Google Earth Engine Mega Course: Remote Sensing Applications from Udemy

Welcome to the Google Earth Engine Mega Course: Remote Sensing Applications, the only course you need to learn to code and become an Earth Engine expert. With a 4.5 average rating, this Earth Engine course is one of the highest-rated courses.

At 12+ hours, this Earth Engine course is without a doubt the most comprehensive Google Earth Engine course available online. Even if you have zero programming experience, this course will take you from beginner to mastery.

Here's why:

The course is taught by an experienced geospatial data scientist.
The course has been updated to be 2024-ready and you'll be learning the latest tools available on the cloud.
The curriculum was developed over five years, with comprehensive student testing and feedback.
We've taught over 20,000 students how to code and apply spatial data science and cloud computing.
The course is constantly updated with new content, with new projects, and modules.
You will have access to example data and sample scripts.

In this course, we will cover the following topics:

Introduction to Earth Engine JavaScript API
Explore Earth Engine
Sign Up with Earth Engine
Basic JavaScript Data Types
Earth Engine Objects
Client versus Server Side Objects
Image Visualization
Filtering Image Collection
Feature Collection
Clipping Images
Import and Export Images
Cloud Masking
Calculate Spectral Indices
Reducers
Zonal Statistics
Machine Learning Classification
Drought Monitoring
Urban Mapping
Surface Water Mapping
Forest Monitoring
Air Pollution Monitoring
Earth Engine Web Apps

The course includes over 12+ hours of HD video tutorials. We'll take you step-by-step through engaging video tutorials and teach you everything you need to know to succeed as a spatial data scientist and Earth Engine expert.

So, what are you waiting for? Enroll now and start learning.

What's inside

Learning objectives

Students will access and sign up the google earth engine platform
Download, process and visualize various satellite data including landsat, modis, sentinel and viirs
Apply gis techniques to process and analyze various vector data
Generate various visualizations including time series and histogram charts from remote sensing data
Export various vector data including kml and csv files

Export images, charts and videos
Learn to perform various image processing including mosaiccing, compositing, zonal statistics, and neighborhood analysis
Classification of satellite data with machine learning
Master javascript programming language to process earth observations data
Complete a final gis project on downloading, processing, analyzing and visualizing big data

Students will access and sign up the google earth engine platform
Download, process and visualize various satellite data including landsat, modis, sentinel and viirs
Apply gis techniques to process and analyze various vector data
Generate various visualizations including time series and histogram charts from remote sensing data
Export various vector data including kml and csv files
Export images, charts and videos
Learn to perform various image processing including mosaiccing, compositing, zonal statistics, and neighborhood analysis
Classification of satellite data with machine learning
Master javascript programming language to process earth observations data
Complete a final gis project on downloading, processing, analyzing and visualizing big data

Syllabus

Welcome

Introduction to Earth Engine API

Introduction to Earth Engine

Set Up Environment

Get Started with Google Earth Engine

Hello World

Basic JavaScript Data Types

Earth Engine Objects

Client Side Versus Server Side Objects

Digital Image Processing

Remote Sensing Workflows

Image Visualization

Image Collection

Filtering Image Collection

Feature Collection

Clipping Images

Export and Import Geospatial Data

Export Image

Import Shapefiles

Exercise

Advanced Image Processing

Simple Cloud Masking

Advanced Cloud Masking

Calculate Spectral Indices

Reducers

Zonal Statistics

Extract Sample Points

Land Cover Classification

Clustering Classification

Random Forest Classification

Drought Monitoring

LST Analysis

ET Analysis

Soil Moisture Analysis

Water Balance Calculation

Urban Mapping

NLCD Impervious Surface

WorldPop Population

Surface Water Mapping

Water Occurrence

Water Mask

Annual Water Map

National Water Map

Water Prediction with Machine Learning

Forest Monitoring

Global Forest Cover

Global Tree Cover

National Tree Cover

Forest Gain Loss

Forest Gain Loss Area Calculation

Air Pollution Monitoring

Carbonmonoxide

Methane

Nitrogenoxide

Sulferdioxide

Earth Engine Apps

Introduction to Earth Engine Apps

LatLon Locator

Earth Engine Widgets

Dynamic World Viewer App

Final Project

Bonus Lectures

Bonus

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Covers a wide range of remote sensing applications, including drought monitoring, urban mapping, and air pollution monitoring, which are highly relevant in environmental science and urban planning

Teaches JavaScript programming alongside Earth Engine, which develops valuable skills for customizing analyses and building web applications for geospatial data

Explores the Google Earth Engine JavaScript API, which is essential for accessing and processing large-scale geospatial data for research and analysis

Starts with basic JavaScript data types and Earth Engine objects, which builds a strong foundation for learners with little to no programming experience

Includes machine learning classification techniques for satellite data, which are increasingly important for automated analysis and pattern recognition in remote sensing

Requires learners to sign up for Google Earth Engine, which may involve a review process and acceptance based on project proposals or research interests

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Google Earth Engine Mega Course: Remote Sensing Applications with these activities:

Review Remote Sensing Fundamentals

Show steps

Reinforce your understanding of remote sensing principles, including electromagnetic spectrum, sensor types, and image resolution, to better grasp the data used in Google Earth Engine.

Browse courses on Remote Sensing

Show steps

Review textbooks or online resources on remote sensing.
Summarize key concepts and definitions.
Practice identifying different features in satellite imagery.

Brush Up on JavaScript Basics

Show steps

Strengthen your JavaScript skills, focusing on data types, functions, and control flow, as Google Earth Engine uses JavaScript API for scripting and analysis.

Browse courses on JavaScript

Show steps

Complete online JavaScript tutorials or coding exercises.
Practice writing simple JavaScript functions.
Review JavaScript syntax and best practices.

Read 'Remote Sensing and Image Interpretation'

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Gain a deeper understanding of remote sensing principles and image interpretation techniques, which are essential for effectively using Google Earth Engine.

View Remote Sensing and Image Interpretation,... on Amazon

Show steps

Read selected chapters focusing on image processing and analysis.
Take notes on key concepts and techniques.
Relate the concepts to the Google Earth Engine platform.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Practice Image Filtering in Earth Engine

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Sharpen your skills in filtering image collections based on metadata and properties within Google Earth Engine, a crucial skill for data selection and analysis.

Browse courses on Image Filtering

Show steps

Filter Landsat images by date and cloud cover.
Filter Sentinel-2 images by spectral bands.
Experiment with different filtering criteria.

Document a Cloud Masking Workflow

Show steps

Solidify your understanding of cloud masking techniques by creating a detailed documentation of a cloud masking workflow in Google Earth Engine, including code snippets and explanations.

Show steps

Choose a cloud masking algorithm.
Implement the algorithm in Google Earth Engine.
Document each step of the workflow with clear explanations.
Share your documentation with other learners.

Develop a Land Cover Classification Project

Show steps

Apply your knowledge of machine learning and remote sensing to develop a land cover classification project using Google Earth Engine, demonstrating your ability to process and analyze satellite data.

Browse courses on Machine Learning

Show steps

Select a study area and time period.
Gather training data for different land cover classes.
Train a machine learning classifier in Google Earth Engine.
Evaluate the accuracy of the classification results.

Study 'Google Earth Engine Applications'

Show steps

Explore real-world applications of Google Earth Engine to deepen your understanding of its capabilities and potential uses in various fields.

View Earth Engine and Geemap: Geospatial Data... on Amazon

Show steps

Read case studies relevant to your interests.
Analyze the code and workflows used in each application.
Consider how you can adapt these applications to your own projects.

Career center

Learners who complete Google Earth Engine Mega Course: Remote Sensing Applications will develop knowledge and skills that may be useful to these careers:

Geospatial Data Scientist

Geospatial Data Scientists apply programming and data analysis skills to spatial problems. This role focuses on extracting insights from geographic data. This course helps develop the necessary skills for this role, including expertise in JavaScript and the Earth Engine API. The curriculum's coverage of image processing, machine learning classification, and cloud computing sets up a strong foundation for this career. The course also offers practical experience in performing various image processing techniques. Someone interested in becoming a Geospatial Data Scientist will benefit from the comprehensive hands-on experience offered in this course.

See salaries and explore the career path for Geospatial Data Scientist

Remote Sensing Analyst

A Remote Sensing Analyst uses satellite and aerial imagery to gather data about the Earth's surface. This role involves image processing, analysis, and interpretation, all of which are central to this course. The course helps develop expertise in remote sensing workflows, image visualization, and digital image processing. The curriculum also covers techniques such as cloud masking, spectral indices calculation, and zonal statistics which are essential to the work of a Remote Sensing Analyst. By taking this course, you gain hands-on experience using Google Earth Engine to process large datasets and conduct complex spatial analyses.

See salaries and explore the career path for Remote Sensing Analyst

GIS Specialist

A GIS Specialist uses geographic information systems to create and analyze spatial data. This role requires an understanding of mapping and spatial analysis techniques, and this course provides a valuable introduction to those concepts. The course teaches learners how to process and analyze various vector data, generate visualizations like time series and histogram charts, and export various files. The hands-on experience with Google Earth Engine provided by this course helps develop the proficiency needed for a GIS Specialist. The skills learned in data processing, analysis and visualization are directly applicable to this role.

See salaries and explore the career path for GIS Specialist

Environmental Analyst

An Environmental Analyst assesses environmental conditions using a variety of data sources. This role often uses remote sensing data to study changes in land cover, water resources, and air quality. This course is useful because it covers many topics relevant to environmental analysis, including drought monitoring, urban mapping, surface water mapping, forest monitoring, and air pollution monitoring. This course's focus on using Earth Engine for various applications provides the practical skills needed for an Environmental Analyst. This course can equip an Environmental Analyst with the tools to analyze environmental changes using the latest cloud-based spatial analysis platforms.

See salaries and explore the career path for Environmental Analyst

Forestry Specialist

A Forestry Specialist manages and studies forest resources, often using remote sensing data to monitor forest health, cover, and change. This course is valuable for future Forestry Specialists, as the course material covers forest monitoring, global forest cover, global tree cover, and forest gain loss analysis, teaching techniques necessary for this line of work. Gaining the skill to use Google Earth Engine to analyze forest data would be advantageous to anyone interested in a role as a Forestry Specialist. This course helps someone to understand forest dynamics using satellite imagery.

See salaries and explore the career path for Forestry Specialist

Remote Sensing Technician

A Remote Sensing Technician works with remote sensing data, often operating the equipment and processing the data under the guidance of analysts and scientists. This course provides training on the use of Google Earth Engine and may be useful for those looking to become Remote Sensing Technicians. The course provides a practical foundation in remote sensing using a cloud platform to process large datasets. The course topics include the processing of satellite data, visualization, and vector data analysis. The skills gained in this course are valuable for a Remote Sensing Technician to complete their assignments.

See salaries and explore the career path for Remote Sensing Technician

Geographer

Geographers study the Earth's surface, its spatial organization, and the relationships between people and the environment. This role has multiple sub-disciplines. The tools and techniques of remote sensing are essential to a Geographer's work. This course provides the practical skills to analyze and interpret satellite imagery using Google Earth Engine. Topics such as digital image processing, land cover classification, and change detection are all very relevant. This course prepares a Geographer to analyze spatial data effectively.

See salaries and explore the career path for Geographer

Climate Change Analyst

Climate Change Analysts study the impacts of climate change, and this role involves analyzing data from various sources, including remote sensing imagery. This course is suitable for future Climate Change Analysts because it provides tools and techniques for analyzing environmental data related to climate. The course covers topics such as drought monitoring, air pollution monitoring, and land cover changes, all of which are important in climate change research. With the skills in using Google Earth Engine from this course, a Climate Change Analyst can effectively study environmental changes.

See salaries and explore the career path for Climate Change Analyst

Disaster Response Analyst

A Disaster Response Analyst uses data to help prepare for and respond to disasters. This role often utilizes remote sensing data to assess damage, track changes, and support relief efforts. This course can benefit a Disaster Response Analyst due to the techniques it teaches for image processing, data visualization, and change detection. The course covers many necessary skills for disaster response, such as analyzing changes in surface water and land cover in a short period of time using the Google Earth Engine. The skills taught in this course for extracting insights from earth observation data can be very useful to a Disaster Response Analyst.

See salaries and explore the career path for Disaster Response Analyst

Water Resources Analyst

A Water Resources Analyst studies the distribution and management of water resources. This role uses data analysis and modeling techniques to understand water availability, quality, and usage. This course may be useful for anyone interested in taking up this role due to its coverage of surface water mapping, water occurrence, and water prediction with machine learning. Specifically, the course provides hands-on training in the Google Earth Engine platform which helps analyze water resources. An aspiring Water Resources Analyst can learn to process, analyze and visualize water-related data from remote sensing through this course.

See salaries and explore the career path for Water Resources Analyst

Agricultural Analyst

An Agricultural Analyst studies agriculture and food systems. This role may include the analysis of crop health, land use patterns, and environmental impacts with remote sensing data. This course may be useful to an Agricultural Analyst due to its coverage of various remote sensing applications, including land cover classification, drought monitoring, and soil moisture analysis. The hands-on experience from this course in working with satellite imagery helps develop the analytical skills needed for this role. An Agricultural Analyst can use techniques learned in this course to gather insights on agricultural practices.

See salaries and explore the career path for Agricultural Analyst

Urban Planner

Urban Planners design and develop communities. They use data analysis to inform decisions about land use, infrastructure, and development. This course may be useful for urban planners because it teaches remote sensing techniques to analyze urban environments, including urban mapping, population studies, and impervious surface analysis. These techniques are covered through the use of satellite imagery in this course. This course may be valuable to Urban Planners who wish to use satellite data to inform their planning decisions.

See salaries and explore the career path for Urban Planner

Land Use Planner

A Land Use Planner is involved in decisions relating to land use and development. This role will involve the analysis of land cover, environmental impact, and zoning laws. This course may be helpful to a Land Use Planner by providing tools to analyze land cover changes, urban sprawl, and environmental changes. The use of remote sensing data to visualize these changes may be helpful for planning purposes. This course provides the tools and techniques to a Land Use Planner to effectively inform planning decisions using Earth observation data.

See salaries and explore the career path for Land Use Planner

Environmental Consultant

An Environmental Consultant advises organizations on environmental sustainability. This role often requires data analysis and report creation. This course may be useful for an Environmental Consultant due to its focus on environmental monitoring using remote sensing. Topics like forest analysis, water mapping, and air pollution monitoring provide insights for environmental consultation. The ability to process large datasets using Google Earth Engine may be valuable to an Environmental Consultant. This course provides hands-on experience for environmental data analysis.

See salaries and explore the career path for Environmental Consultant

Cartographer

A Cartographer designs and creates maps, often by using geographic data. This course may be helpful since it covers the basics of mapping as well as how to export and import geospatial data. The course covers remote sensing workflows and data visualization, which form an important part of a cartographer's tasks. While this role may not be solely focused on remote sensing, the skills developed in this course might be valuable for a Cartographer. This course teaches the manipulation of spatial data.

See salaries and explore the career path for Cartographer

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Google Earth Engine Mega Course: Remote Sensing Applications.

Earth Engine and Geemap

Save

Showcases various real-world applications of Google Earth Engine. It provides practical examples and case studies that demonstrate how to use the platform for environmental monitoring, natural resource management, and urban planning. It valuable resource for learning how to apply Google Earth Engine to solve real-world problems and expand on the course materials. This book is particularly useful as additional reading to deepen understanding.

Earth Engine and Geemap: Geospatial Data Science...

Paperback

$$$

Remote Sensing and Image Interpretation, Seventh...

Save

Provides a comprehensive overview of remote sensing principles and techniques. It covers a wide range of topics, including image acquisition, processing, and interpretation. It valuable reference for understanding the theoretical foundations of remote sensing and how they apply to practical applications in Google Earth Engine. This book is commonly used as a textbook in remote sensing courses.

Remote Sensing and Image Interpretation, Seventh...

Paperback

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Remote Sensing and Image Interpretation, Seventh...

Kindle Edition

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Google Earth Engine Mega Course

Remote Sensing Applications

What's inside

Learning objectives

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

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