Geographical data can reveal patterns in where things happen, how places differ, and how spatial relationships change what we conclude. But making sense of those patterns requires more than producing a map or calculating a statistic. We need to ask useful questions, choose appropriate methods, examine uncertainty, and communicate findings responsibly.
This open book brings statistical reasoning, spatial analysis and geovisualisation together as complementary ways of understanding geographical phenomena. It is written for students, educators and practitioners who want to learn independently or use selected chapters as a reference. Examples from Singapore and the wider region connect concepts to real geographical data.
How to use this book¶
Part 1 — Core Chapters introduces geographical and statistical thinking, spatial data, statistical comparisons, point patterns, areal patterns, and geovisualisation and storytelling.
Part 2 — Worked Examples provides applications that connect questions, methods and interpretation.
Part 3 — Data and Notebooks offers Python-based materials for exploring and reproducing selected analyses.
Part 4 — Lecture Slides preserves the course-aligned teaching slides for readers who find the visual summaries useful.
Start with Chapter 1 if you are new to the subject, or go directly to a topic of interest. The core chapters combine explanations, figures, worked examples, and self-check activities. Some sections offer optional deeper reading. Python notebooks support hands-on exploration, but the conceptual chapters can also be read without running code.
What you will learn¶
By working through the book, you should be able to:
Formulate geographical questions and think critically about data and spatial representation.
Describe, compare and interpret statistical, point and areal patterns.
Recognise how spatial context, analytical choices and uncertainty affect interpretation.
Explore selected methods through Python examples and reproducible notebooks.
Communicate geographical evidence through clear and responsible visualisation.
Origins and authorship¶
This book is developed and maintained by Benny Chin, Department of Geography, National University of Singapore (NUS). It grew from materials originally prepared for GE5230 Geospatial Statistics and Visualisation, taught in the MSc in Applied GIS programme. The book is now presented as a wider learning resource; it is not restricted to that course. The lecture slides and some notebooks retain their original course-specific context.
Licensing¶
Parts 1 and 2 — concepts and worked examples. Original text, explanations and project-created figures are licensed under Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International (CC BY-NC-ND 4.0). Redistribution of adaptations, including translations, requires separate permission from the applicable rights holders.
Part 3 — code and notebooks. Original executable code cells and reusable scripts are licensed under the MIT License. The accompanying prose, learning questions, illustrations and other original non-code materials in notebooks retain the book’s CC BY-NC-ND 4.0 licence.
Part 4 — lecture slides. Original project-owned slide text and graphics are subject to CC BY-NC-ND 4.0. Embedded third-party images, diagrams or resources retain their respective rights and must be assessed individually.
External datasets and other third-party materials — all parts. Each dataset, boundary, geocoding source, background map or reused asset retains its provider’s applicable licence and attribution requirements. The project’s CC and MIT licences do not relicense these resources. Refer to the dataset catalogue and third-party sources and licensing inventory.
© 2026 Benny Chin for original material, subject to other rights holders’ contributions and licences.