Book Image

Learning Geospatial Analysis with Python - Third Edition

By : Joel Lawhead
Book Image

Learning Geospatial Analysis with Python - Third Edition

By: Joel Lawhead

Overview of this book

Geospatial analysis is used in almost every domain you can think of, including defense, farming, and even medicine. With this systematic guide, you'll get started with geographic information system (GIS) and remote sensing analysis using the latest features in Python. This book will take you through GIS techniques, geodatabases, geospatial raster data, and much more using the latest built-in tools and libraries in Python 3.7. You'll learn everything you need to know about using software packages or APIs and generic algorithms that can be used for different situations. Furthermore, you'll learn how to apply simple Python GIS geospatial processes to a variety of problems, and work with remote sensing data. By the end of the book, you'll be able to build a generic corporate system, which can be implemented in any organization to manage customer support requests and field support personnel.
Table of Contents (15 chapters)
Free Chapter
1
Section 1: The History and the Present of the Industry
5
Section 2: Geospatial Analysis Concepts
10
Section 3: Practical Geospatial Processing Techniques

Fiona

The Fiona library provides a simple Python API around the OGR library for data access and nothing more. This approach makes it easy to use and is less verbose than OGR while using Python. Fiona outputs GeoJSON by default. You can find a wheel file for Fiona at http://www.lfd.uci.edu/~gohlke/pythonlibs/#fiona.

As an example, we'll use the GIS_CensusTract_poly.shp file from the dbfpy example we looked at earlier in this chapter.

First, we'll import fiona and Python's pprint module to format the output. Then, we'll open the shapefile and check its driver type:

>>> import fiona
>>> from pprint import pprint
>>> f = fiona.open("GIS_CensusTract_poly.shp")
>>> f.driver