Summary
In this chapter, we covered the foundations of remote sensing, including metadata, band swapping, histograms, clipping images, image classification, feature extraction, change detection, and creating footprints. Like in the other chapters, we stayed as close to pure Python as possible, and where we compromised on this goal for processing speed, we limited the software libraries as much as possible to keep things simple. However, if you have the tools from this chapter installed, you have a complete remote sensing package that is limited only by your desire to learn.
The techniques in this chapter are foundational to all remote sensing processes and will allow you to build more complex operations.
In the next chapter, we’ll investigate elevation data. Elevation data doesn’t fit squarely in GIS or remote sensing as it has elements of both types of processing.
