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Learning Geospatial Analysis with Python

Learning Geospatial Analysis with Python - Third Edition

By : Joel Lawhead
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Learning Geospatial Analysis with Python

Learning Geospatial Analysis with Python

3 (3)
By: Joel Lawhead

Overview of this book

Geospatial analysis is used in almost every domain you can think of, including defense, farming, and even medicine. With this systematic guide, you'll get started with geographic information system (GIS) and remote sensing analysis using the latest features in Python. This book will take you through GIS techniques, geodatabases, geospatial raster data, and much more using the latest built-in tools and libraries in Python 3.7. You'll learn everything you need to know about using software packages or APIs and generic algorithms that can be used for different situations. Furthermore, you'll learn how to apply simple Python GIS geospatial processes to a variety of problems, and work with remote sensing data. By the end of the book, you'll be able to build a generic corporate system, which can be implemented in any organization to manage customer support requests and field support personnel.
Table of Contents (15 chapters)
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Section 1: The History and the Present of the Industry
5
Section 2: Geospatial Analysis Concepts
10
Section 3: Practical Geospatial Processing Techniques

Preface

The book starts by giving you the background of geospatial analysis, and then offers a flow of the techniques and technology used and splits the field into its component specialty areas, such as Geographic Information Systems (GIS), remote sensing, elevation data, advanced modeling, and real-time data. The focus of the book is to lay a strong foundation in using the powerful Python language and framework to approach geospatial analysis effectively. In doing so, we'll focus on using pure Python as well as certain Python tools and APIs, and using generic algorithms. The readers will be able to analyze various forms of geospatial data, learn about real-time data tracking, and see how to apply what they learn to interesting scenarios.

While many third-party geospatial libraries are used throughout the examples, a special effort will be made by us to use pure Python, with no dependencies, whenever possible. This focus on pure Python 3 examples is what will set this book apart from nearly all other resources in this field. We will also go through some popular libraries that weren't in the previous version of the book.

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