Chapter 9. Processing Big Images
Processing satellite images (or other remote sensing data) is a computational challenge for two reasons: normally, the images are big (many megabytes or gigabytes) and many images are needed in combination to produce the desired information.
Opening and processing many big images can consume a lot of computer memory. This condition sets a tight limit on what the user can do before running out of memory.
In this chapter, we will focus on how to perform sustainable image processing and how to open and make calculations with many big images while keeping the memory consumption low with efficient code.
The following topics will be covered:
An introduction to satellite images and Landsat 8 data
How to select and download Landsat 8 data
What happens to the computer memory when we work with images?
How to read images in chunks
What are Python iterators and generators?
How to iterate through an image
How to create color compositions with the new techniques
