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


We started the chapter off with a history lesson from the ancient Greeks, who began to theorize and test that the Earth was round and not, in fact, flat. With an understanding that the Earth is round, we then dove into GCSs to develop an understanding of how we represent the three-dimensional Earth in two-dimensional space. We talked about various versions of GCSs, such as WGS 1984, which has become the de facto standard GCS, given its high degree of accuracy. We also briefly spoke about the GCJ-02 GCS, which is utilized in China, and the issues it presents due to the randomized offset algorithm.

In the next section, we covered PCSs, which convert angular units, such as degrees used within GCSs, into measurements that use units, such as meters and miles. We covered multiple types of PCSs, including equal-area, conformal, equidistant, and true-direction projections. We also introduced you to the standard identifiers and authoritative sources that maintain projected coordinate...