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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

The Geospatial Technology Landscape

The geospatial technology ecosystem consists of hundreds of software libraries and packages. This vast array of choices can be overwhelming for newcomers to geospatial analysis. The secret to learning geospatial analysis quickly is understanding the handful of libraries and packages that really matter. Most software, both commercial and open source, is derived from these critical packages. Understanding the ecosystem of geospatial software and how it's used allows you to quickly comprehend and evaluate any geospatial tool.

Geospatial libraries can be assigned to one or more of the following high-level core capabilities, which they implement to some degree. We will be learning about these capabilities in this chapter:

  • Data access
  • Computational geometry (including data reprojection)
  • Image processing
  • Visualization tools
  • Metadata tools

In...

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Tech Concepts
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Programming languages
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Learning Geospatial Analysis with Python
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