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)
Part 1:The Essentials of Geospatial Data Science
Free Chapter
Chapter 1: Introducing Geographic Information Systems and Geospatial Data Science
Part 2: Exploratory Spatial Data Analysis
Part 3: Geospatial Modeling Case Studies

Geospatial file formats

As mentioned at the start of this chapter, geospatial data is data with a geographic component. This geographic component is often a latitude and longitude coordinate that is collected via a global positioning system (GPS). A geographic component can also be derived from an address using a process called geocoding. However, there are also many other geographic components that can relate tabular, or attribute, data to standard administrative geographies. We’ll talk more about administrative boundaries at length later in our discussion on vector data. It is also worth noting that geospatial data is a subset of spatial data or data that is related to a point in some broader study space.

Vector data

Vector data is not unique to the field of geographic information systems (GIS) or geospatial data science and has applications in many digital mediums. When talking about vector data in GIS or geospatial data science, we are talking about data that represents...