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

Rasterio

The GDAL library we introduced earlier in this chapter is extremely powerful, but it wasn't designed for Python. The rasterio library solves that problem by wrapping GDAL in a very simple, clean Pythonic API for raster data operations.

This example uses the satellite image from the GDAL example in this chapter. We'll open the image and get some metadata, like the following

>>> import rasterio
>>> ds = rasterio.open("SatImage.tif")
>>> ds.name
'SatImage.tif'
>>> ds.count
3
>>> ds.width
2592
>>> ds.height
2693