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International audience; The population of Egypt more than tripled between 1960 and 2020, registering an increase from 27 million to about 100 million inhabitants. More than 95% of its territory consists of deserts. Its population is concentrated along the Nile, the narrow, fertile strip that runs from southern Egypt (Upper Egypt) to the north (Lower Egypt) over a distance of 1800 km. The population density of the entire country is 90 inhabitants per square kilometre, but the figure rises to 1140 inhabitants per square kilometre taking into account only the populated areas. Despite very rapid urbanization in the twentieth century, mainly benefiting the Cairo agglomeration, Alexandria and a dozen major cities, mostly in the Nile delta, Egypt is still predominantly rural. 1 The total fertility rate (TFR) in Egypt has declined progressively since the early 1960s when it was about 6.7 children per woman (Fig. 1). However, the decline showed an erratic trend until the mid-1980s, when the fertility transition finally started. Fertility continued to decline until the mid-1990s.

International audience; The Mediterranean is too often presented as a heterogeneous geographical area. Demography has helped to create this narrative of a Mediterranean of contrasts in which the different shores are systematically opposed: a northern shore in decline, with low fertility rates and an ageing population, as opposed to the young and fertile southern and eastern shores, which are experiencing rapid growth. However, this spatial dichotomy is gradually disappearing due to demographic transition: population growth and fertility are in decline, and the disparities between the different areas of the Mediterranean are vanishing. Moreover, demographic transition automatically gives rise to an ageing population. While the varied populations of the Mediterranean are currently differentiated by their levels of ageing, it is inevitable that these levels will converge in the future. This paper studies this future convergence, including the hypothesis that the southern and eastern shores will catch up with the northern shore. It also envisages a potential challenge to the spatial dichotomy of demographic ageing in the Mediterranean. To this end, we will go beyond the national frameworks generally used for studies of the Mediterranean as a whole and examine each Mediterranean country at a sub national level. After creating demographic projections based on 4 prospective scenarios, we will use various methods (cartography, spatial statistics, etc.) to express how the southern regions will catch up, how the space will change, and how the spatial dichotomy of ageing in the Mediterranean will evolve.

International audience; This article’s purpose is to draw attention to the results of the latest censuses in France, and to the dichotomy that remains between space and population in terms of settlement dynamics. A detailed examination on different levels – from counties (“départements”) to villages/towns (“communes”)- shows territories where the demographic dynamics are opposed. These dynamics don’t fit with commonplace conceptions, even in the scientific world. Beyond a mark that’s still visible and quantifiable, the “diagonal of emptiness” (a line drawn between the Pyrenees and the Ardennes) has actually not totally emptied. However, its geography is varied and can only be evaluated with thorough consideration removed from preconceptions. This is the point of our article, based on sharp cartography and measurements of spatial patterns. These indicate that some spaces in France seem to be literally abandoned by human beings.; Cet article souhaite attirer l’attention du lecteur sur les résultats des derniers recensements français et sur les distorsions qui perdurent entre espace et population en termes de dynamiques de peuplement. Une exploration détaillée de plusieurs niveaux géographiques (du département à la commune) montre des espaces dont les dynamiques démographiques s’opposent. Ces dynamiques ne répondent pas aux idées reçues et que l’on retrouve assez répandues, même dans le monde scientifique. Au-delà d’une empreinte encore visible et mesurable, la « diagonale du vide » n’a pas partout fini de se vider. Sa géographie est cependant variée, et ne peut être appréciée qu’avec un regard minutieux et départi d’a priori. C’est ce que nous avons tenté de faire en nous appuyant sur une cartographie fine et des mesures de structure spatiale. Celles-ci mettent en évidence une France dont certains espaces semblent délaissés par les hommes.

In this chapter, we present the main econometric specifications capturing spatial heterogeneity, or models of absolute locations, and examine how these specifications can be extended to further allow for spatial autocorrelation models of heterogeneous reaction by emphasizing the complex links between spatial heterogeneity and spatial autocorrelation. We detail some of these issues in the growth and convergence context in this chapter by first presenting the specifications allowing for discrete heterogeneity, that is, when different parameters are estimated following spatial regimes including a focus on recent papers dealing with the endogenous detection of convergence in the presence of spatial autocorrelation. Then we present continuous spatial heterogeneity models: geographically weighted regressions and models allowing for both continuous spatial heterogeneity and spatial autocorrelation. We conclude with some research directions.

Air pollution in trace elements (TE) remains a concern for public health in Europe. For this reasons, networks of air pollution concentrations or exposure are deployed, including a moss bio-monitoring programme in Europe. Spatial determinants of TE concentrations in mosses remain unclear. In this study, the French dataset of TE in mosses is analyzed by spatial autoregressive model to account for spatial structure of the data and several variables proven or suspected to affect TE concentrations in mosses. Such variables include source (atmospheric deposition and soil concentrations), protocol (sampling month, collector, and moss species), and environment (forest type and canopy density, distance to the coast or the highway, and elevation). Modeled atmospheric deposition was only available for Cd and Pb and was one of the main explanatory variables of the concentrations in mosses. Predicted soil content was also an important explanatory variable except for Cr, Ni, and Zn. However, the moss species was the main factor for all the studied TE. The other environmental variables affected differently the TE. In particular, the forest type and canopy density were important in most cases. These results stress the need for further research on the effect of the moss species on the capture and retention of TE, as well as for accounting for several variables and the spatial structure of the data in statistical analyses.

International audience; This paper explains how to make international comparisons on a Mediterranean scale for demographic and geographical themes. This study deals with the variability observed of surfaces and populations of the grids available of the Mediterranean countries. First, we wonder what makes the relevance of a grid compared to another. Then, we use spatial autocorrelation as an indicator of spatial and statistical characteristics of a grid for a specific variable. We create two grids for the occasion. Comparing several grids, we explore the variability generated by the variable of population density. The results show the importance of this kind of approach before beginning any international comparison. They also remind the importance of MAUP in spatial studies.; Cet article s’interroge sur la manière de procéder à des comparaisons internationales à l’échelle méditerranéenne dans une perspective démographique et géographique. Cette étude porte sur la variabilité observée des surfaces et des populations des différents maillages disponibles pour les pays du pourtour méditerranéen. Nous nous interrogeons d’abord sur ce qui fait la pertinence d’un maillage par rapport à un autre. Nous proposons ensuite d’utiliser l’autocorrélation spatiale comme indicateur de qualité des caractéristiques spatiales et statistiques d’un maillage pour une variable donnée. En nous appuyant sur une comparaison entre plusieurs maillages infranationaux, dont deux maillages construits pour l’occasion, nous explorons la variabilité engendrée par les maillages choisis sur une variable qui associe espace et population : la densité. Les résultats obtenus soulignent l’importance de ce type de démarche en préalable à tout travail de comparaison international et rappelle au passage l’importance que peut prendre concrètement le MAUP (Modifiable Areal Unit Problem) dans les études spatialisées.; Questo articolo esamina come fare confronti internazionali su scala mediterranea in una prospettiva demografica e geografica. Questo studio si concentra sulla variabilità osservata delle superfici e delle popolazioni di diverse reti disponibili per i paesi mediterranei. Ci chiediamo in primo luogo su ciò che rende rilevante una griglia rispetto ad un’altra. Inoltre ci proponiamo di utilizzare l’autocorrelazione spaziale come indicatore di qualità delle caratteristiche statistiche e spaziali di una griglia per una data variabile. Basandoci su un confronto tra diverse griglia infra-nazionali, tra cui due reti realizzate ad hoc, esploriamo la variabilità generata dalla griglia prescelta su una variabile che unisce lo spazio e la popolazione: la densità. I risultati sottolineano l’importanza di questo tipo di approccio prima di qualsiasi opera di confronto internazionale e ricorda la potenziale importanza che può assumere il MAUP (Modifiable Areal Unit Problem) negli studi spaziali.

International audience; Agriculture provides many ecosystem services such as food, fiber, clean water, and sequestration of carbon. The efficiency of such ecosystem services depends on crop composition and farmer decisions. Current knowledge on landscape changes is focused on crop allocation process at farm scale and rotations at field scale, whereas the impact of farmer decisions on the choice of crop acreages is poorly known. Therefore, we have built a method to assess the evolution of farm crop acreages in time and space and to identify factors ruling agricultural landscape changes. We use a dynamic typology, which is a multi-year classification of farmers. The seven steps of the method include three steps on farm typology, three steps on landscape changes, and then one step on change factors. We applied the method on 3,591 farms in Guadeloupe. Eight farm types were distinguished according to crop acreages. Our results show evidence of a diversification of 111 sugarcane growers toward production of vegetables and fruits. Spatial analysis revealed a relationship between diversification and water availability. Our method could be used to measure ecosystem services or disservices associated with changes in agricultural landscapes.

This paper provides a quantitative assessment of the effects of input and output prices on French GHG emissions from agriculture, forestry and other land use (AFOLU) at the NUTS3 level. Reduced-form, random-effect spatial error models are estimated for four emissions categories (nitrogen use, manure management, enteric fermentation, and land use, land-use change and forestry) in order to account for both spatial autocorrelation and spatial unobserved heterogeneity. The main findings are: (i) price impacts on emission levels are found to be significant, although sign and magnitude vary from one emission category to the other, (ii) estimated price effects are more apparent when emission categories are analyzed separately rather than aggregated, and (iii) the spatial dimension is found to play an important role. The estimated models are then used to simulate the effects of a doubling of crop prices on AFOLU emissions. The results indicate that this would lead to an 11%-increase in agricultural sources., Cette présentation propose une évaluation quantitative des effets des prix des produits et des intrants sur les émissions française de gaz à effet de serre dues à l'agriculture, la forêt et les autres usages des sols (AFOLU) au niveau NUTS3. Plusieurs modèles (formes réduites), incluant des effets aléatoires spatiaux, sont estimés pour chacune des quatre catégories d'émissions (utilisation d'azote synthétique, gestion des effluents d'élevage, fermentation entérique et usages des sols, changements et forêts afin de tenir compte à la fois de l'auto-corrélation spatiale et de l'hétérogénéité spatiale inobservable. Les principales conclusions portent sur : (i) l'impact des prix sur les niveaux d'émission est important, bien que le signe et l'ampleur varient d'une catégorie d'émission à l'autre, (ii) les effets des prix sont plus apparents lorsque les catégories d'émissions sont analysées séparément plutôt qu'agrégées, et (iii) la dimension spatiale joue un rôle important. Les modèles estimés sont ensuite utilisées pour simuler les effets d'un doublement des prix des cultures sur les émissions AFOLU qui conduirait à une augmentation de 11% des émissions agricoles.

International audience; It has long been known that insufficient consideration of spatial autocorrelation leads to unreliable hypothesis-tests and inaccurate parameter estimates. Yet, ecologists are confronted with a confusing array of methods to account for spatial autocorrelation. Although Beale et al. (2010) provided guidance for continuous data on regular grids, researchers still need advice for other types of data in more flexible spatial contexts. In this paper, we extend Beale et al. (2010)'s work to count data on both regularly- and irregularly-spaced plots, the latter being commonly encountered in ecological studies. Through a simulation-based approach, we assessed the accuracy and the type I errors of two frequentist and two Bayesian ready-to-use methods in the family of generalized mixed models, with distance-based or neighbourhood-based correlated random effects. In addition, we tested whether the methods are robust to spatial non-stationarity, and over- and under-dispersion - both typical features of species distribution count data which violate standard regression assumptions. In the simplest of our simulated datasets, the two frequentist methods gave inflated type I errors, while the two Bayesian methods provided satisfying results. When facing real-world complexities, the distance-based Bayesian method (MCMC with Langevin-Hastings updates) performed best of all. We hope that, in the light of our results, ecological researchers will feel more comfortable including spatial autocorrelation in their analyses of count data.

L'optimisation d'une opération de mélange de poudre repose essentiellement sur un travail expérimental à l'échelle du laboratoire qui doit pouvoir être transposer aux mélangeurs de plus grandes tailles. Définir des lois d'extrapolation et améliorer notre connaissance de la dynamique du mélange est donc nécessaire. Dans ces travaux, la dynamique de mélange au sein des mélangeurs Turbula® a été étudiée en s'appuyant sur l'analyse des cinétiques de mélange et des fonctions d'autocorrélation pour plusieurs systèmes particulaires. Selon les vitesses de rotation de l'axe moteur, 3 régimes d'écoulement ont été définis et les principaux mécanismes de mélange et de ségrégation apparaissant pour chacun de ces régimes ont été identifiés en lien avec les propriétés d'écoulement des produits. Dans un deuxième temps, les qualités de mélange obtenues dans différentes tailles de mélangeurs ont été comparées sur la base du principe des similitudes afin de mettre en évidence les facteurs ayant une influence lors du passage d'une taille de mélangeur à une autre. Enfin dans le cadre d'une application industrielle, une méthodologie s'appuyant sur l'intensité de ségrégation et l'autocorrélation spatiale, a été développée pour identifier des défauts d'homogénéité au sein de plaques bipolaires composites.

Until about the end of WWII, the territorial organization of the economy could be expressed along a very strong center-periphery gradient, with industries and services concentrated in cities while the countryside supplied agricultural products. Since the industrial revolution, industrial regions had emerged essentially in mining regions which perturbed this very simple scheme, but without fundamentally modifying it. In the first half of the 20th century, with the advent of mass transportation and of the individual car, the residential functions started to deconcentrate and residential suburbs developed. However, as a general rule, most non-agricultural economic functions remained tightly attached to the city core and its immediate surroundings, and with them their jobs. These structures were accounted for by various theoretical models, of which the Von Thunen land-rent model family, the Weber models of industrial localization and regional specialization, and the Christaller model of hierarchical city networks were the most prominent. However, since 1945, those jobs have seen their territorial distribution shift. First, the importance of agriculture dwindled, to the profit first of industrial activities, then of services. Land-hungry activities, such as the industry and logistical activities vacated the urban centers in search for ample space, which they generally found in suburban settings under the guise of industrial zones. But they weren't alone at deconcentrating. Retail and personal services tended to follow their customers in the suburbs. During the last quarter of the 20th century, selected suburbs evolved from purely residential or industrial functions to more complete economic ones, integrating retail, high tech and professional services. By 1990, the phenomenon was largely recognized in North America, where those job-intensive suburbs were nicknamed edge cities. Empirical studies showed convincingly that the same patterns of job and functional deconcentration were found in the whole world and especially in western countries. Job suburbanization is contemporary with major spatial and functional economical upheavals. The economy, for instance, evolved from the fordist integrated economical model dominated by very large companies internalizing most of their functions in a vertical, hierarchical relationship pattern to a post-fordist disintegrated model where companies concentrate on their core competencies and subcontract in a horizontal, contractual manner their non-core needs. Economical spatial deconcentration is also contemporary with the current version of globalization, materialized by the emergence of global cities and metropolises which keep constant communication flow between themselves, in a horizontal manner, and which are less and less dependent on their hinterland for their economical survival and development. Likewise, the economy becomes more and more informational, relying on knowledge, immaterial services, instant worldwide communication, and the production of sophisticated products for which worldwide shipping costs became negligible, and for which the location needs shifted from access to markets to access to qualified workers. While globalization, metropolization and the post-fordist economical transition have been thoroughly studied, job suburbanization has not been the focus of such an interest from the scientific community. Consequently, we lack empirical evidence and theoretical advances which would help us to better understand how the economy spatially evolved since 1945 and where the world is heading if the trends seen since 1945 are maintained. The prime goal of this work is to provide a better understanding of the way the economy spatially evolved at the intra-metropolitan scale, based on the example of Switzerland, a fairly exemplary western country. The work is divided in three major parts – an introductory one, an empirical one, and a inferential one. The core hypothesis of this work is that as the individual car became ubiquitous, proximal relations were progressively supplanted by accessibility relations. We surmise that job distributions and their evolution can be explained by accessibility patterns and change, which are in turn dependent on a number of factors – the population distribution, the structure and state of the road network, the state of the car technology, and the time commuters are ready to travel to go to work. The first three chapters aim at defining our object of study in chapter 1, to give an understanding of the country on which we will be working and of the data at our disposal in chapter 2, and a working definition of what constitutes a job center in chapter 3, where major distinctions between urban, mixed, suburban, exurban, touristic centers and edgeless space are introduced which accompanies us for the rest of the work. The next four chapters constitute the empirical part of the work. Chapter 4 seeks at describing as precisely as possible the territorial evolution of the Swiss economy since WWII, studying it at nine different points in time from 1939 to 2008. Chapter 5 takes a long-term view of the same series of data and seeks to detect, describe and explain the trends which are unearthed by this larger view. Chapter 6 concentrates on the latter half of the period under review and studies the distributions along more precise branch divisions, as well as miscellaneous other classifications according to added value and productivity, interaction needs, job qualification and creativity. Chapter 7 concentrates on the command and control structure of the economy as seen through the spatial relations entertained by headquarters and their subsidiaries, by Swiss and foreign multinationals, by the public and private sector. Finally, chapters 8 and 9 undertake the inferential part of our work, and aim at testing our core hypothesis of a statistically demonstrable link between accessibility, which is defined and thoroughly studied in its historical dimension in chapter 8, and a measure of job quality. Chapter 9, the last of the work, takes this core hypothesis to the statistical test. The results of this work are multiple. First of all, it shows that the spatial structure of the economy indeed transitioned from a very strong center-periphery organization in 1939, when two thirds of all non-agricultural jobs were located in urban centers, about a quarter in the country-side and the rest in numerous small industrial villages, to a vastly different structure in 2008 with less than half such jobs located in urban centers while suburban centers capitalize about a quarter of them, the rest being distributed mainly in edgeless space – industrial villages having somewhat lost in importance. This work shows that the spatial components of the economical structure have also greatly evolved. While in 1939 urban centers concentrated most of the economic functions and all of the commanding ones, spatial specialization has been relentless since then, and especially since the last quarter of the 20th century. Suburban centers have grown, but also gained in quality, especially in the high tech and the professional services sectors, and in commanding functions: as of 2008, they hosted more jobs in headquarters than in subsidiaries. In parallel, cities have tended to specialize on some key sectors of the economy: finance and governmental services at large, accompanied by personal services catering for the new urban elite. Taken altogether those developments pick at the prevailing spatial economic theories and show a major departure from the Christallerian model. Anecdotal evidence shows that by and large suburban centers seem not located haphazardly in the larger suburban belt, but are concentrated on several specific point within it, namely the higher accessibility areas, especially highway junctions and interchanges. This hints at the possibility that high accessibility is a determinant of job localization. In the course of this work we demonstrated first that accessibility is more dependent on road network changes that to other parameters such as population distribution, technological changes and attitude changes towards commuting, and that the accessibility changes due to road network evolutions display far stronger local accessibility gradients. Secondly, we demonstrated the existence of a link between accessibility and job density taken as a measure of job quality, after taking into account the effects of spatial autocorrelation. Much of the unexplained variance shown by a global regression model can be modeled away as regional effects when using a geographically weighted regression, so that the combination of regional effects and accessibility accounts for a major part of the job density variance. Finally, the introduction of time lags between accessibility conditions and job densities hinted at the possibility that a causal link exists between the two, accessibility changes preceding, and maybe then causing, job density changes: in short, this work shows that accessibility by car is a major determinant of job localization.

This paper presents various approaches dealing with heterogeneous reaction combined with interaction between neighboring units of observation developed in the spatial econometric literature, in the framework of cross-sectional models, and applied to the study of growth and convergence processes. We present the main econometric specifications capturing discrete or continuous spatial heterogeneity: the spatial regimes model and the locally linear, geographically weighted regression (GWR). We then examine how these specifications can be extended to further allow for spatial autocorrelation.; La présence d'effets spatiaux, hétérogénéité et dépendance spatiales, dans les processus de croissance et de convergence régionales a récemment été mis en évidence dans la littérature. Cet article est une introduction aux différentes approches méthodologiques, développées en économétrie spatiale dans le contexte des modèles en coupe transversale et appliquées à l'étude des processus de croissance, dont l'objectif est de traiter le problème de l'hétérogénéité combinée à l'interaction entre unités d'observations voisines. Les spécifications d'économétrie spatiale intégrant l'hétérogénéité spatiale discrète ou continue, en particulier le modèle à régimes spatiaux et le modèle de régression localement linéaire, géographiquement pondéré (GWR) sont d'abord présentées. Deux approches alternatives permettant la prise en compte simultanée de l'hétérogénéité spatiale continue et de la dépendance spatiale sont ensuite développées.

This paper presents various approaches dealing with heterogeneous reaction combined with interaction between neighboring units of observation developed in the spatial econometric literature, in the framework of cross-sectional models, and applied to the study of growth and convergence processes. We present the main econometric specifications capturing discrete or continuous spatial heterogeneity: the spatial regimes model and the locally linear, geographically weighted regression (GWR). We then examine how these specifications can be extended to further allow for spatial autocorrelation., La présence d'effets spatiaux, hétérogénéité et dépendance spatiales, dans les processus de croissance et de convergence régionales a récemment été mis en évidence dans la littérature. Cet article est une introduction aux différentes approches méthodologiques, développées en économétrie spatiale dans le contexte des modèles en coupe transversale et appliquées à l'étude des processus de croissance, dont l'objectif est de traiter le problème de l'hétérogénéité combinée à l'interaction entre unités d'observations voisines. Les spécifications d'économétrie spatiale intégrant l'hétérogénéité spatiale discrète ou continue, en particulier le modèle à régimes spatiaux et le modèle de régression localement linéaire, géographiquement pondéré (GWR) sont d'abord présentées. Deux approches alternatives permettant la prise en compte simultanée de l'hétérogénéité spatiale continue et de la dépendance spatiale sont ensuite développées.

Demographers often use maps and regional tabulations to evidence the spatial dimension of population characteristics. While they display considerable ability to test the strength of statistical links between phenomena, they rarely attempt to use similar tools to investigate the nature and extent of spatial correlation between demographic variables. This paper examines this question by combining theoretical and practical issues in the measurement of spatial autocorrelation, using recent Indian demographic variables. After a brief summary of the basic tools commonly used to examine geographical differentials, the paper includes a review of recent spatial exploratory and geostatistical tools. The second part of the paper is devoted to the application of these tools to a set of district-level variables derived from the Indian 2001 census, representing the major population characteristics as well other non-demographic variables. The conclusion sums some of the benefits and difficulties associated with spatial analysis in demography.