Mastering Geospatial Analysis with Python

Book Image

Mastering Geospatial Analysis with Python

By : Silas Toms, Paul Crickard, Eric van Rees

Book Image

Mastering Geospatial Analysis with Python

By: Silas Toms, Paul Crickard, Eric van Rees

Overview of this book

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.

Title Page

Copyright and Credits

Copyright and Credits

Packt Upsell

Contributors

Preface

Free Chapter

Package Installation and Management

Package Installation and Management

Introducing Anaconda

Running a Jupyter Notebook

Managing Python packages

Python virtual environments

Introduction to Geospatial Code Libraries

Introduction to Geospatial Code Libraries

Geospatial Data Abstraction Library (GDAL) and the OGR Simple Features Library

Python shapefile library (pyshp)

How it all works together

Introduction to Geospatial Databases

Introduction to Geospatial Databases

Installing PostgreSQL and PostGIS on Windows

Installing PostgreSQL and PostGIS on Mac

Working with PostgreSQL and PostGIS using Python

Data Types, Storage, and Conversion

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

Vector Data Analysis

Vector Data Analysis

OGR Simple Features Library

Shapely and Fiona

Raster Data Processing

Raster Data Processing

Raster operations using GDAL

Raster operations using PostgreSQL

Geoprocessing with Geodatabases

Geoprocessing with Geodatabases

A crime dashboard

Automating QGIS Analysis

Automating QGIS Analysis

Working in the Python console

Writing custom toolboxes

ArcGIS API for Python and ArcGIS Online

ArcGIS API for Python and ArcGIS Online

Introducing the ArcGIS API for Python and ArcGIS Online

Geoprocessing with a GPU Database

Geoprocessing with a GPU Database

Cloud geodatabase solutions

Flask and GeoAlchemy2

Flask and GeoAlchemy2

Flask and its component modules

GeoDjango

Installing and configuring Django and GeoDjango

Creating the application

Geospatial REST API

Geospatial REST API

Writing a REST API in Python

The REST API application

Deploying Flask to IIS

Cloud Geodatabase Analysis and Visualization

Cloud Geodatabase Analysis and Visualization

How to install CARTOframes

Signing up for a CARTO account

Virtual environments

Using Jupyter Notebook

Automating Cloud Cartography

Automating Cloud Cartography

All things cartographic

Python Geoprocessing with Hadoop

Python Geoprocessing with Hadoop

What is Hadoop?

Installing the Hadoop framework

Esri GIS tools for Hadoop

HDFS and Hive in Python

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What is Hadoop?

Hadoop is an open-source framework for working with large quantities of data spread across a single computer to thousands of computers. Hadoop is composed of four modules:

Hadoop Core
Hadoop Distributed File System (HDFS)
Yet Another Resource Negotiator (YARN)
MapReduce

The Hadoop Core makes up the components needed to run the other three modules. HDFS is a Java-based file system that has been designed to be distributed and is capable of storing large files across many machines. By large files, we are talking terabytes. YARN manages the resources and scheduling in your Hadoop framework. The MapReduce engine allows you to process data in parallel.

There are several other projects that can be installed to work with the Hadoop framework. In this chapter, you will use Hive and Ambari. Hive allows you to read and write data using SQL. You will use Hive to run the spatial queries on your data at the end of the chapter. Ambari provides a web user interface to Hadoop and Hive. In this...