Book Image

Learning Geospatial Analysis with Python

By : Joel Lawhead
Book Image

Learning Geospatial Analysis with Python

By: Joel Lawhead

Overview of this book

Geospatial Analysis is used in almost every field you can think of from medicine, to defense, to farming. This book will guide you gently into this exciting and complex field. It walks you through the building blocks of geospatial analysis and how to apply them to influence decision making using the latest Python software. Learning Geospatial Analysis with Python, 2nd Edition uses the expressive and powerful Python 3 programming language to guide you through geographic information systems, remote sensing, topography, and more, while providing a framework for you to approach geospatial analysis effectively, but on your own terms. We start by giving you a little background on the field, and a survey of the techniques and technology used. We then split the field into its component specialty areas: GIS, remote sensing, elevation data, advanced modeling, and real-time data. This book will teach you everything you need to know about, Geospatial Analysis from using a particular software package or API to using generic algorithms that can be applied. This book focuses on pure Python whenever possible to minimize compiling platform-dependent binaries, so that you don’t become bogged down in just getting ready to do analysis. This book will round out your technical library through handy recipes that will give you a good understanding of a field that supplements many a modern day human endeavors.
Table of Contents (17 chapters)
Learning Geospatial Analysis with Python Second Edition
About the Author
About the Reviewers

Downloading map and elevation images

We'll download the OSM base map first, which has streets and labels:

# Download the OSM basemap"Downloading basemap")
wms(mminx, mminy, mmaxx, mmaxy, osm_WMS, osm_lyr, osm_epsg, osm_style, osm_img, w, h)

This section will produce an intermediate image, as shown in the following screenshot:

Next, we'll download some elevation data from the SRTM dataset. SRTM is nearly-global and provides a 30-90 m resolution. The Python module makes working with this data easy. downloads the datasets that it needs to make a request. So if you download data from different areas, you may need to clean out the cache located in your home directory (~/.srtm). This part of the script can also take up to 2-3 minutes to complete depending on your computer and Internet connection speeds:

# Download the SRTM image

# downloader"Retrieving SRTM elevation data")
# The SRTM module will try to use a local cache
# first and if needed download it...