Categories: GIS Career and Jobs

Download these Free GIS, Analytical, and Programming eBooks from Springer

If you’re looking for free digital books covering GIS, analysis, and programing to improve your geospatial skills, Springer has eBooks you can download from its site. Books can be downloaded in PDF and EPub formats.


H/T Olivia Powell

GIS Books

Python for ArcGIS

By Laura Tateosian, 2015. This book introduces Python scripting for geographic information science (GIS) workflow optimization using ArcGIS. Python for ArcGIS contains 200 sample Python scripts and 175 classroom-tested exercises reinforce the learning objectives. Download: Python For ArcGIS

ArcGIS for Environmental and Water Issues

William Bajjali, 2018. This book contains step-by-step tutoriasl on the applications of Geographic Information Systems (GIS) in environmental and water resource issues. Download: ArcGIS for Environmental and Water Issues


Data Analysis

Siegmund Brandt, 2014. The fourth edition of this textbook presents a comprehensive introduction to statistical and numerical methods for the evaluation of empirical and experimental data. Download: Data Analysis


Vít Pászto, Carsten Jürgens, Polona Tominc, & Jaroslav Burian, eds., 2020. This open access book is based on “Spationomy – Spatial Exploration of Economic Data”, an interdisciplinary and international project in the frame of ERASMUS+ funded by the European Union. Download: Spationomy

Maritime Spatial Planning

Jacek Zaucha & Kira Gee, 2019. The authors and contributors examine marine spatial planning from disciplines as diverse as geography, urban planning, political science, natural science, sociology and education; reflecting the growing critical engagement with MSP in many academic fields. Download: Maritime Spatial Planning


An Introduction to Machine Learning

Miroslav Kubat, 2017. This textbook presents fundamental machine learning concepts. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Download: An Introduction to Machine Learning

Time Series Analysis

Jonathan D. Cryer and Kung-Sik Chan, 2008. Time Series Analysis With Applications in R, Second Edition, presents an accessible approach to understanding time series models and their applications. Download: Time Series Analysis


The Python Workbook

Ben Stephenson, 2014. The Python Workbook focuses exclusively on exercises, following the philosophy that computer programming is a skill best learned through experience and practice. Download: The Python Workbook

Data Structures and Algorithms with Python

Kent D. Lee & Steve Hubbard, 2015. This textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently.

Introductory Statistics with R

Peter Dalgaard, 2008. This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. Download: Introductory Statistics with R

A Beginner’s Guide to R

Alain F. Zuur, Elena N. Ieno, & Erik H. W. G. Meesters, 2009. This book covers how to download and install R, import and manage data, elementary plotting, an introduction to functions, advanced plotting, and common beginner mistakes. Download A Beginner’s Guide to R



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