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Updated in [July 25th, 2023]

This course is designed to take users who use GIS for basic geospatial data/GIS/Remote Sensing analysis to the next level by introducing them to the exciting capabilities of Google Earth Engine. Through this course, users will learn how to use Machine Learning algorithms for land use and land cover (LULC) mapping and change detection. By the end of the course, users will be proficient in unsupervised and supervised classification strategies for LULC mapping, spectral indices calculation, and change detection. They will also gain an understanding of the practical aspects of GIS and Remote Sensing, such as acquiring satellite data, assessing the accuracy of their map, and designing a beautiful change map. This course is ideal for professionals such as geographers, programmers, social scientists, geologists, and all other experts who need to use LULC maps in their field. Through practical exercises, users will be given precise instructions, codes, and datasets to create LULC maps and change maps using Google Earth Engine. Downloadable materials will also be provided to teach users how to sign in to Google Earth Engine.

Course Syllabus

Introduction

Getting started with Google Earth Engine & EO browser

Basics of Jave Scrips for Google Earth Engine and first steps in image analysis

Theory: on Machine Learning and Image CLassification

Unsupervised (K-means) image analysis in Google Earth Engine

Supervised image analysis in Google Earth Engine

Introduction to change detection in Google Earth Engine