Google Earth Engine for Remote Sensing Analysis Masterclass

Get introduced and Become Expert in Geospatial analysis & Remote Sensing for geospatial analysis in Google Earth Engine

4.33 (39 reviews)



5.5 hours


Feb 2021

Last Update
Regular Price

What you will learn

Students will gain access to and a thorough knowledge of the Google Earth Engine platform

Get introduced and advance JavaScript skills on Google Earth Engine platform

Learn how to obtain satellite data, apply image preprocessing for Landsat and Sentinel data in in Google Earth Engine

Learn how import and export spatial data (vector and rsater) from / into the platform

Run analyisis for geospatial applications on the cloud

You'll have a copy of the codes used in the course for your reference

Learn how to calculate spectral indices, create maximim composites and work with Big data on cloud

Apply geospatial analysis for real practical example: flood mapping with Sentinel 2 images

Learn image classification (land cover mapping) basics in Earth Engine


Google Earth Engine for Geospatial Analysis: 3 Courses in 1

This course is designed to take users who use GIS for basic geospatial data/GIS/Remote Sensing analysis to perform geospatial analysis tasks with Big Data on the cloud! This course provides you with all the necessary knowledge to start and advance your skills with Geospatial analysis and includes more than 5 hours of video content, plenty of practical analysis, and downloadable materials. After taking this course, you will be able to implement PRACTICAL, real-life spatial geospatial analysis, and tasks with the Big Data on the cloud.

This course is designed to equip you with the theoretical and practical knowledge of applied geospatial analysis, namely Remote Sensing and some Geographic Information Systems (GIS). This course emphasizes the importance of understanding the Google Earth Engine platform and JavaScript to be able to implement the spatial analysis on the cloud. So, we will start with the thorough introduction to the Earth Engine Platform, then move to the basics of image analysis (which is essential to understand when you would like to work with Earth Engine) and then move to a comprehensive overview of JavaScript basics for spatial analysis. We will cover essential blocks to equip you with the background knowledge and get you started with your analysis on the cloud.

You will learn how to import / export data to Earth Engine, how to perform arithmetical image calculation, how to map functions over image collections, and do iterations. We will cover Sentinel and Landsat image pre-processing and analyses for such applications as drought monitoring, flood mapping, and land cover unsupervised and supervised (machine learning algorithms such as Random Forest) classification.

By the end of the course, you will feel confident and completely understand the basics of JavaScript for spatial analysis and you will learn practical geospatial analysis with Big Data on Google Earth Engine cloud. This course will also prepare you for using geospatial analysis with open source and free software tools.

One important part of the course is the practical exercises. You will be given some precise instructions, codes, and datasets to create for geospatial analysis in Google Earth Engine.

INCLUDED IN THE COURSE: You will have access to all the data used in the course, along with the Java code files. You will also have access to future resources. Enroll in the course today & take advantage of these special materials!


Google Earth Engine for Remote Sensing Analysis Masterclass
Google Earth Engine for Remote Sensing Analysis Masterclass
Google Earth Engine for Remote Sensing Analysis Masterclass
Google Earth Engine for Remote Sensing Analysis Masterclass




Introduction to Google Earth Engine

Why to work with Google Earth Engine?

Lab: Sign up for Google Earth Engine

Interface of Google Earth Engine: Code Editor & Explorer

Short introduction to spatila and satellite data . theory

Types of spatial data: vector and raster data

Introduction to raster data (satellite images)

Difference between sensors and platforms

Introduction to Landstat Program of NASA

Introduction to Sentinel Program of ESA

Overview of datasets in Earth Engine

Getting started with JavaScrip and geospatial analysis in Google Earth Engine

JavaScript - get started!

Lab: Introduction to JavaScript

Lab: Mapping and Reducing Collection - Landsat Example

Lab: Working with image collections and image visualization

Lab: Image visualisation

Section 4: Practical Task

Image Calculations and Mapping Functions in Earth Engine

Introduction to image data: Landsat

Lab: Image Calculations Part 1 - Single Image Calculations

Lab: Image Calculations Part 2 - Create a composite and calculate NDVI

Lab: Calculate Zonal Statistics in Earth Engine

Lab: Short introduction to functions - Maximum NDVI Example

Lab: How to map a function over an image collection: Example of Landsat and NDVI

Lab: How to change default names for output image collection

Importing / Exporting Data in Google Earth Engine

Lab: Export image data from Google Earth Engine: an Introduction

Lab: Importing ratser and vector files into Google Earth Engine

Lab: Image mosaicking, clipping, reprojecting and exporting as tiff to Drive

Section 6 - Practical Task

Examples: Geospatial Analysis in Google Earth Engine

How to work with spatial data and remote sensing images - theory

Lab: Iterating function over Image Collection - Example of Drought Monitoring

Lab: Image preprocessing - Cloud masking of Sentinel 2 images

Normalized Difference Water Index for flood monitoring - thoery

Lab: Flood Mapping with Sentinel-2 and NDWI

Your Project - Flood Mapping

Introduction to Land use / land cover (LULC) classification

Land use land cover mapping - overview

Supervised classification with Google Earth Engine (explorer)

Unsupervised Image Classification and Image Compositing

Supervised land use mapping with Google Earth Engine and Random Forest

Task: Image Classification




Fabian3 February 2021

Een goede introductie over Google Earth Engine. Ik vond met name image compositing, de iterating function en het importeren van eigen data erg interessant. Een pluspunt is dat de toegelichte Javascript-code telkens als tekstbestand kan worden gedownload.

Sunil29 January 2021

The course is a good match but I would still suggest the author to work on delivering the concepts first before explaining the code.

Валерия25 January 2021

This is a great course. The content is very helpful for understanding remote sensing in Earth Engine, and this is one of the best course you can take to learn remote sensinggeospatial analysis & Remote Sensing.

Bogdan22 January 2021

Thank you for this amazing course in Google Earth Engine that helped me learn a lot about Remote sensing fundamentals! What I liked most about this course is that it gives an overall look on Remote Sensing in a simple and easy way and also the fact that it is very practical!!

Sean10 December 2020

Great course that I found very informative. However, there were duplicate videos from your previous course on GEE which was disappointing because I was hopping to be challenged in new ways to develop and refine my skills. Great course in general and will absolutely to future courses with you relating to GIS and GEE.

Triderisetiyono1 December 2020

I wish resource availability and organization of the course can be improved in the near future. Other than that, this was a good course, I learned a lot!

Людмила7 October 2020

Excellent instruction. I tried many instructors to refresh my concepts and learn new things, not that other instructors were bad, some of them were very good too, but this course structured with the Questions and Solutions codes, to the point material with targeted and simple approach appealed to my learning style, instruction pace was excellent. This course motivated me to enroll in other courses by the same instructor.

Jessie21 August 2020

A step by step learning from very basics of JAvaScript to advanced topics such as machine learning! great!


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