47 numpy to cog

Create a fresh conda env to run this example if needed.

conda create -n cog python=3.9
conda install mamba -c conda-forge
mamba install leafmap rio-cogeo -c conda-forge

1	`# !pip install leafmap`

1	`# !pip install rio-cogeo`

import leafmap

url = "https://github.com/opengeos/leafmap/raw/master/examples/data/cog.tif"
in_cog = "cog.tif"
out_cog = "ndvi.tif"

Download a sample dataset.

leafmap.download_from_url(url, in_cog)

Convert image to numpy array.

arr = leafmap.image_to_numpy(in_cog)

arr.shape

Computer NDVI.

ndvi = (arr[3] - arr[0]) / (arr[3] + arr[0])

ndvi.shape

Convert numpy array to COG.

leafmap.numpy_to_cog(ndvi, out_cog, profile=in_cog)

m = leafmap.Map()
m.add_raster(in_cog, band=[4, 1, 2], layer_name="Color infrared")
m.add_raster(out_cog, palette="Greens", layer_name="NDVI")
m