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A Research Agenda for Spatial Analysis
This Research Agenda explores the future of spatial analysis, and how the field informs and challenges the policy landscape. A wide range of contributors from different intellectual communities address the problem of causality in geographic analysis, arguing that diversity is crucial for the future success of the discipline.
This title contains one or more Open Access chapters.
This title contains one or more Open Access chapters.
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Critical Acclaim
Contributors
Contents
More Information
Elgar Research Agendas outline the future of research in a given area. Leading scholars are given the space to explore their subject in provocative ways, and map out the potential directions of travel. They are relevant but also visionary.
This Research Agenda explores the future of spatial analysis, and how the field informs and challenges the policy landscape. A wide range of contributors from different intellectual communities address the problem of causality in geographic analysis, arguing that diversity is crucial for the future success of the discipline.
Chapters define and explore specific concepts and practices within the field, for instance data science and geosimulation, providing perspectives on the current state of the art of these areas within geography, and how they will shift in the future. In the first section, contributors cover the fundamentals of the topic, as well as various ways to handle the ‘spatial variable’, including the concept of space, the scale of spatial patterns and what those patterns reveal. The book then analyses schools of practice, including geographical data science, causality, generative modelling and machine learning.
A Research Agenda for Spatial Analysis will prove an invaluable resource for spatial analysts and geographic information scientists interested in learning about the direction of future developments in the field. Additionally, scholars and students of human and urban geography and geographic research methods will benefit from this crucial overview of the topic.
This Research Agenda explores the future of spatial analysis, and how the field informs and challenges the policy landscape. A wide range of contributors from different intellectual communities address the problem of causality in geographic analysis, arguing that diversity is crucial for the future success of the discipline.
Chapters define and explore specific concepts and practices within the field, for instance data science and geosimulation, providing perspectives on the current state of the art of these areas within geography, and how they will shift in the future. In the first section, contributors cover the fundamentals of the topic, as well as various ways to handle the ‘spatial variable’, including the concept of space, the scale of spatial patterns and what those patterns reveal. The book then analyses schools of practice, including geographical data science, causality, generative modelling and machine learning.
A Research Agenda for Spatial Analysis will prove an invaluable resource for spatial analysts and geographic information scientists interested in learning about the direction of future developments in the field. Additionally, scholars and students of human and urban geography and geographic research methods will benefit from this crucial overview of the topic.
Critical Acclaim
‘A thought-provoking volume, condensing pressing and interesting issues in contemporary spatial analysis into one compact package, and, indeed, offering so much more than agenda setting: a bird’s eye perspective on key challenges in spatial analysis, a conversation starter, and a manifesto that will appeal to students, researchers, and practitioners, alike.’
– Rachel Franklin, Newcastle University, UK
‘This series of thought-provoking chapters offers a fresh perspective on core concepts and application areas in the evolving interdisciplinary field of spatial data science, situated in the context of the new era of big data and machine learning. An invaluable source of inspiration for anyone embarking on new research projects.’
– Luc Anselin, University of Chicago, US
‘The editors have done a magnificent job of assembling insightful essays that present key themes in spatial analysis, such as scale, pattern, process and interaction, in ways that can be used to define many different geographies whilst enabling a synthesis of geospatial ideas to be established. This is important reading for everyone who has a concern for the application of geographical science to the grand challenges that manifest themselves spatially.’
– Michael Batty, CASA, University College London, UK
– Rachel Franklin, Newcastle University, UK
‘This series of thought-provoking chapters offers a fresh perspective on core concepts and application areas in the evolving interdisciplinary field of spatial data science, situated in the context of the new era of big data and machine learning. An invaluable source of inspiration for anyone embarking on new research projects.’
– Luc Anselin, University of Chicago, US
‘The editors have done a magnificent job of assembling insightful essays that present key themes in spatial analysis, such as scale, pattern, process and interaction, in ways that can be used to define many different geographies whilst enabling a synthesis of geospatial ideas to be established. This is important reading for everyone who has a concern for the application of geographical science to the grand challenges that manifest themselves spatially.’
– Michael Batty, CASA, University College London, UK
Contributors
Contributors include: Daniel Arribas-Bel, Luke Bergmann, Christopher Brunsdon, James Cheshire, Clémentine Cottineau, Urška Demsar, Adam Dennett, A. Stewart Fotheringham, Anita Graser, Gareth Griffith, Richard Harris, Alison Heppenstall, Stephen Law, Robin Lovelace, David Manley, Trisalyn Nelson, Ana Petrović, Francisco Rowe, Yao Shen, Michelle Stuhlmacher, David O’Sullivan, Gwylim Owen, Maarten Van Ham, Levi John Wolf, Meng Le Zhang, Chen Zhong
Contents
Contents:
Introduction to A Research Agenda for Spatial Analysis 1
Richard Harris, Alison Heppenstall and Levi John Wolf
PART I CONCEPTS IN SPATIAL ANALYSIS
1 Linking spatial pattern to process: an old
challenge with new barriers 13
Trisalyn A. Nelson
2 Reconstructing the map 27
James Cheshire
3 Space: towards a global sense of place 39
Luke Bergmann and David O’Sullivan
4 How to solve the scale “problem” in spatial analytics 55
A. Stewart Fotheringham
5 Reproducible research, and research into
reproducibility: review and prospects 67
Chris Brunsdon
PART II COMMUNITIES OF PRACTICE IN SPATIAL ANALYSIS
6 Geographic data science: a manifesto 85
Daniel Arribas-Bel and Anita Graser
7 Causal, not casual, spatial data science 97
Gareth Griffith, Gwylim Owen and Meng Le Zhang
8 Generative modelling and geosimulation 113
Clémentine Cottineau
9 Progress on machine learning applications in geography 127
Stephen Law, Yao Shen and Chen Zhong
10 Earth observation 147
Michelle Stuhlmacher
11 Integrated science of movement: crossing the
boundary between human mobility and animal
movement research 159
Urška Demšar
12 Spatial interaction modelling: a manifesto 177
Francisco Rowe, Robin Lovelace and Adam Dennett
13 The neighbourhood: where Wilson, Schelling and
Hägerstrand meet 197
Ana Petrović, Maarten van Ham and David Manley
Conclusion: spatial analysis – the geographer’s art? 209
Richard Harris, Alison Heppenstall and Levi John
Wolf
Introduction to A Research Agenda for Spatial Analysis 1
Richard Harris, Alison Heppenstall and Levi John Wolf
PART I CONCEPTS IN SPATIAL ANALYSIS
1 Linking spatial pattern to process: an old
challenge with new barriers 13
Trisalyn A. Nelson
2 Reconstructing the map 27
James Cheshire
3 Space: towards a global sense of place 39
Luke Bergmann and David O’Sullivan
4 How to solve the scale “problem” in spatial analytics 55
A. Stewart Fotheringham
5 Reproducible research, and research into
reproducibility: review and prospects 67
Chris Brunsdon
PART II COMMUNITIES OF PRACTICE IN SPATIAL ANALYSIS
6 Geographic data science: a manifesto 85
Daniel Arribas-Bel and Anita Graser
7 Causal, not casual, spatial data science 97
Gareth Griffith, Gwylim Owen and Meng Le Zhang
8 Generative modelling and geosimulation 113
Clémentine Cottineau
9 Progress on machine learning applications in geography 127
Stephen Law, Yao Shen and Chen Zhong
10 Earth observation 147
Michelle Stuhlmacher
11 Integrated science of movement: crossing the
boundary between human mobility and animal
movement research 159
Urška Demšar
12 Spatial interaction modelling: a manifesto 177
Francisco Rowe, Robin Lovelace and Adam Dennett
13 The neighbourhood: where Wilson, Schelling and
Hägerstrand meet 197
Ana Petrović, Maarten van Ham and David Manley
Conclusion: spatial analysis – the geographer’s art? 209
Richard Harris, Alison Heppenstall and Levi John
Wolf
