Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
 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

Arrow left icon
Product type Paperback
Published in Nov 2023
Publisher Packt
ISBN-13 9781837639175
Length 432 pages
Edition 4th Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Joel Lawhead Joel Lawhead
Author Profile Icon Joel Lawhead
Joel Lawhead
Arrow right icon
View More author details
Toc

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

Putting It All Together

Throughout the book, we’ve touched upon all the important aspects of geospatial analysis, and we’ve used a variety of different techniques in Python to analyze different types of geospatial data. In this final chapter, we will draw on nearly all of the topics we have covered to produce a real-world product that has become very popular – a GPS route analysis report.

These reports are common to dozens of mobile app services, GPS watches, in-car navigation systems, and other GPS-based tools. A GPS typically records location, time, and elevation. From these values, we can derive a vast amount of ancillary information about what happened along the route on which that data was recorded. Fitness apps, including Runkeeper, MapMyRun, Strava, and Nike Plus, all use similar reports to present GPS-tracked exercise data from running, hiking, biking, and walking.

We will create one of these reports using Python. This program is nearly 500 lines...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime