Comparison of Thematic Maps Using Symbolic Entropy

Comparison of thematic maps is an important task in a number of disciplines. Map comparison has traditionally been conducted using cell-by-cell agreement indicators, such as the Kappa measure. More recently, other methods have been proposed that take into account not only spatially coincident cells in two maps, but also their surroundings or the spatial structure of their differences. The objective of this paper is to propose a framework for map comparison that considers 1) the patterns of spatial association in two maps, in other words, the map elements in their surroundings; 2) the equivalence of those patterns; and 3) the independence of patterns between maps. Two new statistics for the spatial analysis of qualitative data are introduced. These statistics are based on the symbolic entropy of the maps, and function as measures of map compositional equivalence and independence. As well, all inferential elements to conduct hypothesis testing are developed. The framework is illustrated using real and synthetic maps. Key word: Thematic maps, map comparison, qualitative variables, spatial association, symbolic entropy, hypothesis tests

Comparison of thematic maps using symbolic entropy

Comparison of thematic maps is an important task in a number of disciplines. Map comparison has traditionally been conducted using cell-by-cell agreement indicators, such as the Kappa measure. More recently, other methods have been proposed that take into account not only spatially coincident cells in two maps, but also their surroundings or the spatial structure of their differences. The objective of this paper is to propose a framework for map comparison that considers 1) the patterns of spatial association in two maps, in other words, the map elements in their surroundings; 2) the equivalence of those patterns; and 3) the independence of patterns between maps. Two new statistics for the spatial analysis of qualitative data are introduced. These statistics are based on the symbolic entropy of the maps, and function as measures of map compositional equivalence and independence. As well, all inferential elements to conduct hypothesis testing are developed. The framework is illustrated using real and synthetic maps

Iz časopisa

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Distribution-free inference for Q(m) based on permutational bootstrapping: an application to the spatial co-location pattern of firms in Madrid

The objective of this paper is to present a distribution-free inferential framework for the Q(m) statistic based on permutational bootstrapping. Q(m) was introduced in the literature as a tool to test for spatial association of qualitative variables, or more precisely, patterns of co-location/co-occurrence. The existing inferential framework for this statistic is based on asymptotic results. A challenge for these results is the need to limit the overlap in the neighborhoods of proximate observations, which tends to reduce the size of the sample, with consequent impacts on the size and power of the statistic. A computationally intensive inferential framework, such as presented in this paper, allows for greater versatility of Q(m). We show that under the bootstrap version the issues with size are ameliorated and the test is more powerful. Furthermore, in this framework there is no longer the need to control for overlap, which allows for applications to variables with more categories and smaller sample sizes. The proposed approach is demonstrated empirically using a case study of co-location of business establishments in Madrid.The authors would like to express their thanks to the project ECO2009-10534 of the Ministerio de Ciencia e Innovación del Reino de España

Análisis de Estructuras Espaciales Persistentes. Desempleo Departamental en Argentina.

This paper presents a collection of spatial econometrics tools to detect global and local spatial dependence. These tools are used to analyze the spatial structure of the unemployment rate in Argentina in Census 2001 and 2010. Detailed study enables identification and comparison of persistent spatial structures in the departamental distribution of unemployment

Análisis de Estructuras Espaciales Persistentes. Desempleo Departamental en Argentina.

This paper presents a collection of spatial econometrics tools to detect global and local spatial dependence. These tools are used to analyze the spatial structure of the unemployment rate in Argentina in Census 2001 and 2010. Detailed study enables identification and comparison of persistent spatial structures in the departamental distribution of unemployment

On Cells and Agents : Geosimulation of Urban Sprawl in Western Germany by Integrating Spatial and Non-Spatial Dynamics

Urban sprawl is one of the most challenging land-use and land-cover changes in Germany implicating numerous consequences for the anthropogenic and geobiophysical spheres. While the population and job growth rates of most urban areas stagnate or even decrease, the morphological growth of cities is ubiquitous. Against this backdrop, the quantitative and qualitative modeling of urban dynamics proves to be of central importance. Geosimulation models like cellular automata (CA) and multi-agent systems (MAS) treat cities as complex urban systems. While CA focus on their spatial dynamics, MAS are well-suited for capturing autonomous individual decision making. Yet both models are complementary in terms of their focus, status change, mobility, and representations. Hence, the coupling of CA and MAS is a useful way of integrating spatial pattern and non-spatial processes into one modeling infrastructure. The thesis at hand aims at a holistic geosimulation of the future urban sprawl in the Ruhr. This region is particularly challenging as it is characterized by two seemingly antagonistic processes: urban growth and urban shrinkage. Accordingly, a hybrid modeling approach is to be developed as a means of integrating the simulation power of CA and MAS. A modified version of SLEUTH (short for Slope, Land-use, Exclusion, Urban, Transport, and Hillshade) will function as the CA component. SLEUTH makes use of historic urban land-use data sets and growth coefficients for the purpose of modeling physical urban expansion. In order to enhance the simulation performance of the CA and to incorporate important driving forces of urban sprawl, SLEUTH is for the first time combined with support vector machines (SVM). The supported CA will be coupled with ReHoSh (Residential Mobility and the Housing Market of Shrinking City Systems). This MAS models population patterns, housing prices, and housing demand in shrinking regions. All dynamics are based on multiple interactions between different household groups as well as stakeholders of the housing market. Moreover, this thesis will elaborate on the most important driving factors, rates, and most probable locations of urban sprawl in the Ruhr as well as on the future migration tendencies of different household types and the price development in the housing market of a polycentric shrinking region. The results of SLEUTH and ReHoSh are loosely coupled for a spatial analysis in which the municipal differences that have emerged during the simulations are disaggregated. Subsequently, a concept is developed in order to integrate the CA and the MAS into one geosimulation approach. The thesis introduces semi-explicit urban weights as a possibility of assessing settlement-pattern dynamics and the regional housing market dynamics at the same time. The model combination of SLEUTH-SVM and ReHoSh is finally calibrated, validated, and implemented for simulating three different scenarios of individual housing preferences and their effects on the future urban pattern in the Ruhr. Applied to a digital petri dish, the generic urban growth elements of the Ruhr are being detected

Analyse de la variabilité individuelle d'utilisation du transport en commun à l'aide de données de cartes à puce

RÉSUMÉ L’achalandage des réseaux de transport en commun varie en fonction de nombreux paramètres. Des facteurs exogènes tels que la météo sont souvent rapportés dans la littérature mais il existe aussi des facteurs individuels : en effet, chaque usager a une utilisation temporelle et spatiale du transport en commun qui lui est propre. D’une part, des différences sont visibles entre les individus. Cette variabilité interpersonnelle est particulièrement prononcée dans les réseaux qui desservent un grand nombre de personnes du fait de la grande hétérogénéité des comportements observés.----------ABSTRACT Transit ridership varies according to many parameters. Exogenous factors such as weather are often reported in the literature, but there are also individual factors, as every user has a specific temporal and spatial use of the transit system. On the one hand, differences can be found between individuals. This interpersonal variability is particularly pronounced in networks which serve a lot of people because of the great heterogeneity of observed behaviors. On the other hand, intrapersonal variations are noticeable within the behavior of each individual, more or less in a short-term scope, depending on the evolution of the individual’s restrictions and preferences