Handling and Mapping Geographic Information / Claire Cunty and Hélène Mathian.

Format:

Book

Author/Creator:

Cunty, Claire, author.

Mathian, Hélène, author.

Series:

ISTE Consignment Series

Language:

English

Subjects (All):

Cartography.

Physical Description:

1 online resource (327 pages)

Edition:

First edition.

Place of Publication:

London, England : ISTE, [2024]

Summary:

With the increasing proliferation of data and the systematization of geographic information referencing, maps are now a major concern - not only for specialists, but also for urban planning and development organizations and the general public. However, while producing a map may seem straightforward, the actual process of transforming data into a useful map with a specific purpose is characterized by a series of precise operations that require knowledge in a variety of fields: statistics, geography, cartography and so on. Handling and Mapping Geographic Information presents a wide range of operations based on a variety of examples. Each chapter adopts a different approach, explaining the methodological choices made in relation to the theme and the pursued objective. This approach, encompassing the entire map production process, will enable all readers, whether students, researchers, teachers or planners, to understand the multiple roles that maps can play in the analysis of geographical data.

Contents:

Cover

Title Page

copyright Page

Contents

Foreword

Introduction

Chapter 1. Exploring Statistical Relationships with Maps and Charts

1.1. Introduction

1.2. Mapping the world: which world? what data?

1.2.1. Planispheres, projections and centers

1.2.2. Grid-related issues

1.2.3. Data at global scale: a composite material

1.3. Exploring data and relationships with maps and charts

1.3.1. Exploring statistical relationships and spatial organizations

1.3.2. Formalizing a relationship: from a statistical model to the map of model deviations

1.4. Describing statistical relationships between several variables

1.5. Conclusion

1.6. References

Chapter 2. Heterogeneous Data Integration and Geoweb Cartographic Representations

2.1. Introduction

2.2. New data: from production to visualization

2.2.1. New data production methods and new scientific applications

2.2.2. Data with high spatial and temporal resolution but poorer attributes and quality?

2.2.3. Visualizing new data on Web platforms

2.3. New data, traditional data: why and how to integrate them?

2.3.1. Data heterogeneity, integration, interoperability: preamble to vocabulary development

2.3.2. Visual overlay of heterogeneous data, facilitated by advances in technical interoperability

2.3.3. Term-to-term matching to assess the quality and enrich the attributes of new data

2.3.4. Aggregations for combining heterogeneous data within "pivotal" spatiotemporal units

2.3.5. Interpolated data measuring two continuous phenomena to compare them within a common grid

2.4. Conclusion

2.5. References

Chapter 3. Environmental Data and Cartographic Objects

3.1. Introduction

3.1.1. Defining cartographic objects: positioning the problem

3.1.2. Specific environmental data.

3.2. Building cartographic objects: deconstructing to reconstruct

3.2.1. From geographic object to cartographic object

3.2.2. A few reminders on set theory

3.2.3. Defining objects and collecting data

3.3. Dealing with disparate and incomplete data: examples from environmental geography

3.3.1. Defining cartographic objects from incomplete data

3.3.2. Defining cartographic objects at reference scales

3.4. Conclusion

3.5. References

Chapter 4. Mapping and Identifying Geographic Configurations: The Example of Segregation

4.1. Introduction

4.2. Mapping: rendering spatial configurations visible or invisible

4.2.1. Defining the study framework

4.2.2. The scale of spatial configurations: a question of geographic mesh

4.2.3. How the map is created

4.3. How to measure a phenomenon so as to reveal its forms

4.3.1. The dependence of measures to the definition of categories

4.3.2. The indices approach

4.3.3. Multivariate analysis approach: qualifying segregated neighborhoods

4.4. Capturing spatial forms using dynamic approaches

4.4.1. Why a dynamic approach to spatial morphologies?

4.4.2. Approaches using spatial indices or spatial autocorrelation

4.4.3. Approach based on discontinuities

4.4.4. Approach based on population potential

4.5. Conclusion

4.6. References

Chapter 5. Map and Statistical Model to Explore Spatial Heterogeneity

5.1. Introduction

5.2. From raw open-source data to statistical data

5.2.1. Open-source data with a complex structure

5.2.2. Object of study and scale of analysis

5.3. Preliminary explorations of spatial variations

5.3.1. Maps to explore the spatial structure of each variable

5.3.2. Testing the hypothesis of an administrative or spatial effect in spatial organization

5.4. Analyzing relationships statistically and rendering a map.

5.4.1. Hedonic regression principles

5.4.2. Model with no spatial attributes

5.4.3. Spatial model estimated by GWR

5.5. Conclusion

5.6. References

Chapter 6. Mapping Time

6.1. Introduction

6.2. Formalization

6.2.1. Spatial objects and their temporal component

6.2.2. From spatiotemporal objects to spatiotemporal data

6.2.3. From geographic data to cartographic data

6.2.4. Visualizing time

6.3. Monitoring territorial changes

6.3.1. Visualizing temporal phenomena

6.3.2. Representing changes

6.4. Representing phenomena associated with movement

6.4.1. Representing movements: from points to trajectories

6.4.3. Shape changes

6.5. Representing temporality

6.5.1. Tracking the spatial organization of events

6.5.2. Representing lifespan, duration and change

6.5.3. Representing space-time

6.6. Conclusion

6.7. References

Chapter 7. Cartograms, Anamorphic Maps: Transformed Territories

7.1. Introduction

7.2. Cartograms to represent count data associated with areal units

7.2.1. Why use cartograms?

7.2.2. Links between methods and data

7.2.3. Anatomy of the cartogram: methods

7.2.4. The piezopleth map to represent rates associated with areal units

7.3. Anamorphic map for the representation of space-time

7.3.1. Accessibility to a place (unipolar accessibility)

7.3.2. Accessibility between all places (multipolar accessibility)

7.3.3. Azimuthal transformation

7.4. Anamorphic maps, cartograms: cross-cutting reflections on common principles and reading difficulties

7.4.1. Some principles underlying all methods

7.4.2. Anamorphic maps layout

7.4.3. Reading and understanding anamorphic maps: some difficulties

7.5. Conclusion

7.6. References

Chapter 8. Exploration, Aggregation and Spatiotemporal Visualization of Big Data

8.1. Introduction.

8.2. Defining the object of study and selecting the corpus

8.2.1. Press news: a multidimensional object

8.2.2. Defining international news

8.2.3. Corpus definition based on RSS news feeds

8.3. Crossing the "who" and "what" dimensions

8.4. Crossing the "who", "what" and "when" dimensions

8.4.1. Detecting trends

8.4.2. Analysis of seasonal variations

8.4.3. Analysis of weekly variations

8.5. Crossing the "who", "what" and "where" dimensions

8.5.1. Mapping the distribution of international news by country

8.5.2. Identifying and mapping specific national features

8.6. Graphs to represent co-location relationships

8.6.1. Measuring and visualizing association links

8.6.2. From co-citations to global regionalization

8.7. Conclusion

8.8. References

Conclusion

List of Authors

Index

EULA.

Notes:

Description based on publisher supplied metadata and other sources.

Description based on print version record.

ISBN:

9781394325788

1394325789

9781394325771

1394325770

9781394325764

1394325762

OCLC:

1457920419