Spatio-temporal Approaches E-Book

Hélène Mathian

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 311

Veröffentlichungsjahr: 2014

Beschreibung

Spatio-temporal Approaches presents a well-built set of concepts, methods and approaches, in order to represent and understand the evolution of social and environmental phenomena within the space. It is basedon examples in human geography and archeology (which will enable us to explore questions regarding various temporalities) and tackles social and environmental phenomena. Chapter 1 discusses how to apprehend change: objects, attributes, relations, processes.

Chapter 2 introduces multiple points of view about modeling and the authors try to shed a new light on the different, but complementary approaches of geomaticians and thematicians. Chapter 3 is devoted to the construction of spatio-temporal indicators, to various measurements of the change, while highlighting the advantage of an approach crossing several points of view, in order to understand the phenomenon at hand. Chapter 4 presents different categories of simulation model in line with complexity sciences. These models rely notably on the concepts of emergence and self-organization and allow us to highlight the roles of interaction within change. Chapter 5 provides ideas on research concerning the various construction approaches of hybrid objects and model couplings.

Leseprobe

Contents

Introduction

1 Building Objects in Time

1.1. Different points of view on ontology

1.2. Locating spatial objects in time

1.3. Conclusion

2 From Empirical Questioning to Spatiotemporal Modeling

2.1. From the conception of entities to their analysis of responding to thematic issues

2.2. Challenges and models: the possible misunderstandings

2.3. Application examples

2.4. Conclusion

3 Analyzing Spatio-temporal Data: Empirical and Statistical Approaches

3.1. Statistical data and spatio-temporal analysis

3.2. Following the evolution of the structure of spatial systems

3.3. Understanding the evolution of a spatial system’s entities

3.4. Conclusion

4 Exploring the Underlying Processes of Change: Simulation Models

4.1. Computer simulation versus statistical approach: different points of view about explanation

4.2. Microsimulation models

4.3. Computing models: simulation and emergence

4.4. Conclusion

Conclusion

Bibliography

Index

First published 2014 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 Ltd27-37 St George’s RoadLondon SW19 4EUUKwww.iste.co.uk

John Wiley & Sons, Inc.111 River StreetHoboken, NJ 07030USAwww.wiley.com

© ISTE Ltd 2014The rights of Hélène Mathian and Lena Sanders to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.

Library of Congress Control Number: 2014947782

British Library Cataloguing-in-Publication DataA CIP record for this book is available from the British LibraryISSN 2051-2481 (Print)ISSN 2051-249X (Online)ISBN 978-1-84821-552-8

Introduction

The objective of this book is to introduce a constructed set of concepts, methods and approaches to represent and understand the evolution of social and environmental phenomena embedded in space. It relies on applications concerning not only human geography (field in which the authors have most practical experience), but also environmental geography and archeology in order to test the genericity of the proposed approaches. These three disciplinary fields are actually different on the thematic level, but they share similar epistemological and methodological stakes. Indeed, irrespective of the phenomenon (whether it is about monitoring glaciers in the context of climate change, about urban sprawl and the consequences of metropolitanization or about the transformations of the landscape), the aim is to consider how it is embedded in space and how it evolves over time. The ways of combining theme, space and time are discussed both in social and natural sciences, and it has given rise to numerous formalizations. In 1960s, Berry (pioneer of the “New Geography”) proposed the concept of the “geographic information matrix” to apprehend these three-dimensions in geography [BER 64]. The “triad” (what, where and when), of geomatics inspiration, was developed by Peuquet in 1980s in the context of development of geographical information systems (GIS)1 [PEU 84]. These approaches were then enriched by referring to the work of philosophers. Galton, for example, proposed the concept of “hyperobject” for an approach fully integrating space and time [GAL 04]. All these approaches will be combined here.

The book clearly falls within the scope of the field named “spatial analysis”. Definitions about it are various, some highlight the more technical aspects, others insist on the methodological aspects and others finally propose a more comprehensive scientific vision. Our positioning is located at the interface of two definitions: – for the first, spatial analysis is “the formalized study of the configuration and the properties of the produced and lived space of human societies” [PUM 97]; – in the second, spatial analysis is a “set of techniques and models that apply formal structures, generally quantitative, to systems in which the main variable evolves significantly through space” [LON 96]. These two definitions put forward the principle of a formal approach, either at the conceptual, observation or measurement level. Our approach relies on a systematic coming and going between these two definitions, each one supporting the other. We will multiply the points of views about each concept and each method, comparing, for example, the points of view of the philosopher and computer scientist on questions of ontology, those of the geomatician and philosopher on spatiotemporal concepts, those of the statistician and simulation modeler to explain the evolution of societies, of their spaces and environments. Thus, the objective is to articulate concepts from information science, complex systems theory and thematic fields. The latter concern not only geography but also archeology that offers, through the temporalities involved, very stimulating stakes to reflect upon the spatiotemporal approaches.

The models occupy a central place in spatial analysis. Rather than deepening the technical aspects that are related to them, the choice has been made to clarify and discuss different modeling approaches and to emphasize the multiplicity of points of view. “Model” is a polysemic term, and misunderstandings may emerge when specialists in different areas collaborate, notably as far as we are concerned here, computer scientists, geomaticians, geographers and archaeologists. Two definitions, here again, very well reflect, in their complementarity, the position adopted in this book:

– “The model is a schematic representation of reality, developed with the purpose of understanding reality and explaining it” (Haggett [HAG 65] and Durand- Dastès [DUR 92]);

– “To an observer B, an object A* is a model of an object A to the extent that B can use A* to answer questions that interest him about A” (Minsky, [MIN 65]).

While assuming a solid anchorage into reality, an aspect stressed in the first definition, it also seems essential to adopt the distantiation from reality that the second definition implies. This distantiation allows, as a matter of fact, reasoning not only on what may have existed, but also on what could have happened or could eventually happen in the future. In both cases, the model is a scientific support tool for reflection.

The risk of misunderstanding with regard to the term “model” is accentuated by the fact that, faced with a given problematic, the models that are mobilized at different stages of the research are of a different nature: conceptual model, data model, statistical model and computer simulation model. Rather than confining ourselves to a particular point of view, our objective is precisely to address the concept of models in a broad manner: models to build objects, to generate, manage and describe information, models to explain and understand spatial phenomena and their evolutions. The emphasis will be on the conceptual framework rather than on the technical and operational aspects that can easily be deepened elsewhere. In order to explore and analyze relationships in space and time, we will favor the application of simple, classic, robust statistical methods, of common use and accessibility in social science, by showing how certain couplings or sequences allow addressing complex issues. When this is necessary relative to the problematics, especially when it comes to understanding how structures emerge from the interactions between elementary entities, the methods coming from complex systems theory will be called into action. The privileged modeling methods from this domain, such as cellular automata and multiagent systems, which allow simulating the emergence of spatial structures from the interactions between entities considered as elementary, will be, therefore, presented.

Space will be apprehended in a multiscale manner, with a thorough reflection on the meaning of the entities that make it up, and privileging a systemic perspective, with particular attention paid to the interactions operating in space according to different temporalities. The manner in which the concept of system is called upon in spatial analysis has become richer over the past decades. In its simplest definition, a system is a set of entities that interact and hence form, a whole, which has limits, and which is distinguishable from its environment. The expression “the whole is more than the sum of the parts” is classically associated with this vision. Thus, a spatial system is a system composed of a set of spatial entities interacting, for example, system of cities, settlement system, system of land use and landscape system. For over a decade now, human and social sciences have been focusing on the field of complex systems that offer the advantage of taking into account several levels of entities: “complex systems consist of qualitatively different organizational strata, in particular, a microlevel and a macrolevel. Between them there exist a “bottom up” and “top down” interaction, i.e. a quasi-cyclical causal relation” [WEI 06]. Spatial analysis is further concerned with a whole set of intermediary levels which qualify as meso-geographical. The diversity of these levels and of the entities that are associated with them is today renewed through the proliferation of fine-grained data allowing for a great variety of aggregations. In addition to the effects from nesting different levels, Dauphine and Provitolo [DAU 13] identify two other sources of complexity. On the one hand, a number of simple systems on the formal plan may show erratic and unpredictable behaviors (properties that have significantly mobilized mathematicians and physicists from complex systems theory). On the other hand, in a multidimensional context, the significant number of domains interacting represents an additional source of complexity, especially when environmental and human systems interact.

This systemic design implies identifying and clarifying the multiple interactions between the entities of a same level (horizontal interactions) and between the levels that constitute the system (vertical interactions). To use the expression of Irwin and Geoghegan [IRW 01], our position is closer to the “creative” use of spatiotemporal data and further from the question of the “correct” use. The latter has given rise to a large number of specific developments to respond to essential statistics issues such as the correction of the effects of spatial dependency or of process heterogeneity in space [GRI 91, ANS 95, DUB 14] etc. Actually, geographers, historians and archaeologists have strong assumptions on the role that space plays or may play in observed phenomena. We have placed the emphasis on how we can take it into account in formalizing space, as well as time, and integrating them in the analyses. The most common way of taking space into account is without any doubt through the distance to a structuring element. The challenge lies in moving beyond this single linear formalization of space and introducing either multiscale effects (for example, through the multiple and overlapping influences of centers of different levels according to their distance), or other formalizations such as neighborhoods, territorial contexts and even going to the point of integrating “fuzzy” belongings. Space is no longer only analyzed to understand similarities but also to extract differences [FOT 00]. We are committed to building information and also integrating results of models based on assumptions (for example, the potential model) to bring original and useful insight.

The pedagogical aspects will not be overlooked, but it seemed to us essential to present applications that were “life-size” and not overly simplified. The choice was, therefore, made to privilege examples derived from research practice, considered in all their complexity and richness. In practice, the spatiotemporal problematics contains, in general, two sources of complexity: – the objects of interest themselves, often of multiscale and evolving character, that have to be built in order to follow them (identity and change); – the approaches adopted that may be hybrid, or include couplings, or sequences of methods. A crossbreeding of these two aspects is necessary to describe complex phenomena and to understand the functioning of spatial systems such as settlement systems, educational systems, socioenvironmental relationships, river systems, etc. The objective is to propose a generic framework to conduct such an approach in the context of social sciences where each analysis is not an end in itself (“flawless piece of result”), but a useful brick in the construction of the knowledge of the phenomenon analyzed [FOT 00].

The book is organized into four chapters (Figure I.1).

Figure I.1.Book structure and relationships between chapters

Chapter 1 is devoted to the design and construction of objects, attributes, relationships and processes that are associated with the problematics raised. We defend the idea that the quality of the formalization upstream, irrespective of the degree of sophistication of further processing applied, is a necessary condition for ensuring the relevance of the results. With the enlargement of the observation fields (fineness of temporal and spatial granularity and multiplication of observation means), the reflection on the meaning of the entities of interest has to be intensified.

Chapter 2, entitled “From Empirical Questioning to Spatio-Temporal Modeling”, is dedicated to the transition, more delicate than most often thought a priori, between the thematic questions formulated by the researcher or practitioner, the adequate methods to answer them and the observable entities available. In this chapter, we clarify the potential gaps between these three sets, and we exemplify the sequence of methods related to specific issues. This chapter represents a connection between Chapter 1 and Chapters 3 and 4, in the sense that it enlightens the categories discussed from a theoretical point of view in Chapter 1 and introduces through practical examples the problematics that are then deepened in the following two chapters.

Chapters 3 and 4 address the practices developed to present and understand the change of spatial systems, both at the level of the elementary entities that make them up and that of the systems-entities themselves. Chapter 3 is dedicated to the description and statistical explanation, the ways of studying how the interrelationships between different phenomena embedded in space evolve. Chapter 4 deals directly with the processes at stake during change and the modeling of the mechanisms underlying these processes. Particular emphasis is put on computer simulation methods. Figure I.1 illustrates the position of these two chapters in direct relation with the first two and how they complement one another.

1Geographical information system (GIS) refers to the computing environment integrating methods and tools for the process of geographical information, whereas geographical information science or geomatics refer to the set of concepts and methods underlying the processing of geographical information.

1

Building Objects in Time

The world is composed of “things” that we conceptualize as objects “with the purpose of building knowledge from it” [DEB 04]. Information is increasingly more abundant. It is also available at more diverse granularity levels due to technological progress in the field of acquisition and storage. In such a context, the possibilities of observation are multiplying for the researcher. From this multiplication of possibilities arises the need to choose, and especially that of clarifying the choices made: reflection first on the objects that we consider as relevant relative to the problems posed (conceptual dimension); choice then of the observable entities that will allow us to study these objects of interest (empirical dimension); choice finally of what we will observe about the characteristics and behaviors of these objects (heuristic dimension). Therefore, the purpose is to build objects from observable “things” in the empirical world, and to give them a meaning relative to the problematics at stake. This path is not always as immediate as we would like. Two concrete examples can illustrate it effectively :