Learning Geospatial Analysis with Python

If you know Python and would like to use it for Geospatial Analysis this book is exactly what you’ve been looking for. With an organized, user-friendly approach it covers all the bases to give you the necessary skills and know-how.

Learning Geospatial Analysis with Python

Learning
Joel Lawhead

If you know Python and would like to use it for Geospatial Analysis this book is exactly what you’ve been looking for. With an organized, user-friendly approach it covers all the bases to give you the necessary skills and know-how.
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Book Details

ISBN 139781783281138
Paperback364 pages

About This Book

  • Construct applications for GIS development by exploiting Python
  • Focuses on built-in Python modules and libraries compatible with the Python Packaging Index distribution system – no compiling of C libraries necessary
  • This is a practical, hands-on tutorial that teaches you all about Geospatial analysis in Python

Who This Book Is For

This book is for anyone who wants to understand digital mapping and analysis and who uses Python or another scripting language for automation or crunching data manually.This book primarily targets Python developers, researchers, and analysts who want to perform Geospatial, modeling, and GIS analysis with Python.

Table of Contents

Chapter 1: Learning Geospatial Analysis with Python
Geospatial analysis and our world
History of geospatial analysis
Geospatial analysis and computer programming
Importance of geospatial analysis
Geographic Information System concepts
Raster data concepts
Common vector GIS concepts
Common raster data concepts
Creating the simplest possible Python GIS
Summary
Chapter 2: Geospatial Data
Data structures
Vector data
Raster data
Point cloud data
Summary
Chapter 3: The Geospatial Technology Landscape
Data access
Computational geometry
Desktop tools
Metadata management
Summary
Chapter 4: Geospatial Python Toolbox
Installing third-party Python modules
Python networking libraries for acquiring data
Python markup and tag-based parsers
Python JSON libraries
OGR
PyShp
dbfpy
Shapely
GDAL
NumPy
PIL
PNGCanvas
PyFPDF
Spectral Python
Summary
Chapter 5: Python and Geographic Information Systems
Measuring distance
Coordinate conversion
Reprojection
Editing shapefiles
Performing selections
Creating images for visualization
Dot density calculations
Choropleth maps
Using spreadsheets
Using GPS data
Summary
Chapter 6: Python and Remote Sensing
Swapping image bands
Creating histograms
Clipping images
Classifying images
Extracting features from images
Change detection
Summary
Chapter 7: Python and Elevation Data
ASCII Grid files
Creating a shaded relief
Creating elevation contours
Working with LIDAR
Summary
Chapter 8: Advanced Geospatial Python Modelling
Creating an NDVI
Creating a flood inundation model
Least cost path analysis
Summary
Chapter 9: Real-Time Data
Tracking vehicles
Storm chasing
Summary
Chapter 10: Putting It All Together
A typical GPS report
Working with GPX-Reporter.py
Summary

What You Will Learn

  • Automate Geospatial analysis workflows using Python
  • Code the simplest possible GIS in 60 lines of Python
  • Mold thematic maps with Python tools
  • Get a hold of the various forms the geospatial data comes in
  • Produce elevation contours using Python tools
  • Create flood inundation models
  • Learn Real-Time Data tracking and apply it in storm chasing

In Detail

Geospatial analysis is used in almost every field you can think of from medicine, to defense, to farming. It is an approach to use statistical analysis and other informational engineering to data which has a geographical or geospatial aspect. And this typically involves applications capable of geospatial display and processing to get a compiled and useful data.

"Learning Geospatial Analysis with Python" uses the expressive and powerful Python programming language to guide you through geographic information systems, remote sensing, topography, and more. It explains how to use a framework in order to approach Geospatial analysis effectively, but on your own terms.

"Learning Geospatial Analysis with Python" starts with a background of the field, a survey of the techniques and technology used, and then splits the field into its component speciality areas: GIS, remote sensing, elevation data, advanced modelling, and real-time data.

This book will teach you everything there is to know, from using a particular software package or API to using generic algorithms that can be applied to Geospatial analysis. This book focuses on pure Python whenever possible to minimize compiling platform-dependent binaries, so that you don’t become bogged down in just getting ready to do analysis.

"Learning Geospatial Analysis with Python" will round out your technical library with handy recipes and a good understanding of a field that supplements many a modern day human endeavors.

Authors

Table of Contents

Chapter 1: Learning Geospatial Analysis with Python
Geospatial analysis and our world
History of geospatial analysis
Geospatial analysis and computer programming
Importance of geospatial analysis
Geographic Information System concepts
Raster data concepts
Common vector GIS concepts
Common raster data concepts
Creating the simplest possible Python GIS
Summary
Chapter 2: Geospatial Data
Data structures
Vector data
Raster data
Point cloud data
Summary
Chapter 3: The Geospatial Technology Landscape
Data access
Computational geometry
Desktop tools
Metadata management
Summary
Chapter 4: Geospatial Python Toolbox
Installing third-party Python modules
Python networking libraries for acquiring data
Python markup and tag-based parsers
Python JSON libraries
OGR
PyShp
dbfpy
Shapely
GDAL
NumPy
PIL
PNGCanvas
PyFPDF
Spectral Python
Summary
Chapter 5: Python and Geographic Information Systems
Measuring distance
Coordinate conversion
Reprojection
Editing shapefiles
Performing selections
Creating images for visualization
Dot density calculations
Choropleth maps
Using spreadsheets
Using GPS data
Summary
Chapter 6: Python and Remote Sensing
Swapping image bands
Creating histograms
Clipping images
Classifying images
Extracting features from images
Change detection
Summary
Chapter 7: Python and Elevation Data
ASCII Grid files
Creating a shaded relief
Creating elevation contours
Working with LIDAR
Summary
Chapter 8: Advanced Geospatial Python Modelling
Creating an NDVI
Creating a flood inundation model
Least cost path analysis
Summary
Chapter 9: Real-Time Data
Tracking vehicles
Storm chasing
Summary
Chapter 10: Putting It All Together
A typical GPS report
Working with GPX-Reporter.py
Summary

Book Details

ISBN 139781783281138
Paperback364 pages
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