LIVEPROJECT

Monitoring Changes in Surface Water Using Satellite Image Data

Time series data, Image segmentation, CNN, Auto Decoder, UNet

We just launched our liveProject platform — where you can sign up for a structured project and get real-world experience.

In this liveProject, you’ll fill the shoes of a data scientist at UNESCO (United Nations Educational, Scientific and Cultural Organization). Your job involves assessing long-term changes to freshwater deposits, one of humanity’s most important resources. Recently, two European Space Agency satellites have given you a massive amount of new data in the form of satellite imagery. Your task is to build a deep learning algorithm that can process this data and automatically detect water pixels in the imagery of a region. To accomplish this, you will design, implement, and evaluate a convolutional neural network model for image pixel classification, or image segmentation. Your challenges will include compiling your data, training your model, evaluating its performance, and providing a summary of your findings to your superiors. Throughout, you’ll use the Google Collaboratory (“Colab”) coding environment to access free GPU computer resources and speed up your training times.

Learn more about liveProject here: https://liveproject.manning.com/