A spatial multicriteria model for urban accessibility mapping

Accessibility is nowadays an important issue for the development of cities. It is seen as a priority in order toguarantee equal access to fundamental rights, to improve the quality of life of citizens and to ensure that everyone, regardless of age, mobility or ability, have equal access to all the resources and benefits cities have to offer. Consequently, factors closely related to the accessibility have gained a higher relevance for identifying and assessing the location of urban facilities. The main goal of the paper is to present an accessibility evaluation model applied in Santarém, in Brazil, a city located midway between the larger cities of Belem and Manaus. The research instruments, sampling method and data analysis proposed for mapping urban accessibility are described. Daily activities were used to identify and group key destinations. The model was implemented within a geographic information system and integrates the individualâ s perspective through the definition of each key destination weight, reflecting their significance for daily activities in the urban area. Accessibility to key destinations was mapped over 24 districts of the city of Santarém. The results of this model application can support city administration decision-making for new investments in order to improve urban quality of life.

Comparison of maps of spatial variability of soil resistance to penetration constructed with and without covariables using a spatial linear model

A study about the spatial variability of data of soil resistance to penetration (RSP) was conducted at layers 0.0-0.1 m, 0.1-0.2 m and 0.2-0.3 m depth, using the statistical methods in univariate forms, i.e., using traditional geostatistics, forming thematic maps by ordinary kriging for each layer of the study. It was analyzed the RSP in layer 0.2-0.3 m depth through a spatial linear model (SLM), which considered the layers 0.0-0.1 m and 0.1-0.2 m in depth as covariable, obtaining an estimation model and a thematic map by universal kriging. The thematic maps of the RSP at layer 0.2-0.3 m depth, constructed by both methods, were compared using measures of accuracy obtained from the construction of the matrix of errors and confusion matrix. There are similarities between the thematic maps. All maps showed that the RSP is higher in the north region.

Non-testability of equal weights spatial dependence

We show that any invariant test for spatial autocorrelation in a spatial error or spatial lag model with equal weights matrix has power equal to size. This result holds under the assumption of an elliptical distribution. Under Gaussianity, we also show that any test whose power is larger than its size for at least one point in the parameter space must be biased.

Short-term temporal changes in the spatial variability model of CO2 emissions from a Brazilian bare soil

In this work, the spatial variability model of CO2 emissions and soil properties of a Brazilian bare soil were investigated. Carbon dioxide emissions were measured on three different days at contrasted soil temperature and soil moisture conditions, and soil properties were investigated at the same points where emissions were measured. One spatial variability model of soil CO2 emissions was found for each measurement day, and these models are similar to the ones of soil properties studied in an area of 100 x 100 m. (C) 2000 Elsevier B.V. Ltd. All rights reserved.

A spatial stochastic model for rumor transmission

We consider an interacting particle system representing the spread of a rumor by agents on the d-dimensional integer lattice. Each agent may be in any of the three states belonging to the set {0,1,2}. Here 0 stands for ignorants, 1 for spreaders and 2 for stiflers. A spreader tells the rumor to any of its (nearest) ignorant neighbors at rate lambda. At rate alpha a spreader becomes a stifler due to the action of other (nearest neighbor) spreaders. Finally, spreaders and stiflers forget the rumor at rate one. We study sufficient conditions under which the rumor either becomes extinct or survives with positive probability.

Trade Coefficients and the Role of Elasticity in a Spatial CGE Model Based on the Armington Assumption

The Armington Assumption in the context of multi-regional CGE models is commonly interpreted as follows: Same commodities with different origins are imperfect substitutes for each other. In this paper, a static spatial CGE model that is compatible with this assumption and explicitly considers the transport sector and regional price differentials is formulated. Trade coefficients, which are derived endogenously from the optimization behaviors of firms and households, are shown to take the form of a potential function. To investigate how the elasticity of substitutions affects equilibrium solutions, a simpler version of the model that incorporates three regions and two sectors (besides the transport sector) is introduced. Results indicate: (1) if commodities produced in different regions are perfect substitutes, regional economies will be either autarkic or completely symmetric and (2) if they are imperfect substitutes, the impact of elasticity on the price equilibrium system as well as trade coefficients will be nonlinear and sometimes very sensitive.

A Bayesian Spatial Mixture Model for FMRI Analysis

We develop, implement and study a new Bayesian spatial mixture model (BSMM). The proposed BSMM allows for spatial structure in the binary activation indicators through a latent thresholded Gaussian Markov random field. We develop a Gibbs (MCMC) sampler to perform posterior inference on the model parameters, which then allows us to assess the posterior probabilities of activation for each voxel. One purpose of this article is to compare the HJ model and the BSMM in terms of receiver operating characteristics (ROC) curves. Also we consider the accuracy of the spatial mixture model and the BSMM for estimation of the size of the activation region in terms of bias, variance and mean squared error. We perform a simulation study to examine the aforementioned characteristics under a variety of configurations of spatial mixture model and BSMM both as the size of the region changes and as the magnitude of activation changes.

Perception of global image contrast is predicted by the same spatial integration model of gain control as detection and discrimination

How are the image statistics of global image contrast computed? We answered this by using a contrast-matching task for checkerboard configurations of ‘battenberg’ micro-patterns where the contrasts and spatial spreads of interdigitated pairs of micro-patterns were adjusted independently. Test stimuli were 20 × 20 arrays with various sized cluster widths, matched to standard patterns of uniform contrast. When one of the test patterns contained a pattern with much higher contrast than the other, that determined global pattern contrast, as in a max() operation. Crucially, however, the full matching functions had a curious intermediate region where low contrast additions for one pattern to intermediate contrasts of the other caused a paradoxical reduction in perceived global contrast. None of the following models predicted this: RMS, energy, linear sum, max, Legge and Foley. However, a gain control model incorporating wide-field integration and suppression of nonlinear contrast responses predicted the results with no free parameters. This model was derived from experiments on summation of contrast at threshold, and masking and summation effects in dipper functions. Those experiments were also inconsistent with the failed models above. Thus, we conclude that our contrast gain control model (Meese & Summers, 2007) describes a fundamental operation in human contrast vision.

Research networks and inventors’ mobility as drivers of innovation evidence from Europe

We investigate the importance of the labour mobility of inventors, as well as the scale, extent and density of their collaborative research networks, for regional innovation outcomes. To do so, we apply a knowledge production function framework at the regional level and include inventors’ networks and their labour mobility as regressors. Our empirical approach takes full account of spatial interactions by estimating a spatial lag model together, where necessary, with a spatial error model. In addition, standard errors are calculated using spatial heteroskedasticity and autocorrelation consistent estimators to ensure their robustness in the presence of spatial error autocorrelation and heteroskedasticity of unknown form. Our results point to the existence of a robust positive correlation between intraregional labour mobility and regional innovation, whilst the relationship with networks is less clear. However, networking across regions positively correlates with a region’s innovation intensity.

Complex Vertical FDI and Firm Heterogeneity: Evidence from East Asia

In this paper we statistically test the validity of the mechanics of complex VFDI in Japanese machinery FDI to East Asia; we do this by estimating a multiple-spatial lag model. From the theoretical point of view, in complex VFDI, the production activity of affiliates in a given country is positively related to that in neighboring countries which have large differences in factor prices with the given country. Our empirical results show that such mechanics of complex VFDI work in Japanese FDI to East Asia, and that they work more strongly in the MNEs with higher productivity. These results have an important implication for the policies of developing countries in attracting FDI.

Relação espacial dos óbitos e internações por tuberculose com indicadores sociais em Ribeirão Preto (SP)

Objetivo: Propôs-se analisar a relação espacial dos óbitos e internações evitáveis por TB com indicadores sociais em Ribeirão Preto/SP. Métodos: Trata-se de um estudo ecológico em que foram considerados os casos de óbitos e internações, tendo como causa básica do óbito e motivo principal da internação, a tuberculose (CID A15.0 a A19.9), ocorridos na zona urbana de Ribeirão Preto e registrados respectivamente no Sistema de Informação sobre Mortalidade e no Sistema de Internação Hospitalar do Sistema Único de Saúde no período de 2006 a 2012. Foi realizada a análise univariada das variáveis sociodemográficas e operacionais dos casos investigados. Para construção dos indicadores sociais utilizou-se a análise de componentes principais, sendo selecionados dados das áreas de abrangência do município, considerando os dados do Censo Demográfico de 2010. A geocodificação dos casos foi processada no TerraView versão 4.2.2. Recorreu-se à regressão linear múltipla, pelo método dos mínimos quadrados e à regressão espacial para análise da relação de dependência espacial entre os indicadores sociais e as taxas de mortalidade e de internações por TB. A autocorrelação nos resíduos da regressão linear múltipla foi testada por meio do Teste Global de Moran, as análises foram realizadas considerando os softwares Arcgis-versão 10.1, Statistica versão 12.0, OpenGeoDa versão 1.0 e R versão 3.2.3. Para o diagnóstico do melhor modelo de regressão espacial, utilizou-se o teste Multiplicador de Lagrange. Em todos os testes, foi fixado o nivel de significancia de alfa em 5% (p< 0,05). Resultados: Foram registrados 50 casos de óbitos e 196 casos de internações por TB. A maioria dos casos registrados em ambos os sistemas se deu em pessoas do sexo masculino (n=41; 82%/n=146; 74,5%) e com a forma clínica pulmonar (n=44; 80,0%/n=138; 67,9%). Na construção dos indicadores sociais, três novas variáveis surgiram, apresentando respectivamente variância total de 46,2%, 18,7% e 14,6% sendo denominadas como indicadores de renda, desigualdade social e equidade social. Na modelagem para verificar relação espacial entre os óbitos e os indicadores sociais observou-se que a equidade social foi indicador estatisticamente significativo (p=0,0013) com relação negativa a mortalidade, sendo o Modelo da Defasagem Espacial o melhor método para testar a dependência espacial, com valor de ? (rho) estimado em 0,53 e altamente significativo (p=0,0014). Já na modelagem da relação espacial entre as internações por tuberculose e os indicadores sociais, o indicador de renda apresentou-se estatisticamente significativo (p=0,015) com relação negativa a internação e o melhor método para testar a dependência espacial também foi o Modelo da Defasagem Espacial com valor de ? (rho) estimado em 0,80 e altamente significativo (p<0,0001). Conclusão: O estudo contribuiu no avanço do conhecimento de que a mortalidade e as internações por tuberculose são eventos socialmente determinados, o que sugere investimento por parte da gestão

Where is the economics in spatial econometrics?

Spatial econometrics has been criticized by some economists because some model specifications have been driven by data-analytic considerations rather than having a firm foundation in economic theory. In particular this applies to the so-called W matrix, which is integral to the structure of endogenous and exogenous spatial lags, and to spatial error processes, and which are almost the sine qua non of spatial econometrics. Moreover it has been suggested that the significance of a spatially lagged dependent variable involving W may be misleading, since it may be simply picking up the effects of omitted spatially dependent variables, incorrectly suggesting the existence of a spillover mechanism. In this paper we review the theoretical and empirical rationale for network dependence and spatial externalities as embodied in spatially lagged variables, arguing that failing to acknowledge their presence at least leads to biased inference, can be a cause of inconsistent estimation, and leads to an incorrect understanding of true causal processes.

A bayesian spatial individual effects probit model of the 2010 UK general election

The Conservative Party emerged from the 2010 United Kingdom General Election as the largest single party, but their support was not geographically uniform. In this paper, we estimate a hierarchical Bayesian spatial probit model that tests for the presence of regional voting effects. This model allows for the estimation of individual region-specic effects on the probability of Conservative Party success, incorporating information on the spatial relationships between the regions of the mainland United Kingdom. After controlling for a range of important covariates, we find that these spatial relationships are significant and that our individual region-specic effects estimates provide additional evidence of North-South variations in Conservative Party support.

Bayesian estimation of the spatial Durbin error model with an application to voter turnout in the 2004 presidential election

The potential for spatial dependence in models of voter turnout, although plausible from a theoretical perspective, has not been adequately addressed in the literature. Using recent advances in Bayesian computation, we formulate and estimate the previously unutilized spatial Durbin error model and apply this model to the question of whether spillovers and unobserved spatial dependence in voter turnout matters from an empirical perspective. Formal Bayesian model comparison techniques are employed to compare the normal linear model, the spatially lagged X model (SLX), the spatial Durbin model, and the spatial Durbin error model. The results overwhelmingly support the spatial Durbin error model as the appropriate empirical model.