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Google Earth Engine for Machine Learning & Change Detection

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Description

What you’ll learn

  • Students will gain access to and a thorough knowledge of the Google Earth Engine platform
  • Implement machine learning algorithms on geospatial (satellite images) data in Earth Engine for LULC mapping
  • Get introduced and advance JavaScript skills on Google Earth Engine platform
  • Fully understand the main types of Machine Learning (supervised and unsupervised learning)
  • Learn how to apply supervised and unsupervised Machine Learning algorithms in Google Earth Engine
  • Learn how to obtain satellite data, apply image preprocessing, create training and validation data in Google Earth Engine
  • Implement calculation of change detection (pre and post-event detection) based on spectral indices
  • You’ll have a copy of the codes used in the course for your reference

Land Use/Land Cover Mapping and Change Detection with Machine Learning in Google Earth Engine

Are you ready to elevate your geospatial analysis skills and become proficient in land use and land cover (LULC) mapping and change detection? This comprehensive course is designed to empower users who have a basic background in GIS, geospatial data, and remote sensing with the knowledge and tools required for advanced geospatial analysis.

Course Highlights:

  • Extensive coverage of machine learning algorithms and their practical application

  • In-depth understanding of Google Earth Engine for LULC mapping and change detection

  • Step-by-step guidance on acquiring satellite data, preprocessing, spectral indices calculation, and change map design

  • Real-world projects and practical exercises to reinforce your skills

  • Downloadable materials, including data and Java code files

  • Access to future resources to support your geospatial endeavors

Course Focus:

This course is more than just theory; it’s about hands-on learning and practical implementation. You’ll gain proficiency in unsupervised and supervised classification strategies for LULC mapping, which is a fundamental skill for GIS and remote sensing analysts. By the end of this course, you’ll feel confident in performing advanced geospatial analysis, including machine learning algorithms for mapping and change detection, all using real and openly available data in Google Earth Engine.

Why Choose This Course:

Unlike other training resources, every lecture in this course aims to enhance your GIS and remote sensing skills in a clear and actionable manner. You’ll be equipped to analyze spatial data for your own projects and earn recognition from future employers for your advanced GIS skills and knowledge of cutting-edge LULC techniques.

What You’ll Learn:

  • Google Earth Engine sign-in and interface navigation

  • Data preprocessing on the cloud and spectral indices calculation

  • Introduction to JavaScript

  • Machine learning theory and its application in GIS

  • Classification of satellite images using various machine learning algorithms (supervised and unsupervised) in Google Earth Engine

  • Training, validation data collection, and accuracy assessment

  • Change detection techniques in Google Earth Engine

  • Completion of your own geospatial project on the cloud

Enroll Today:

If you’re a geographer, programmer, social scientist, geologist, or any professional seeking to use LULC maps in your field and want to master state-of-the-art classification algorithms for tasks like land cover and land use mapping, this course is your solution. Sign up now and unlock the confidence and expertise to tackle complex geospatial challenges!

INCLUDED IN THE COURSE: You’ll have access to all the data used throughout the course, along with Java code files. Plus, you’ll enjoy access to future resources, making this course a valuable investment in your geospatial career. Enroll today and take advantage of these special materials!

Who this course is for:

  • Geographers, Programmers, geologists, biologists, social scientists, or every other expert who deals with GIS maps in their field

Course content

  • Introduction2 lectures • 12min
  • Introduction
  • Getting started with Google Earth Engine & EO browser5 lectures • 45min
  • Getting started with Google Earth Engine & EO browser
  • Basics of Jave Scrips for Google Earth Engine and first steps in image analysis9 lectures • 1hr 25min
  • Basics of Jave Scrips for Google Earth Engine and first steps in image analysis
  • Theory: on Machine Learning and Image CLassification7 lectures • 1hr 9min
  • Theory: on Machine Learning and Image CLassification
  • Unsupervised (K-means) image analysis in Google Earth Engine4 lectures • 36min
  • Unsupervised (K-means) image analysis in Google Earth Engine
  • Supervised image analysis in Google Earth Engine6 lectures • 1hr 25min
  • Supervised image analysis in Google Earth Engine
  • Introduction to change detection in Google Earth Engine6 lectures • 44min
  • Introduction to change detection in Google Earth Engine

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