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
Section 1: The History and the Present of the Industry
Section 2: Geospatial Analysis Concepts
Section 3: Practical Geospatial Processing Techniques


Sometimes, you may find that PIL is overkill for your purposes, or you are not allowed to install PIL because you do not have administrative rights to the machine that you're using to install Python modules that have been created and compiled in C. In those cases, you can usually get away with the lightweight pure Python PNGCanvas module. You can install it using easy_install or pip.

Using this module, we can repeat the raster shapefile example we performed using PIL but in pure Python, as you can see here:

>>> import shapefile
>>> import pngcanvas
>>> r = shapefile.Reader("hancock.shp")
>>> xdist = r.bbox[2] - r.bbox[0]
>>> ydist = r.bbox[3] - r.bbox[1]
>>> iwidth = 400
>>> iheight = 600
>>> xratio = iwidth/xdist
>>> yratio = iheight/ydist
>>> pixels = []
>>> for...