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Geographical Modeling
Modeling Methodologies in Social Sciences Set coordinated by Roger
Waldeck
Geographical Modeling
Cities and Territories
Edited by
Denise Pumain
First published 2019 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.
Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:
ISTE Ltd
John Wiley & Sons, Inc.
27-37 St George’s Road 111 River Street London SW19 4EU Hoboken, NJ 07030
UK USA
www.iste.co.uk
www.wiley.com
© ISTE Ltd 2019
The rights of Denise Pumain to be identified as the author of this work have been asserted by her in accordance with the Copyright, Designs and Patents Act 1988.
Library of Congress Control Number: 2019949917
British Library Cataloguing-in-Publication Data
A CIP record for this book is available from the British Library
ISBN 978-1-78630-490-2
2.2. Explaining by reasons or laws: choosing an epistemological framework
2.3. The modeling approach: diversity of models
2.4. Explaining through statistical relationships or mechanisms
2.5. Choosing the level of abstraction for the phenomenon to be explained: general versus particular
2.6. Choosing the level of abstraction for the model: stylized or realistic, KISS or KIDS
2.6.1. Modes of representation of space: from a stylized space to a
2.6.2. Formalizing spatial mechanisms: from stylized to
Chapter 3. Effects of Distance and Scale Dependence in Geographical Models of Cities and Territories
Cécile TANNIER
3.1. Three fundamental principles for modeling cities and territories...................................
3.1.1.
3.1.2.
3.2.
3.3.3.
Chapter 4. Incremental Territorial Modeling
Clémentine COTTINEAU, Paul CHAPRON, Marion LE TEXIER and Sébastien REY-COYREHOURCQ
4.1. The map and the territory
4.1.1. Modeling as one map:
4.1.2. The representation of territory as an input of the model
4.1.3. The representation of territory as an output of the model
4.2. Generality and specificity: explaining by ways of geographical models
4.2.1.
4.2.2. General/specific/singular
4.3. Incremental territorial modeling
4.3.1. Identifying the object, scale, configuration, and stylized facts ..................................
4.3.2. Gathering the different theoretical explanations
4.3.3. Hierarchizing the interaction processes between agents
4.3.4. Hierarchizing the interaction processes between agents and their environment ............................
4.3.5. Implementing mechanisms and their formal alternatives
4.3.6. Combining, simulating, and comparing
4.4. Challenges and limits of multi-modeling
4.4.1. The combinatorial curse.......................
4.4.2. Human and technical costs
4.4.3. Subjectivity in the choice of building blocks..........
4.4.4. Comparing models of different structures
4.4.5. Sharing and accumulation of knowledge
4.5.
Chapter 5. Methods for Exploring Simulation Models
5.1. Social sciences and experimentation
5.2. Geographical data and computer skills
5.3. New generation simulations
5.3.1. A virtual laboratory: the OpenMOLE platform
5.3.2. The SimpopLocal experiment: simulation of an emergence in geography ..........................
5.3.3. Implementation of SimpopLocal, from NetLogo to OpenMOLE ..................................
5.3.4. Calibration and validation
5.4. Other examples of OpenMOLE applications: network–territory interaction models
5.5. Perspectives
5.5.1. Methods
5.5.2. Tools
5.6. Conclusion
Chapter 6. Model Visualization
6.1. Introduction
6.2. Visualization as modeling
6.2.1. Visualization as a tool for interdisciplinarity
6.2.2. Visualization and reproducibility
6.2.3. Visualizing a model means learning
6.3. Visualize to evaluate
6.3.1. Visualize before modeling
6.3.2. Visualize during the simulation
6.3.3. Visualizing after the simulation
6.4. Visualizing to compare
6.4.1. Which models should be compared?
6.4.2. How should visual comparison be done?
6.5. Visualizing to communicate
6.5.1. Visualizing to disseminate
6.6. Some obstacles inherent in model visualization
6.6.1. Producing and visualizing massive data
6.6.2. Visualization of aggregated data
6.7. Conclusion
Introduction
Never has geography been so present in our societies. For centuries, stimulated by the curiosity of travelers, the appetite of merchants, and the greed of powers, knowledge about the planet, its resources, and the riches of its cities and territories has never ceased to increase while remaining the privilege of the powerful. Precise knowledge of the terrain was an essential prerequisite for the great strategist Sun Tzu, in his famous book, The Art of War, published in China’s warring kingdoms during the Spring and Fall period in the 5th Century BCE. The French geographer Yves Lacoste confirmed, as recently as 1976, the strategic capacities of the discipline by showing in his provocatively-named book, La géographie, ça sert, d’abord, à faire la guerre (Geography primarily serves to make war), that it was supported in France by a nationalist and imperialist state power.
In France, geographic learning has been a requirement for all students in school curricula since 1870. However, it is especially since the emergence of mobile phones in the early 2000s that geography has been a factor in daily life. Even in the poorest countries, a very large majority of people are able to connect to the Internet, see images and maps from around the world, use satellite positioning services, GPS, Galileo, Glonass, or Baidu, to mark routes, navigate the world, geolocate, or make themselves visible to nearby “services” and “friends”. This revolution surpasses, by the number of applications it generates and the extent to which they are shared, the one that has occurred more discreetly since the 1970s with the widespread use of geographical information systems (GIS), in administrations, for spatial planning, and in companies, for logistics management. The limited capacity
Introduction written by Denise PUMAIN.
of the computers of the time and the insufficient competence of the services in the analysis and modeling of spatial data have long slowed down the effective integration of these tools into many activities (Goodchild 2016).
One of the current challenges in fully exploiting the new major computer capacities and democratizing geographical information is to make judicious and appropriate use of the knowledge and skills accumulated about cities and territories, not only through geography, but also by all disciplines that have sooner or later integrated the “spatial turn” into their research approaches, from agronomy to archeology and from history to epidemiology.
These disciplines share the construction of models, which are above all summaries of knowledge, simplified in relation to the diversity and complexity of individual cases, but communicable and improvable because they are codified, at a given moment in the state of knowledge, by mathematical or computer formalizations. The knowledge integrated into a model represents sets of recurrent facts in empirical observations, which have been selected according to the hierarchy of their effects on the problem being studied, with more or less parsimony depending on whether we focus on the generality or precision of the results. Calculation or simulation is used to propose predictions, or to explore possible scenarios, as part of the model assumptions. According to appropriate granularities and levels of resolution, all forms of modeling can be used with extremely variable objectives: laboratory hypothesis tests for theoretical models, serious games with a didactic function, support models designed to solve difficult situations including contradictory or even conflicting issues, models inserted in interactive applications intended for information or decision support, commonplace models generally used for location choices or infrastructure templates, and so on.
Critics of models often denounce oversimplification, or selection bias, and question the quality of the data used to validate them. Admittedly, each model has its shortcomings and deficiencies, but the great advantage of modeling, compared to the subtleties of written or spoken rhetoric, is that it requires very detailed clarification of the assumptions of discourse and intentions in order to better share them. Modelers are informed of the defects and deficiencies of their models; they are the first to deplore them and are constantly trying to overcome them.
The uses and functions of the models are multiple. They are often designed for prediction (meteorological and financial models), more broadly
data mining models, for the validation of an analytical theory (economic models) or, in geography, for the planning and discussion of territorial issues (decision support models and companion models), but social science modeling develops practices that are much broader and richer than those anchored in the traditional scientific imagination. Models are also used to deepen and test explanations using an abductive approach (Besse 2000) that interacts with conceptual constructions and empirical data, as will be shown in several chapters of this book.
Several publications have already proposed more or less ambitious syntheses of geographic modeling. For this expression in French, the Google Scholar algorithm offers some 40,000 references, which are mainly journal articles. Collective books or textbooks are less common. The book published by Lena Sanders in 2001 is pioneering in this field. The work of Yves Guermond (2005) compiles the productions and practices of the laboratory of the University of Rouen. Others have focused on the important processes of spatiotemporal change (Mathian and Sanders 2014) or only deal with certain urban models (Antoni et al. 2011; Bonhomme et al. 2017). Most recently, two books by Arnaud Banos (2013, 2016) and one by Frank Varenne (2017) laid the foundations for epistemological and philosophical reflection on geographical models.
The book we propose here is part of a multidisciplinary collection. It is designed to provide didactic information on the modeling process, in its particularities justified by the handling of geographical concepts and information, and illustrated with examples representative of the major innovations that have taken place over the past decade. Chapter 1 recalls the foundations of the geographical discipline on which models can be based to take into account the complexity in the organization and evolution of cities and territories. Chapter 2 deciphers the crucial choices for modeling, which are at the root of the diversity of models and their uses: we examine to what extent the complex can be simplified or, on the contrary, how can we try to integrate it into the models. Chapter 3 describes the models that establish explicit relationships between contrasting spatial morphologies, which present inequalities on different scales, and the social processes that generate them, according to “micro–macro” dynamics. Chapter 4 explores the construction stage of city and territory models and proposes a new incremental multi-modeling method. Chapter 5 introduces various possible uses of a simulation platform, OpenMOLE, which uses evolutionary algorithms and provides access to HPC equipment. Finally, Chapter 6 is
devoted to the new visualization tools that are so important for model exploration and validation, as well as for communicating their results.
At the end of the book, the index brings together the main concepts that characterize geographical modeling. For the concepts that are already precisely defined in the chapters devoted to them, the multiple page numbers that testify to their appearance throughout the book make it possible to understand how they also apply to widely shared intellectual and practitioner approaches. Moreover, essential concepts such as “space”, “simulation”, “territory”, “city”, and “visualization” do not appear in the index because they are used and enriched many times by all of the authors. It is also because of the great coherence of these texts that the bibliographical references, which often appear several times, are grouped into one list at the end. This provides an original and updated state of the art on the major parallel and convergent directions in geographical modeling.
Complexity in Geography
The last three or four decades have completely renewed the modeling practices of geographers. Two major changes, one epistemological and the other technical, are at the origin of these transformations. Technological change is the tremendous expansion of information processing capabilities, which has made work that could previously only be sketched as thought experiments possible, or work that has been carried out wholly incompletely due to a lack of powerful computing resources. This technical change has made it possible since about the 2000s to fully implement a major epistemological change that occurred sometime earlier in the 1970s and 1980s. This is the introduction of paradigms and models from the natural sciences into geography, whose keywords are self-organization (the dissipative structures of Prigogine and Nicolis (1971)), synergetics (Haken 1977; Weidlich 2006), and complexity and the notion of emergence (Bourgine et al. 2008). We will not recall here those filiations that are already mentioned in several works (e.g. Dauphiné 2003; Pumain et al. 1989; Sanders 1992). We want to show not so much how these forms of modeling can be applied in geography, but how to proceed for real model transfers, since many theories of the discipline had already largely anticipated the need for the newly proposed formalizations.
Transferring scientific language, concepts, methods, and instruments from one discipline to another is only a fruitful operation if it meets an expectation, a real need for innovation. In this case, it is not so much the paradigm of complexity as such that has been the novelty for the human and social sciences since they have always been confronted with the
Chapter written by
Denise PUMAIN.
Geographical Modeling: Cities and Territories, First Edition. Edited by Denise Pumain.
irreversibility of the trajectories of their objects, the near impossibility of prediction, and the phenomena of emergence in the systems studied. It is because complexity sciences provide complementary methods, means to process information and to formalize knowledge. Many geographers have adopted these references to work on their models. These have contributed to building cumulative knowledge when previously acquired intuitions could benefit from the transfer. This is why it seemed useful in this introductory chapter to remind geographers as well as readers trained in other sciences of the disciplinary fundamentals on which geography modeling can be based, particularly to deal with the complex objects that are cities and territories. We quickly retrace the successive postures of geographers faced with the possibilities of modeling, and then, we outline a set of regularities that can be more easily modeled among the objects that geography studies. These regularities partly lead to specific modeling practices by geographers, which are largely motivated by the multiplicity of observation scales, but also practices that have been much more in demand over the past two decades by the influx of geolocalized data, which opens up considerable development opportunities.
The general idea is that the complexity of the objects and processes observed by geographers is always constructed, not so much in formulating universal “laws”, but more often by including spatiotemporal elements, like in other human and social sciences, which are fundamentally “historical sciences” (Passeron 1991). These disciplines share with the natural sciences certain forms of nonlinear relationships, processes of self-organization, morphogenesis, dynamics oriented by attractors, or emergence phenomena characteristic of complex systems, which are formalizable on specific case subsets or segments of their trajectory. Geography adds to this complexity of nonlinear processes the specific feature of being interested in a very wide diversity of variables and levels of observation, including natural and social elements, in an attempt to formalize the evolution of landscapes, cities, and territories, which gives an additional dimension to the complexity of the systems that geography models1.
1 A few other disciplines such as archeology or social and environmental epidemiology also deal with indicators relating to the natural sciences as well as the humanities and social sciences.
1.1. A first bifurcation in the epistemology of geographic modeling
Geography appears among the humanities and social sciences as one of the most practiced in modeling (Banos 2013; Sanders 2001). Geography has often been identified as a pioneer in the use of digital tools. It is no coincidence that a philosopher has chosen to test his conceptions of modeling with this discipline (Varenne 2018).
This is a paradox: indeed, until recently, geography seemed to be a “soft science”, insofar as it does not assert theories as powerfully unitary as the so-called mainstream economy, and does not export its concepts as much as sociology, if we think, for example, of the French theory in vogue in the United States for at least 30 years. However, the theoretical and quantitative “revolution” that began in the 1950s in Sweden and the United States and then developed in France in the 1970s (Cuyala 2014; Pumain and Robic 2002), probably explains, to a large extent, why a certain “spatial turn” took place in most human and social sciences in the 1990s. Concepts and methods, software tools such as geographic information systems (GIS), and research questions brought by geographic space modeling practices (Banos 2016; Bonhomme et al. 2017) have been successfully imported into almost all disciplines.
However, in everyday language as in many representations of common sense, the “geography” or description of the Earth sometimes seems to be summed up in terms of nomenclatures, knowledge of locations (latitude, longitude, and altitude), and place names, the toponyms that societies have associated with them, whether they are mountain ranges, rivers, islands, or cities. However, academic geographic science – once the era of exploratory journeys and the “discoveries” of the regions of indigenous peoples by colonizers had passed – relied in the late 19th Century on questions designed to unpack the reasons for the diversity of the imprints shaped by societies on the Earth’s surface. Agrarian landscapes and forms of habitats, the exploitation of mining resources and industrial production, arrangements of villages and cities, traffic routes, and tangible or intangible flows have been examined at all scales, in a diverse range of geographical environments and according to their evolution over the course of history. Two main types of explanation successively dominated the research. In the first half of the 20th Century, the main focus was on the relationship between a society and its environment, speculating on the more or less favorable or constraining nature of natural conditions and the social capacity to develop them,
according to a somewhat “vertical” interpretation of its relationship with the resources offered locally by the planet. In the second half of the 20th Century, another, more “horizontal” way of producing explanations emerged, which tends to interpret the characteristics of a territory or a city from its situation in the world, i.e. from its relations with other territories and other cities. In truth, these two explanatory forms, which lead to very different models, are complementary and are necessarily articulated in any geographical interpretation of a particular city or territory.
1.1.1. “Vertical” explanations for the “science of places, not people” 2
In its academic history, geography has long been at the interface between the natural and human sciences. Taking into account the description of the planet (Robic et al. 2006) and its transformation into environments and landscapes by societies (Robic 1992), it had built a few general models. The relationship between the material organization of societies and natural resources, mediated by climatic and altitudinal zones, had been well observed and described, revealing some regularities. In particular, they highlighted the fairly close interdependence between ancient societies and the local character of mineral and plant resources used in housing and agriculture, which did not, however, exclude long-distance trade in less common commodities. When such regularities were systematized to excess (e.g. “limestone votes left, granite votes right” to caricature the positions of André Siegfried, founding geographer of electoral sociology in the 1930s, who actually linked the hydrography of these environments to their form of habitat, grouped, or dispersed and to the degree of dependence of the inhabitants on the domination of landowners), the corresponding statements were quickly rejected on the grounds of “determinism”. Conversely, noting the great diversity of selections and combinations of resources made by societies under more or less equivalent physical conditions could also, on the contrary, lead to “exceptionalism” (Schaefer 1953). This expression covers Schaefer’s criticism, both of the claims, which was frequent at the time, of a specificity of the geographical explanation, based on the genetics of the places, and of its consequence consisting in highlighting the uniqueness of the places. Regional
2 The expression in quotation marks is by Vidal de la Blache, with the intention of characterizing the geography project to distinguish it from that of Durkheimian sociology, which became institutionalized at the same time, between the end of the 19th Century and the beginning of the 20th Century.
idiosyncrasies have been the subject of numerous demonstrations denying the possibility of a rise in generality, the authors insisting sometimes on the strong constraint exerted by local resources and sometimes on the social free will with regard to how using and transforming them, as well as to the diversity of their creations in terms of the forms of their political, social, and cultural organizations. In the early days of academic geography, it was, therefore, physical geography in the fields of geomorphology or climate, which allowed modeling. Thus, since the early 1960s, the English geographer Richard Chorley (1962) advocated the transposition of von Bertalanffy’s general theory of systems into geomorphology and advocated the design of open systems, both for physical and human geography3. In such systems, the second law of thermodynamics does not apply and evolutions are not directed toward the maximum entropy and homogeneity, but other processes generate all kinds of configurations, formalized in models, which were listed five years later in a book written with Peter Haggett about these two branches of geography (Chorley and Haggett 1967).
1.1.2. “Horizontal” explanations for the science of the spatiality of societies
Some other types of regularities had indeed been observed since at least the early 19th Century in the organization of cities and territories and gave rise to various attempts at formalization, through mathematical models or iconic representations. The regularities of the spacing of cities, the hierarchy of their functions, and the interlocking of their catchment areas had been described since 1841 by the Saint-Simonian Jean Reynaud as “the general system of cities” strongly constrained by the use of the nearest service and thus generating forms of circular or hexagonal service areas, interlocking according to a hierarchy of rarity of urban services (Reynaud 1841; Robic 1982). This concept and the derived spatial models had little immediate impact, but the principles of a theory associating the size of cities with the rarity of their economic functions and the extent of their clientele in the surrounding region were rediscovered and systematized by the German geographer Walter Christaller (1933) in a “central place theory”, which was the subject of multiple tests in all parts of the world (Berry and Pred 1961).
3 “Open-system thinking, however, directs attention to the heterogeneity of spatial organization, to the creation of segregation, and to the increasingly hierarchical differentiation which often takes place with time. These latter features are, after all, hallmarks of social, as well as biological, evolution” (p. 10).
This theory actually included the previous model known as the “Reilly law of retail gravitation” (Reilly 1931), which explained the location of commercial activities by competition between businesses and services frequented by consumers under the constraint of proximity. In both the Reilly and Christaller models, travel costs are borne by the consumer and are added to the price of goods, encouraging people to buy from the nearest place. This determines, in the cartographic representations, more or less circular-shaped catchment areas, which fit together in the form of hexagons in the spatial diagrams drawn by Christaller.
In fact, these early geographic models validate what American cartographic geographer Waldo Tobler (1970) later referred to as “the first law of geography” (“everything interacts with everything, but two close things are more likely to interact than two distant things”). This law summarizes many of the previous observations made about the movement of people in space. The first formalizations can be attributed to the geographer Ernst Georg Ravenstein (1885), who published several articles from 1885 onward which summarized the main characteristics of population movements in a period of high rural exodus under the title “Migration laws” in a British statistical journal.
It was the American geographer Edward Ullmann who, in 1954, proposed defining geography as the science of spatial interactions. In his work Geography as Spatial Interaction, he certainly introduces the same “physical” model as the astrophysicist Stewart (1948), namely, a “gravitation” model (the flows between two geographical units are proportional to the product of their masses and inversely proportional to the distance that separates them) but he truly transposes this idea to the social sciences. He specifies the geographical conditions that are likely to explain the exchange and the movement: there must be a complementarity between a demand for a given product from a certain place of origin and the resources available in a place of supply, and travel must be possible, and therefore not too costly, for the exchange to take place. The characteristic principle that organizes geographical space is, therefore, the constraint of proximity; it includes the “sociological” principle that puts it into practice, stipulating that the nearest destination is chosen. There must also be no closer places offering the same product, or intermediate locations, which the sociologist Stouffer (1940) calls intervening opportunities.
The geography that is built on these foundations (Abler et al. 1977) is then conceived as a science of the organization of space. This expression
was coined by the French geographer Jean Gottman (1961) about the Northeast megalopolis, the group of cities that stretches from Boston to Washington. Although it is made up of distinct urban entities, whose urban structure is not continuous, this large regional complex appears to be a functional unit due to the multiplicity of communication and exchange networks that connect these cities together and make them complementary in a differentiated territory. The concept of a region then gradually emerged from the criteria of landscape homogeneity or historical delimitation that had hitherto underpinned it and was enriched by the concept of a functional region, defined by the polarization of traffic flows and the strong economic and social interdependencies between the cities and countryside that constitute it. This new form taken by geographical investigation then makes it possible, under the designation of “locational analysis” (Haggett 1965), to identify all kinds of regularities in geographical space and to build canonical models, whose ancestors are often shared by economists specializing in the emerging “regional science” (Isard 1960).
The translation into French of Peter Haggett’s book (Locational Analysis in Human Geography) by Hubert Fréchou in 1973 converted the title to “spatial analysis”. This expression, which was used in subsequent manuals (e.g. Pumain and Saint-Julien 1997), is the subject of one of the three main entries in the online encyclopedia Hypergeo, entitled “the spatiality of societies”, alongside the entries “societies and environment” and “cities, regions, and territories”. The notion of spatial analysis in French covers a perspective centered on human geography and a broader and less strictly technical theoretical content than in the practices of British or North American geographers. For example, British geographers Paul Longley and Michael Batty closely associate the spatial analysis with specialized GIS software in their 1996 and 2003 books, and the preface to their 2003 book defines it as “a kind of data mining technology”. More broadly, the definitions given by French-speaking geographers for spatial analysis readily incorporate the statements of theories and models, and some specialists in “social geography” have sometimes also claimed this expression as a means of designating their activity.
1.1.3. The discussed status of modeling
Since the 1970s, attempts at modeling in geography have been subject to heavy criticism. To mention just one example, let us recall one of the most eminent geographers of his generation, Pierre George, a member of the
Institute, who denounced both a “scientific adventurism”, “quantitative illusion”, and a “new determinism” (1972). For this Marxist geographer, criticism focuses above all on the idea that quantified formalizations can only use biased data, as they depend on the policies that build them. More surprisingly, by placing himself in the field of philosophy, Pierre George also denounces a “much more serious mystification” brought by the “formalization applied to geographical data”. According to him, it “presupposes, indeed, the acceptance of the idea that men and their initiatives are integrated into concentration camp categories from which they can only escape by a statistically negligible, politically and socially reprehensible marginalism, the marginalism of the anomaly, compared to an institutionalized system and disseminated by all modern means of imposing information and official culture” (1976, p. 54). Many other authors have denounced the models as too general and simplistic. The use of mathematical models, often quite simple, was denounced as unsuitable for accurately representing individual and social processes, e.g. in terms of location or displacement choices. The main argument against any modeling was the respect for human freedom, which was not to be represented as “obeying” the constraints of distance or natural conditions. The modeling was also denounced for political reasons such as an attempt to “naturalize” social processes, which would have been tantamount to accepting the established order and would not have allowed it to be called into question. This tension is also well expressed by the Anglo-American geographer David Harvey, who accepts Popperian models and logic in a first book on explanation in geography (Harvey 1969), then in a second book on the relations of domination in the urban space (Harvey 1973), and finally proposes a Marxian critique of capitalism and imperialism (Harvey 1982) –without, however, going so far as to accept post-modern criticism or to deny modeling.
The dissociation between Marxist interpretations and the use of quantitative models has often been more pronounced in English-speaking countries4 than in continental Europe, where the “theoretical and quantitative revolution” was more opposed to conservative geographers, both politically
4 There are exceptions, including the work of William Bunge, who in 1962 proposed a “Theoretical Geography” based on axioms and which was rather geometrical, and who also analyzed social inequalities in the suburbs of Chicago with quantified indices (Fitzgerald: Geography of a Revolution, Schenkman Publishing Cy, Cambridge, 1971, p. 1071) where he denounced the capture of land rents by the richest and the poor living conditions imposed on black people.
and methodologically. The successive waves of radical geography, phenomenology, and then post-modern geography that have emerged in the United States since the 1980s have spread to Europe with unequal intensities while making many criticisms of modeling (under the pretexts of “fetishization of space”, voluntarily forgetting actors, conflicts, social, or colonial, then forgetting representations, sensations, or, even more recently, emotions). An integrative definition of spatial analysis as “the formalized study of the configuration and properties of space produced and experienced by human societies” (Pumain and Saint-Julien 1997) proposed in a handbook signified a willingness to calm these controversies, which have aroused animated debate among all social sciences. In the 1990s and the decades that followed, there was a very large development of models, a widening of their practical uses, and a progressive enrichment of their content, largely supported by the generalization of geographical information systems and the integration of geolocation into all kinds of technical devices (see Chapter 6). Finally, the dizzying increase in computing capacity was expected to free up modeling from some of the qualitative limitations that could hinder the consideration of hazards and individual specificities in models (see Chapters 3–5).
According to our constructive perspective for modeling, proposals contrary to modeling, which are still used in some publications today, are based on misunderstandings that are deliberately not well clarified. They are likely to maintain controversies, not very valuable for the image of geography, and can be classified under three main types: those that reject any kind of regularity in the organization of the space of societies and deny the usefulness of a geographical discipline; those that treat geographical space as an inert container of physical objects and social relationships; and those that place any explanation within the exclusive framework of a theory of mono-disciplinary inspiration, such as certain geo-economic models or even certain narratives of post-modern inspiration or certain militant texts. However, we believe that geographical modeling can integrate a very wide variety of social processes, both individual and collective, and can be based on knowledge established by several disciplines, at different levels of resolution and granularity of its objects, from the individual to the world. Like a more discursive geography, strengthening existing powers is not the primary function of modeling; it can also be used to promote sustainable development and help the poorest populations and territories.
1.2. Modeled regularities
With their theories of complex systems, physicists who enter the social sciences to propose models are often tempted to project some of the constraints they have built to analyze the forces at work in the physical world. Although energy, in the various forms of solar radiation, gravity or animal, human, and mechanical work, is always taken into account in technical artifacts or human organizations, it is not very effective to consider that this is the main constraint (or last resort) that would govern the construction of human activity on the Earth’s surface and from which the form of the socio-spatial organizations studied in geography would have been identified (West 2017). The configurations of cities and territories that can be modeled by geographers are built by accumulated human work, carried out under material constraints, but also with some well-identified anthropological and social determinants, e.g. the relatively universal principle of the “law of least effort” as enunciated by G. K. Zipf (1949), or the frequent effects of political, cultural, or economic domination were observed in social relations and interactions.
The history, the forms of political and economic organization of societies, and their cultural creations are always part of the explanations proposed in “general geography” or in local or regional monographs. However, geography itself provides a modelable dimension to these constructions, to which the other disciplines of the natural and social sciences are articulated as in any explanation of complex social systems. Modeling takes into account major regularities, which are accepted, often implicitly, by most geographers. These regularities include the constraint of proximity, which brings into play various expressions of distance in all gradient models of the center-periphery type, or the organization of geographical space in levels, leading to great attention being paid to the scale of structures and processes or the reduction of interactions by territorial boundaries or barriers (physical or socio-cultural) that create discontinuities. Models of spatial change integrate the other regularity of temporal persistence of geographical objects, which is certainly shorter than those of geological periods or ecosystems, but so much longer than that of daily movements or human lives or even sometimes than the passage of generations, which leads to many reflections on the resilience of cities and territories and justifies their modeling.
These major regularities of spatial organization and evolution of space and geographical objects are presented in the following, which necessarily
introduces some repetitions, as the processes that generate them are complex according to the meaning of this term in the social sciences. These processes are difficult to separate from each other because they often interfere together during the genesis of cities and territories.
1.2.1. Proximity and distances
The concept of distance encompasses a range of indicators and measures of separation, adapted to the different types of relationships considered to signify distance, spacing, or remoteness, which have greatly broadened the scope of the concept of distance in the geographical explanation. To conceive a distance is indeed to give oneself a relational representation of space, whose properties then depend on the nature of the chosen distance and, therefore, on the form of the possible relations (offered or revealed) between the parts of space. To do this, we must no longer see space as a simple container, an empty room furnished by human activities, but as a construction, a representation of the relationships (virtual or realized) between different places, variable according to the traffic facilities, or the intensity of the exchanges that we consider. Broadly speaking, two complementary insights are used to define distance as a structuring factor of geographical space, in this relational and also “relativistic” conception of the distance between places.
The notion of geographical location (situation géographique in French) belongs to “classical” geography, appearing very early in the history of the discipline as a major way of explaining inequalities in the concentration of populations, wealth, or certain activities. It defines, to a certain extent, the added value of a location by its position, relative to other locations, therefore by its greater or lesser distance from other locations. The situational advantage is often a better accessibility, i.e. a shorter distance from a number of other places where wealth is produced or circulates. Geographical location is advantageous when the topography improves the accessibility of the place by reducing its access distances: this is how the development of cities located at the crossroads of large valleys or at the maritime outlet of a major land route, such as that of estuary cities, was explained in the 19th Century. Geographical location is also considered more favorable when traffic conditions are easy, relatively reducing distances, e.g. in lowland areas as opposed to mountainous regions. The so-called “contact” situation is the one that makes additional resources close to the sites. The time and cost savings associated with distance travel, when they persist long enough, thus become
important components in explaining concentrations and accumulations of population and activities in the territories.
Distance is a decisive factor in many location models, which represent the effects of “location rents”, which complement those of fertility rents or resource sites. Weber’s optimal industrial location model, developed around 1900, combines distances to sites (raw materials, markets, and labor) to estimate the best possible position for a production plant, minimizing transport costs; the von Thünen agricultural specialization zone model, developed in 1826, uses distance to the urban market and the differential rent it generates as the main explanation for land-use choices.
Some effects of distance are so systematic that they result in repeated configurations, which arise in the spatial organization of most societies at different times, and which are broadly identified as “center-periphery structures”. These are forms of geographical space without precise but highly organized boundaries, a bit like a magnetic field, with a gradient of decreasing intensity as a function of the distance around a pole. The measurement of the relationship between places that define these spaces in the form of fields is then a flow, a quantity of exchanges, a frequency or intensity of relationships (number of commuters between places of residence and work, number of customers between a service provision center and the places surrounding it, number of telephone calls, origins of migrants and goods or investments attracted by a center). These configurations could admittedly be explained as society taking into account the laws of physics because it is a question of saving energy, thus minimizing an expense that then weighs as a constraint on the dynamics of social activities in space. By playing on the similarity between physical and anthropological expressions, the statistician G. K. Zipf (1949) also proposed calling this universal propensity to cut as short as possible and to go as close as possible, “the law of the least effort”, which amounts to organizing activities and movements according to distance.
However, the origin of these almost geometric configurations, generally circular, can also be found elsewhere. Distance explains the shape they take: it does not explain why and how they are formed. The geographical space produced by the societies is oriented (anisotropic). Some places, selected as centers, acquire a social, symbolic, and economic value, which makes them centers where flows of people, energy, materials, and information from the periphery converge. More often than not, this attraction is explained by the fact that the center exercises domination, which may be political, military,