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

Creating a color hillshade

In this example, we'll combine previous techniques to combine our terrain hillshade from Chapter 7, Python and Elevation Data, with the color classification that we used on the LIDAR. For this example, we'll need the ASCII Grid DEMs named dem.asc and relief.asc that we used in the previous chapter.

We'll create a colorized DEM and a hillshade, and then use PIL to blend them together for an enhanced elevation visualization. The code comments will guide you through the example, as many of these steps are already familiar to you:

  1. First, we import the libraries that we need:
import gdal_array as gd
try:
import Image
except ImportError:
from PIL import Image

For this next part, you'll need the following two files: https://github.com/GeospatialPython/Learn/raw/master/relief.zip and https://github.com/GeospatialPython/Learn/raw/master/dem...