Book Image

PostGIS Cookbook - Second Edition

By : Pedro Wightman, Bborie Park, Stephen Vincent Mather, Thomas Kraft, Mayra Zurbarán
Book Image

PostGIS Cookbook - Second Edition

By: Pedro Wightman, Bborie Park, Stephen Vincent Mather, Thomas Kraft, Mayra Zurbarán

Overview of this book

PostGIS is a spatial database that integrates the advanced storage and analysis of vector and raster data, and is remarkably flexible and powerful. PostGIS provides support for geographic objects to the PostgreSQL object-relational database and is currently the most popular open source spatial databases. If you want to explore the complete range of PostGIS techniques and expose related extensions, then this book is for you. This book is a comprehensive guide to PostGIS tools and concepts which are required to manage, manipulate, and analyze spatial data in PostGIS. It covers key spatial data manipulation tasks, explaining not only how each task is performed, but also why. It provides practical guidance allowing you to safely take advantage of the advanced technology in PostGIS in order to simplify your spatial database administration tasks. Furthermore, you will learn to take advantage of basic and advanced vector, raster, and routing approaches along with the concepts of data maintenance, optimization, and performance, and will help you to integrate these into a large ecosystem of desktop and web tools. By the end, you will be armed with all the tools and instructions you need to both manage the spatial database system and make better decisions as your project's requirements evolve.
Table of Contents (18 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Importing NetCDF datasets with Python and GDAL


In this recipe, you will write a Python script to import data from the NetCDF format to PostGIS.

NetCDF is an open standard format, widely used for scientific applications, and can contain multiple raster datasets, each composed of a spectrum of bands. For this purpose, you will use the GDAL Python bindings and the popular NumPy (http://www.numpy.org/) scientific library.

Getting ready

  1. If you are using Windows, be sure to install OSGeo4W, as suggested in the initial instructions for this chapter. This will include Python and GDAL Python bindings with NumPy support.

For Linux users, in case you did not do it yet, follow the initial instructions for this chapter and create a Python virtual environment in order to keep a Python-isolated environment to be used for all the Python recipes in this book. Then, activate it:

$ source postgis-cb-env/bin/activate
  1. For this recipe, you need the GDAL Python bindings and NumPy, the latter being needed by a GDAL method...