Monitoring Changes in Surface Water Using Satellite Image Data you own this product

prerequisites
intermediate Python • intermediate NumPy • intermediate Matplotlib • beginner TensorFlow • basics of deep learning for computer vision
skills learned
work with times series data • perform image segmentation • merge satellite imagery and perform operations on raster datasets • data augmentation for boosting model training • optimize and understand model performance
Daniel Buscombe
8 weeks · 5-8 hours per week · ADVANCED
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Look inside
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.
This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Daniel Buscombe
Daniel Buscombe is a geosciences researcher with 16 years of experience applying innovation in computation, geostatistics, and machine learning to problems in coastal and hydraulic engineering, geophysics, hydrology, and geomorphology. He has written many articles on the application of stochastic statistics, machine learning, and artificial intelligence. Dan has a PhD in nearshore oceanography from the University of Plymouth, UK.

prerequisites

This course is for intermediate Python programmers who know basic data science techniques. You’ll augment your skills with some cutting-edge machine learning methods in demand across industry. To begin this liveProject, you will need to be familiar with:

TOOLS
  • Basic Jupyter Notebook
  • Intermediate NumPy
  • Intermediate Matplotlib
  • Basic SciPy
  • Basic pandas
TECHNIQUES
  • Intermediate Python package installation using conda and pip
  • Basics of neural networks or multi-layer perceptrons
  • Basic concepts in using digital imagery for environmental monitoring

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Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.

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choose your plan

pro

monthly
annual
$24.99
$249.99
only $20.83 per month
  • access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
  • choose another free product every time you renew
  • choose twelve free products per year
  • exclusive 50% discount on all purchases
  • Monitoring Changes in Surface Water Using Satellite Image Data project for free

team

monthly
annual
$49.99
$499.99
only $41.67 per month
  • five seats for your team
  • access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
  • choose another free product every time you renew
  • choose twelve free products per year
  • exclusive 50% discount on all purchases
  • Monitoring Changes in Surface Water Using Satellite Image Data project for free