Landcover classification of drone UAV imagery (RGB and Multispectral) using Random forest with unsupervised segmentation (superpixel) postprocessing.

In this repository I only store the code (Python). The data is taken from Hilden collection, which is accessible by contacting the Hilden Network.

The code is organized into 4 Jupyter notebooks and one Python script with functions:

• 0._ - preprocessing of the images. Filling the gaps and resizing the images if needed.
• 1._ - showing an example of landcover classification on one image
• 2._ - classifying all the prepared in script 0. multispectral imagery
• 3._ - classifying all the prepared in script 0. RGB imagery
• myfunctions - all the custom functions I used

If you want to quickly glance at how the analysis is done, just view the 1._script. It contains images and descriptions of each step.

Please feel free to contact me if you have any questions!