Browse Library
Sign In Start Free Trial
Close icon Search icon
Account
Browse Library Sign In Start Free Trial

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Learning Geospatial Analysis with Python
  • Table Of Contents Toc
Learning Geospatial Analysis with Python

Learning Geospatial Analysis with Python - Fourth Edition

By : Joel Lawhead
5 (7)
Buy this Book
close
close
Learning Geospatial Analysis with Python

Learning Geospatial Analysis with Python

5 (7)
By: Joel Lawhead
Buy this Book

Overview of this book

Geospatial analysis is used in almost every domain you can think of, including defense, farming, and even medicine. In this special 10th anniversary edition, you'll embark on an exhilarating geospatial analysis adventure using Python. This fourth edition starts with the fundamental concepts, enhancing your expertise in geospatial analysis processes with the help of illustrations, basic formulas, and pseudocode for real-world applications. As you progress, you’ll explore the vast and intricate geospatial technology ecosystem, featuring thousands of software libraries and packages, each offering unique capabilities and insights. This book also explores practical Python GIS geospatial applications, remote sensing data, elevation data, and the dynamic world of geospatial modeling. It emphasizes the predictive and decision-making potential of geospatial technology, allowing you to visualize complex natural world concepts, such as environmental conservation, urban planning, and disaster management to make informed choices. You’ll also learn how to leverage Python to process real-time data and create valuable information products. By the end of this book, you'll have acquired the knowledge and techniques needed to build a complete geospatial application that can generate a report and can be further customized for different purposes.
Table of Contents (18 chapters)
close
close
close
Preface
Icon
Preface
Icon
Who this book is for
Icon
What this book covers
Icon
To get the most out of this book
Icon
Download the example code files
Icon
Conventions used
Icon
Get in touch
Icon
Share your thoughts
Icon
Download a free PDF copy of this book
1
Part 1:The History and the Present of the Industry
Icon
Part 1:The History and the Present of the Industry
Lock Free Chapter
2
Chapter 1: Learning about Geospatial Analysis with Python
Icon
Chapter 1: Learning about Geospatial Analysis with Python
Icon
Technical requirements
Icon
Geospatial analysis and our world
Icon
History of geospatial analysis
Icon
Evolution of Geographic Information Systems (GISs)
Icon
Remote sensing
Icon
Point cloud data
Icon
Computer-aided drafting
Icon
Geospatial analysis and computer programming
Icon
The importance of geospatial analysis
Icon
GIS concepts
Icon
Remote sensing concepts
Icon
Common vector GIS concepts
Icon
Common raster data concepts
Icon
Creating the simplest possible Python GIS
Icon
Summary
Icon
Questions
Icon
Further reading
3
Chapter 2: Learning about Geospatial Data
Icon
Chapter 2: Learning about Geospatial Data
Icon
Technical requirements
Icon
Overview of common data formats
Icon
Understanding data structures
Icon
Understanding spatial indexing
Icon
What are overviews?
Icon
What is metadata?
Icon
Understanding the file structure
Icon
Knowing about the most widely used vector data types
Icon
Understanding raster data types
Icon
What is point cloud data?
Icon
More realistic geospatial models with 3D data
Icon
What are web services?
Icon
Understanding geospatial databases
Icon
Sharing data with interchange formats
Icon
Introducing spatiotemporal data
Icon
Summary
Icon
Questions
Icon
Further reading
4
Chapter 3: The Geospatial Technology Landscape
Icon
Chapter 3: The Geospatial Technology Landscape
Icon
Technical requirements
Icon
Understanding data access
Icon
Understanding computational geometry
Icon
Understanding desktop tools (including visualization)
Icon
Understanding metadata management
Icon
A quick look at artificial intelligence
Icon
Summary
Icon
Questions
Icon
Further reading
5
Part 2:Geospatial Analysis Concepts
Icon
Part 2:Geospatial Analysis Concepts
6
Chapter 4: Geospatial Python Toolbox
Icon
Chapter 4: Geospatial Python Toolbox
Icon
Technical requirements
Icon
Using QGIS
Icon
Installing third-party Python modules
Icon
Jupyter
Icon
Python networking libraries for acquiring data
Icon
Bundling and compressing files
Icon
Python markup and tag-based parsers
Icon
Well-Known Text (WKT)
Icon
Python JSON libraries
Icon
OGR
Icon
PyShp
Icon
Shapely
Icon
Fiona
Icon
GDAL
Icon
NumPy
Icon
PIL
Icon
PNGCanvas
Icon
GeoPandas
Icon
PyFPDF
Icon
PyMySQL
Icon
Rasterio
Icon
OSMnx
Icon
Folium
Icon
Summary
Icon
Questions
Icon
Further reading
7
Chapter 5: Python and Geospatial Algorithms
Icon
Chapter 5: Python and Geospatial Algorithms
Icon
Technical requirements
Icon
Measuring distance
Icon
Calculating line direction
Icon
Understanding coordinate conversion
Icon
Understanding reprojection
Icon
Understanding coordinate format conversion
Icon
Calculating the area of a polygon
Icon
Using ChatGPT to measure a polygon perimeter
Icon
Summary
Icon
Questions
Icon
Further reading
8
Chapter 6: Creating and Editing GIS Data
chevron up
Icon
Chapter 6: Creating and Editing GIS Data
Icon
Technical requirements
Icon
Editing shapefiles
Icon
Creating images for visualization
Icon
Using GPS data
Icon
Turning addresses into points with geocoding
Icon
Performing GIS analysis faster with multiprocessing
Icon
Summary
Icon
Questions
Icon
Further reading
9
Chapter 7: Python and Remote Sensing
Icon
Chapter 7: Python and Remote Sensing
Icon
Technical requirements
Icon
Examining raster data properties
Icon
Swapping image bands
Icon
Creating image histograms
Icon
Clipping images
Icon
Classifying images
Icon
Extracting features from images
Icon
Understanding change detection
Icon
Extracting image footprints using ChatGPT
Icon
Summary
Icon
Questions
Icon
Further reading
10
Chapter 8: Python and Elevation Data
Icon
Chapter 8: Python and Elevation Data
Icon
Technical requirements
Icon
Accessing ASCII Grid files
Icon
Creating a shaded relief
Icon
Creating elevation contours
Icon
Working with LiDAR data
Icon
Working with bathymetry
Icon
Summary
Icon
Questions
Icon
Further reading
11
Part 3:Practical Geospatial Processing Techniques
Icon
Part 3:Practical Geospatial Processing Techniques
12
Chapter 9: Advanced Geospatial Modeling
Icon
Chapter 9: Advanced Geospatial Modeling
Icon
Technical requirements
Icon
Creating a normalized difference vegetation index (NDVI)
Icon
Creating a flood inundation model
Icon
Creating a color hillshade
Icon
Performing least cost path analysis
Icon
Converting the route to a shapefile
Icon
Routing along streets
Icon
Geolocating photos
Icon
Calculating satellite image cloud cover
Icon
Summary
Icon
Questions
Icon
Further reading
13
Chapter 10: Working with Real-Time Data
Icon
Chapter 10: Working with Real-Time Data
Icon
Technical requirements
Icon
Limitations of real-time data
Icon
Using real-time data
Icon
Tracking vehicles
Icon
Gathering reports from the field
Icon
Summary
Icon
Questions
Icon
Further reading
14
Chapter 11: Putting It All Together
Icon
Chapter 11: Putting It All Together
Icon
Technical requirements
Icon
Understanding a typical GPS report
Icon
Building a GPS reporting tool
Icon
Summary
Icon
Questions
Icon
Further reading
15
Assessments
Icon
Chapter 1 – Learning about Geospatial Analysis with Python
Icon
Chapter 2 – Learning about Geospatial Data
Icon
Chapter 3 – The Geospatial Technology Landscape
Icon
Chapter 4 – Geospatial Python Toolbox
Icon
Chapter 5 – Python and Geospatial Algorithms
Icon
Chapter 6 – Creating and Editing GIS Data
Icon
Chapter 7 – Python and Remote Sensing
Icon
Chapter 8 – Python and Elevation Data
Icon
Chapter 9 – Advanced Geospatial Modeling
Icon
Chapter 10 – Working with Real-Time Data
Icon
Chapter 11 – Putting It All Together
16
Index
Icon
Index
Icon
Why subscribe?
17
Other Books You May Enjoy
Icon
Other Books You May Enjoy
Icon
Packt is searching for authors like you
Icon
Share your thoughts
Icon
Download a free PDF copy of this book

Summary

In this chapter, we learned how to edit shapefiles and perform spatial and attribute selections. We created thematic maps from scratch using only Python. We also imported data from spreadsheets. Then, we parsed GPS data from NMEA streams. We used geocoding to convert street addresses into locations and back. And finally, we learned how to speed things up with parallel processing.

As a geospatial analyst, you may be familiar with both GIS and remote sensing, but most analysts specialize in one field or the other. That is why this book approaches the fields in separate chapters – so that we can focus on their differences. As we mentioned in the introduction, the techniques in this chapter are the building blocks for all geospatial analysis and will give you the tools you need so that you can learn about any aspect of this field.

In the next chapter, we’ll dive into remote sensing. In GIS, we have been able to explore this field using pure Python modules. In...

CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Learning Geospatial Analysis with Python
End of Section 8
Next Section
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist download Download options
font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected
Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful
Order Page Read Now

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon