight given to the a priori information, a different solution is generated. A Bayesian updating procedure for log-conductivity interpolation that uses a singular value decomposition (SVD) is presented. An efficient and stable algorithm is outlined that computes the updated log-conductivity field and the a posteriori covariance of the estimated values (estimation errors). In addition, an information density matrix is constructed that indicates how well predicted data match observations. Analysis of this matrix indicates the relative importance of the observed data. The SVD updating procedure is used to interpolate the log-conductivity fields of a series of hypothetical aquifers to demonstrate pitfalls and possibilities of the method.     

Bayesian updating revisited

Bayesian updating methods provide an alternate philosophy to the characterization of the input variables of a stochastic mathematical model. Here, a priori values of statistical parameters are assumed on subjective grounds or by analysis of a data base from a geologically similar area. As measurements become available during site investigations, updated estimates of parameters characterizing spatial variability are generated. However, in solving the traditional updating equations, an updated covariance matrix may be generated that is not positive-definite, particularly when observed data errors are small. In addition, measurements may indicate that initial estimates of the statistical parameters are poor. The traditional procedure does not have a facility to revise the parameter estimates before the update is carried out. alternatively, Bayesian updating can be viewed as a linear inverse problem that minimizes a weighted combination of solution simplicity and data misfit. Depending on the weight given to the a priori information, a different solution is generated. A Bayesian updating procedure for log-conductivity interpolation that uses a singular value decomposition (SVD) is presented. An efficient and stable algorithm is outlined that computes the updated log-conductivity field and the a posteriori covariance of the estimated values (estimation errors). In addition, an information density matrix is constructed that indicates how well predicted data match observations. Analysis of this matrix indicates the relative importance of the observed data. The SVD updating procedure is used to interpolate the log-conductivity fields of a series of hypothetical aquifers to demonstrate pitfalls and possibilities of the method.     

Exploring the spread of methamphetamine problems within California, 1980 to 2006

The introduction and spread of high potency methamphetamine has led to dramatic increases in drug-related problems in California. Prior research suggests that drug abuse rates are related to local demographic and economic characteristics, law enforcement activities, and sentencing practices. Methamphetamine abuse in particular has been shown to be reduced by laws regulating the raw materials needed for its production. This research models the regional effects of such laws on the spatio-temporal patterns of growth of methamphetamine-related problems across California from 1980 to 2006. Amphetamine-related arrests and hospital discharges related to amphetamine abuse/dependence were assembled for California counties over the years 1980–2006. Varying-parameter Bayesian space–time models were used to relate the implementation of major laws controlling the distribution of methamphetamine precursors to observed patterns of arrests and discharges and to allow such associations to vary by location. The models used conditionally autoregressive (CAR) Bayesian spatial priors to allow spatial correlation in estimation of county-specific growth in these measures over three distinct time periods: before the 1989 law, between the 1989 and 1997 laws, and after the 1997 law. Growth of arrests and discharges were related to demographic and economic indicators to determine geographic areas more or less susceptible to the spread of methamphetamine problems. Although both problem measures increased during all three periods, each of the precursor laws was associated with short-term reductions in the growth of arrests and discharges. Growth was greatest in central California counties prior to 1989 and increased in coastal counties in later years. From 1980 to 1989 growth was highest for counties with low incomes and high proportions of white residents, while 1989–1997 growth was highest in counties with fewer whites and more Hispanics. Growth after 1997 was not significantly associated with county characteristics. This research demonstrates that the precursor laws did suppress the growth of methamphetamine related arrests and hospital discharges. It also demonstrates specific geographic patterns in the growth of methamphetamine arrests and abuse across California during this time. Early patterns of growth were related to economic and demographic characteristics, while later patterns were not. This suggests that some counties were uniquely susceptible to the early spread of the methamphetamine epidemic, although problems eventually grew dramatically in all California counties.     

The changing structure, distribution and spatial segregation of the unemployed and economically inactive in Great Britain

Key trends in labour demand and supply in the 1980s, and their interactions, had uneven impacts on different population sub-groups and areas in Britain. As the structure of employment shifted from manufacturing to services, and there was a growth in high level non-manual occupations at the expense of less skilled manual jobs, there was increasing concern that the ‘losers’ from these processes of economic and social change would become increasingly ‘isolated’—in socioeconomic and spatial terms. This paper traces the changing contours of the geography of unemployment and inactivity in Great Britain between 1981 and 1991, at the regional and local scales, using a variety of indicators of spatial distribution and segregation. While on some measures there is evidence that unemployment became more widespread, there is evidence that the extent and intensity of non-employment, and the segregation of those without jobs, were exacerbated over the decade.     

The predictability of high-risk zones for heat-related mortality in seven US cities

Heat-related mortality remains a public health challenge in the United States. The objective of this study was to determine the temporal consistency of high-risk zones for heat-related mortality using historical georeferenced mortality data from seven US cities. A generalized additive model was used to identify city-specific threshold temperatures associated with increased mortality, and then the mortality rate on threshold-exceeding days was calculated for each postal code comprising each study city. This process was iterated by withholding subsets of data from the model and assessing predictability via cross-validation. In all cities, the average mortality rate in postal codes targeted for intervention by the statistical model was higher than that in non-targeted areas. Targeted areas for interventions in the study data accounted for 50 % of excess heat-related deaths despite only accounting for 25 % of total mortality. Focusing intervention measures at certain geographical zones within urban areas could be an effective means of combating heat-related mortality because there is temporal consistency in places where the death rate is most sensitive to heat.