Mastering Geospatial Analysis with Python

Explore GIS processing and learn to work with various tools and libraries in Python.
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Mastering Geospatial Analysis with Python

Paul Crickard, Eric van Rees, Silas Toms
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Explore GIS processing and learn to work with various tools and libraries in Python.
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Book Details

ISBN 139781788293334
Paperback440 pages

Book Description

Python comes with a host of open source libraries and tools that help you work on professional geoprocessing tasks without investing in expensive tools. This book will introduce Python developers, both new and experienced, to a variety of new code libraries that have been developed to perform geospatial analysis, statistical analysis, and data management. This book will use examples and code snippets that will help explain how Python 3 differs from Python 2, and how these new code libraries can be used to solve age-old problems in geospatial analysis.

You will begin by understanding what geoprocessing is and explore the tools and libraries that Python 3 offers. You will then learn to use Python code libraries to read and write geospatial data. You will then learn to perform geospatial queries within databases and learn PyQGIS to automate analysis within the QGIS mapping suite. Moving forward, you will explore the newly released ArcGIS API for Python and ArcGIS Online to perform geospatial analysis and create ArcGIS Online web maps. Further, you will deep dive into Python Geospatial web frameworks and learn to create a geospatial REST API.

Table of Contents

Chapter 1: Package Installation and Management
Introducing Anaconda
Running a Jupyter Notebook
Managing Python packages
Python virtual environments
Summary
Chapter 2: Introduction to Geospatial Code Libraries
Geospatial Data Abstraction Library (GDAL) and the OGR Simple Features Library
GEOS
Shapely
Fiona
Python shapefile library (pyshp)
pyproj
Rasterio
GeoPandas
How it all works together
Summary
Chapter 3: Introduction to Geospatial Databases
Installing PostgreSQL and PostGIS on Windows
Installing PostgreSQL and PostGIS on Mac
Working with PostgreSQL and PostGIS using Python
Summary
Chapter 4: Data Types, Storage, and Conversion
Raster and vector data
Raster data formats
Reading and writing vector data with GeoPandas
Reading and writing vector data with OGR
Reading and writing raster data with Rasterio
Reading and writing raster data using GDAL
Summary
Chapter 5: Vector Data Analysis
OGR Simple Features Library
Shapely and Fiona
GeoPandas
Summary
Chapter 6: Raster Data Processing
Raster operations using GDAL
Raster operations using PostgreSQL
Summary
Chapter 7: Geoprocessing with Geodatabases
A crime dashboard
Summary
Chapter 8: Automating QGIS Analysis
Working in the Python console
Writing custom toolboxes
Summary
Chapter 9: ArcGIS API for Python and ArcGIS Online
Introducing the ArcGIS API for Python and ArcGIS Online
Summary
Chapter 10: Geoprocessing with a GPU Database
Cloud geodatabase solutions
Summary
Chapter 11: Flask and GeoAlchemy2
Flask and its component modules
Summary
Chapter 12: GeoDjango
Installing and configuring Django and GeoDjango
Creating the application
Summary
Chapter 13: Geospatial REST API
Writing a REST API in Python
The REST API application
Deploying Flask to IIS
Summary
Chapter 14: Cloud Geodatabase Analysis and Visualization
How to install CARTOframes
Signing up for a CARTO account
Virtual environments
Using Jupyter Notebook
Summary
Chapter 15: Automating Cloud Cartography
All things cartographic
Mapbox Studio
Summary
Chapter 16: Python Geoprocessing with Hadoop
What is Hadoop?
Installing the Hadoop framework
Hadoop basics
Esri GIS tools for Hadoop
HDFS and Hive in Python
Summary

What You Will Learn

  • Manage code libraries and abstract geospatial analysis techniques using Python 3.
  • Explore popular code libraries that perform specific tasks for geospatial analysis.
  • Utilize code libraries for data conversion, data management, web maps, and REST API creation.
  • Learn techniques related to processing geospatial data in the cloud.
  • Leverage features of Python 3 with geospatial databases such as PostGIS, SQL Server, and Spatialite.

Authors

Table of Contents

Chapter 1: Package Installation and Management
Introducing Anaconda
Running a Jupyter Notebook
Managing Python packages
Python virtual environments
Summary
Chapter 2: Introduction to Geospatial Code Libraries
Geospatial Data Abstraction Library (GDAL) and the OGR Simple Features Library
GEOS
Shapely
Fiona
Python shapefile library (pyshp)
pyproj
Rasterio
GeoPandas
How it all works together
Summary
Chapter 3: Introduction to Geospatial Databases
Installing PostgreSQL and PostGIS on Windows
Installing PostgreSQL and PostGIS on Mac
Working with PostgreSQL and PostGIS using Python
Summary
Chapter 4: Data Types, Storage, and Conversion
Raster and vector data
Raster data formats
Reading and writing vector data with GeoPandas
Reading and writing vector data with OGR
Reading and writing raster data with Rasterio
Reading and writing raster data using GDAL
Summary
Chapter 5: Vector Data Analysis
OGR Simple Features Library
Shapely and Fiona
GeoPandas
Summary
Chapter 6: Raster Data Processing
Raster operations using GDAL
Raster operations using PostgreSQL
Summary
Chapter 7: Geoprocessing with Geodatabases
A crime dashboard
Summary
Chapter 8: Automating QGIS Analysis
Working in the Python console
Writing custom toolboxes
Summary
Chapter 9: ArcGIS API for Python and ArcGIS Online
Introducing the ArcGIS API for Python and ArcGIS Online
Summary
Chapter 10: Geoprocessing with a GPU Database
Cloud geodatabase solutions
Summary
Chapter 11: Flask and GeoAlchemy2
Flask and its component modules
Summary
Chapter 12: GeoDjango
Installing and configuring Django and GeoDjango
Creating the application
Summary
Chapter 13: Geospatial REST API
Writing a REST API in Python
The REST API application
Deploying Flask to IIS
Summary
Chapter 14: Cloud Geodatabase Analysis and Visualization
How to install CARTOframes
Signing up for a CARTO account
Virtual environments
Using Jupyter Notebook
Summary
Chapter 15: Automating Cloud Cartography
All things cartographic
Mapbox Studio
Summary
Chapter 16: Python Geoprocessing with Hadoop
What is Hadoop?
Installing the Hadoop framework
Hadoop basics
Esri GIS tools for Hadoop
HDFS and Hive in Python
Summary

Book Details

ISBN 139781788293334
Paperback440 pages
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