Book Image

Applied Geospatial Data Science with Python

By : David S. Jordan
3 (1)
Book Image

Applied Geospatial Data Science with Python

3 (1)
By: David S. Jordan

Overview of this book

Data scientists, when presented with a myriad of data, can often lose sight of how to present geospatial analyses in a meaningful way so that it makes sense to everyone. Using Python to visualize data helps stakeholders in less technical roles to understand the problem and seek solutions. The goal of this book is to help data scientists and GIS professionals learn and implement geospatial data science workflows using Python. Throughout this book, you’ll uncover numerous geospatial Python libraries with which you can develop end-to-end spatial data science workflows. You’ll learn how to read, process, and manipulate spatial data effectively. With data in hand, you’ll move on to crafting spatial data visualizations to better understand and tell the story of your data through static and dynamic mapping applications. As you progress through the book, you’ll find yourself developing geospatial AI and ML models focused on clustering, regression, and optimization. The use cases can be leveraged as building blocks for more advanced work in a variety of industries. By the end of the book, you’ll be able to tackle random data, find meaningful correlations, and make geospatial data models.
Table of Contents (17 chapters)
1
Part 1:The Essentials of Geospatial Data Science
Free Chapter
2
Chapter 1: Introducing Geographic Information Systems and Geospatial Data Science
6
Part 2: Exploratory Spatial Data Analysis
10
Part 3: Geospatial Modeling Case Studies

Introducing geospatial databases and storage

This section will introduce you to geospatial databases and storage software. Let’s begin the discussion with PostgreSQL and PostGIS.

PostgreSQL and PostGIS

PostgreSQL is an open source, object-relational database system that uses Structured Query Language (SQL). PostgreSQL runs on all major operating systems and has been praised for its architecture, scalability, reliability, and extensibility. While PostgreSQL isn’t spatially enabled by default, it can be spatially enabled through the use of the PostGIS database extender.

PostGIS is a project of the Open Source Geospatial Foundation (OSGeo). PostGIS adds spatial operations such as distance, area, union, and intersection, as well as spatial geometry, to the standard PostgreSQL database. If you’ve worked with a standard database in the past, then you’re likely familiar with its row-by-column storage structure as well as its ability to join different sets...