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Geospatial Modeling with Python

Sergio Souza Costa — LambdaGEO, UFMA

This book is a practical guide to geographic data science and discrete spatial simulation using the Python ecosystem.

It is organized in three parts:

  • Part I — Python for Data Science
    Core tools: Pandas, EDA, software engineering.

  • Part II — Geographic Data Science
    Spatial data types, GeoPandas, rasterio, libpysal, visualization.

  • Part III — Discrete Spatial Modeling
    Cellular automata, salabim, NumPy vectorization, and the DisSModel framework — including a full coastal dynamics case study.

How to Use This Book

Each chapter is a Jupyter notebook. You can read it as a book or run it interactively. Code cells are self-contained within each chapter.

Installation

pip install dissmodel>=0.2.0 geopandas rasterio libpysal salabim

For the coastal dynamics case study (Chapter 18):

pip install coastal-dynamics

Source Code

All notebooks and supporting code are available at:

Citation

If you use this material in your research or teaching, please cite:

Costa, S. S. (2026). Geospatial Modeling with Python.
LambdaGEO Research Group, Federal University of Maranhão (UFMA).
https://lambdageo.github.io/geospatial-modeling-book

LambdaGEO Research Group · Federal University of Maranhão (UFMA)
lambdageo.github.io