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Applied Geospatial Data Science with Python

Applied Geospatial Data Science with Python

By : David S. Jordan
4.6 (11)
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Applied Geospatial Data Science with Python

Applied Geospatial Data Science with Python

4.6 (11)
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)
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1
Part 1:The Essentials of Geospatial Data Science
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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

Part 1:The Essentials of Geospatial Data Science

To begin your journey as a geospatial data scientist, it is critical that you familiarize yourself with the critical elements of geospatial data science. In this part of the book, we’ll define geospatial information systems and their relationship to data science and geospatial data science. You’ll also be introduced to various types of geospatial data and a plethora of open geospatial data resources. Later in this part, you’ll be introduced to geographic and projected coordinate systems, which are how we model the earth in different mediums. We’ll conclude the chapter with an introduction to the Python packages you’ll leverage throughout Part 2 and Part 3 of the book.

This part comprises the following chapters:

  • Chapter 1, Introducing Geographic Information Systems and Geospatial Data Science
  • Chapter 2, What Is Geospatial Data and Where Can I Find It?
  • Chapter 3, Working with Geographic...
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