ee_sampling.jl

using PyCall, Plots;
theme(:bright);

# import the ee Python module into Julia
# and initialize the EE API
ee = pyimport("ee");
ee.Initialize();

# produce tabular data that can be plotted by data visualization in Julia
# Fetch a Landsat image.
img = ee.Image("LANDSAT/LT05/C01/T1_SR/LT05_034033_20000913");

# Select Red and NIR bands, scale them, and sample 500 points.
samp_fc = img.select(["B3","B4"]).divide(10000).sample(scale=30, numPixels=500);

# Arrange the sample as a list of lists.
samp_dict = samp_fc.reduceColumns(ee.Reducer.toList().repeat(2), ["B3", "B4"]);
samp_list = ee.List(samp_dict.get("list"));

# Save server-side ee.List as a client-side Array.
samp_data = samp_list.getInfo();

# unpack the red/nir Array rows to 1-d Vectors
red,nir = [samp_data[x,:] for x in 1:size(samp_data,1)];

# plot the data
scatter(red,nir,markersize=5,alpha=0.5,xlabel="Red",ylabel="NIR",leg=false,dpi=200)
# you can save the figure using: 'savefig("<path-to-file>,png")'