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 Learning Geospatial Analysis with Python

You're reading from   Learning Geospatial Analysis with Python Unleash the power of Python 3 with practical techniques for learning GIS and remote sensing

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Product type Paperback
Published in Nov 2023
Publisher Packt
ISBN-13 9781837639175
Length 432 pages
Edition 4th Edition
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Author (1):
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Joel Lawhead Joel Lawhead
Author Profile Icon Joel Lawhead
Joel Lawhead
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Table of Contents (18) Chapters Close

Preface 1. Part 1:The History and the Present of the Industry
2. Chapter 1: Learning about Geospatial Analysis with Python FREE CHAPTER 3. Chapter 2: Learning about Geospatial Data 4. Chapter 3: The Geospatial Technology Landscape 5. Part 2:Geospatial Analysis Concepts
6. Chapter 4: Geospatial Python Toolbox 7. Chapter 5: Python and Geospatial Algorithms 8. Chapter 6: Creating and Editing GIS Data 9. Chapter 7: Python and Remote Sensing 10. Chapter 8: Python and Elevation Data 11. Part 3:Practical Geospatial Processing Techniques
12. Chapter 9: Advanced Geospatial Modeling 13. Chapter 10: Working with Real-Time Data 14. Chapter 11: Putting It All Together 15. Assessments 16. Index 17. Other Books You May Enjoy

The importance of geospatial analysis

Geospatial analysis helps people make better decisions. It doesn’t make the decision for you, but it can answer critical questions that are at the heart of the choice to be made and often cannot be answered any other way. Until recently, geospatial technology and data were tools available only to governments and well-funded researchers. However, in the last decade, data has become much more widely available and software has become much more accessible to anyone.

In addition to freely available government satellite imagery, many local governments now conduct aerial photo surveys and make the data available online. The ubiquitous Google Earth provides a cross-platform spinning globe view of the Earth with satellite and aerial data, streets, points of interest, photographs, and much more. Google Earth users can create custom Keyhole Markup Language (KML) files, which are XML files that are used to load and style data to the globe. This program and similar tools are often called geographic exploration tools because they are excellent data viewers but provide very limited data analysis capabilities.

The ambitious OpenStreetMap project (https://www.openstreetmap.org/#map=5/51.500/-0.100) is a crowd-sourced, worldwide, geographic base map containing most layers commonly found in a GIS. Nearly every mobile phone now contains a GPS, along with mobile apps to collect GPS tracks as points, lines, or polygons. Most phones will also tag photos taken with the phone’s camera with GPS coordinates. In short, anyone can be a geospatial analyst.

The global population has reached 7 billion people. The world is changing faster than ever before. The planet is undergoing environmental changes that have never been seen in recorded history. Faster communication and transportation increase the interaction between us and the environment in which we live. Managing people and resources safely and responsibly is more challenging than ever. Geospatial analysis is the best approach to understanding our world more efficiently and deeply. The more politicians, activists, relief workers, parents, teachers, first responders, medical professionals, and small businesses that harness the power of geospatial analysis, the more potential we have for a better, healthier, safer, and fairer world.

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Learning Geospatial Analysis with Python - Fourth Edition
Published in: Nov 2023
Publisher: Packt
ISBN-13: 9781837639175
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