Satellite images often need to be classified (assigned to a fixed set of types) or to be used for detection of various features of interest. Here we will look at the classification case, using labelled satellite images from various categories from the UCMerced LandUse dataset. scikit-learn is useful for general numeric data types, but it doesn't have significant support for working with images. Luckily, there are various deep-learning and convolutional-network libraries that do support images well, including Keras (backed by TensorFlow) as we will use here.
import intake import numpy as np import geoviews as gv import holoviews as hv import pandas as pd import random from holoviews import opts gv.extension('bokeh')