Mastering Earth Observation with AI & Google Earth Engine from Udemy

Harness the power of Google Earth Engine (GEE) and Artificial Intelligence (AI) to analyze satellite imagery and monitor environmental changes. This comprehensive course will guide you through the fundamentals of remote sensing, machine learning, and deep learning for geospatial analysis.

You will start with an introduction to GEE and remote sensing, learning how to access and process satellite imagery. From there, you’ll dive into Land Use and Land Cover (LULC) mapping, applying machine learning and deep learning techniques to classify landscapes effectively.

The course also covers time-series image visualization, allowing you to create animated representations of changes over time. You’ll explore real-world environmental applications, including forest fire mapping, flood analysis using multiple satellite datasets, and landslide susceptibility mapping. Additionally, you will learn change detection analysis using deep learning, a crucial technique for tracking landscape modifications.

By the end of this course, you will have the skills to:

Utilize GEE for satellite image processing and visualization
Implement machine learning and deep learning for LULC classification
Conduct disaster mapping for floods, forest fires, and landslides
Apply change detection techniques to monitor environmental transformations

Whether you are a researcher, student, or GIS professional, this course will equip you with practical skills to analyze Earth’s dynamic surface using cutting-edge geospatial technologies.

What's inside

Learning objectives

Google earth engine
Remote sensing/earth observation
Time series raster analysis
Change detection analysis
Helpful ideas for semester projects
Multiple ways to prepare lulc maps in cloud environment

Landslide susceptibility mapping
Forest fire mapping
Flood analysis and exposure calculation
Work on real projects
Geospatial analysis

Google earth engine
Remote sensing/earth observation
Time series raster analysis
Change detection analysis
Helpful ideas for semester projects
Multiple ways to prepare lulc maps in cloud environment
Landslide susceptibility mapping
Forest fire mapping
Flood analysis and exposure calculation
Work on real projects
Geospatial analysis

Syllabus

Introduction

Lecture Outline

Saudi Arabia Change in agricultural land

Remote sensing basics

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Provides practical skills in analyzing Earth's surface using cutting-edge geospatial technologies, which is highly relevant for professionals in environmental monitoring and disaster management

Covers Land Use and Land Cover (LULC) mapping, which is a core skill for environmental scientists and urban planners who need to classify landscapes effectively

Teaches time-series image visualization, enabling the creation of animated representations of changes over time, which is useful in climate science and environmental impact assessment

Explores real-world environmental applications like forest fire mapping and flood analysis, which are crucial for disaster response and risk assessment professionals

Requires the use of Google Earth Engine, which may require a learning curve for those unfamiliar with the platform, but is a valuable tool for geospatial analysis

Employs machine learning and deep learning techniques, which may require some prior knowledge of these concepts for effective application in LULC classification and change detection

Reviews summary

Applying ai and gee to earth observation

According to learners, this course provides practical, hands-on experience using Google Earth Engine and AI techniques for Earth observation. Students particularly value the real-world projects covering topics like LULC mapping and disaster analysis (floods, fires, landslides). The provided code examples are frequently highlighted as beneficial for applying concepts directly. Some reviewers note the fast pace and suggest having prior programming or GIS experience might be helpful, but overall sentiment is highly positive, making it a strong resource for researchers, students, and professionals in geospatial analysis.

Useful code examples provided.

"Having the code snippets available for download was very helpful for practicing on my own."

"The provided code made it easy to follow along with the lectures and experiment."

"I could easily adapt the course code for my own project ideas after completing the modules."

Covers relevant environmental analysis.

"Analyzing the Dubai flood event was a timely and very practical example that resonated."

"Mapping landslides using GEE is a technique I can immediately use in my work."

"The forest fire mapping module was very well-explained and practical for real applications."

Learn AI for geospatial analysis.

"Learning how to use machine learning for LULC mapping was a game-changer for my research."

"The integration of deep learning with remote sensing data is highly relevant to current trends."

"It was exciting to see how AI can be applied to real-world satellite data problems effectively."

Apply skills with hands-on labs in GEE.

"The hands-on coding examples in Google Earth Engine were incredibly useful and helped solidify my understanding."

"Loved working on the practical projects like flood and fire mapping, it made the concepts concrete."

"Applying the concepts directly in GEE labs solidified my understanding. This was the best part."

Moves quickly, requires prior knowledge.

"The course moves quite fast if you're new to GEE or programming concepts like JavaScript/Python."

"Suggest having some Python or JavaScript basics before starting to keep up with the coding examples."

"Might be challenging to follow the technical parts without prior GIS or remote sensing experience."

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 Mastering Earth Observation with AI & Google Earth Engine with these activities:

Review Remote Sensing Fundamentals

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Solidify your understanding of remote sensing principles to better grasp the concepts used in satellite image analysis.

Browse courses on Electromagnetic Spectrum

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Review textbooks or online resources on remote sensing fundamentals.
Summarize key concepts like electromagnetic spectrum and spectral reflectance.
Practice identifying different land cover types based on their spectral signatures.

Read 'Remote Sensing and Image Interpretation'

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Gain a deeper understanding of remote sensing principles and image interpretation techniques.

View Remote Sensing and Image Interpretation on Amazon

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Read the chapters related to image processing and classification.
Take notes on key concepts and techniques.
Try to apply the concepts to sample satellite images.

Practice GEE Scripting

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Improve your proficiency in GEE scripting to efficiently process and analyze satellite imagery.

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Work through GEE tutorials on data filtering and image manipulation.
Write scripts to calculate NDVI and other vegetation indices.
Experiment with different image visualization techniques.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Create a Time-Series Visualization

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Visualize changes over time to enhance your understanding of environmental dynamics.

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Gather time-series satellite imagery for a specific location.
Process the imagery to highlight changes over time.
Create an animated GIF or video showcasing the changes.
Write a short description explaining the observed changes.

Follow GEE Disaster Mapping Tutorials

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Learn how to apply GEE for disaster mapping through guided tutorials.

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Find tutorials on flood mapping, forest fire mapping, and landslide susceptibility mapping.
Follow the tutorials step-by-step, implementing the techniques in GEE.
Adapt the tutorials to map disasters in different regions.

Develop a Land Cover Classification Project

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Apply your knowledge to a real-world project to solidify your understanding of LULC mapping.

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Select a region of interest and gather relevant satellite imagery.
Implement machine learning algorithms for land cover classification.
Evaluate the accuracy of your classification results.
Document your project and findings.

Read 'Deep Learning for Remote Sensing Images'

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Explore advanced deep learning techniques for remote sensing image analysis.

View Melania on Amazon

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Read the chapters related to CNNs and change detection.
Implement a deep learning model for building change detection.
Compare the results with traditional methods.

Career center

Learners who complete Mastering Earth Observation with AI & Google Earth Engine will develop knowledge and skills that may be useful to these careers:

Remote Sensing Analyst

As a Remote Sensing Analyst, your responsibilities include analyzing geospatial data acquired from various remote sensing platforms to extract meaningful information about the Earth's surface and atmosphere. This course directly helps build a foundation in using Google Earth Engine (GEE) and AI for analyzing satellite imagery, which are essential tools in this field. The course's modules on Land Use and Land Cover (LULC) mapping, disaster mapping for floods and forest fires, and change detection techniques using deep learning offer practical skills directly applicable to the work of a Remote Sensing Analyst.

See salaries and explore the career path for Remote Sensing Analyst

Climate Change Analyst

A Climate Change Analyst studies long-term climate trends and their impacts on the environment and society. This course helps build a strong foundation in analyzing environmental changes using satellite imagery and AI. The skills learned in time-series image visualization and change detection analysis are essential for tracking changes in land cover, vegetation, and water resources. A Climate Change Analyst can use the techniques taught in this course to monitor the effects of climate change, predict future trends, and develop strategies for adaptation and mitigation.

See salaries and explore the career path for Climate Change Analyst

Environmental Consultant

As an Environmental Consultant, your role is to assess environmental impacts and provide solutions for various environmental issues. This course helps equip you with the skills to analyze environmental changes using satellite imagery and AI. The course’s coverage of forest fire mapping, flood analysis, and landslide susceptibility mapping are directly relevant to assessing risks and developing mitigation strategies. Furthermore, Environmental Consultants can use the change detection techniques learned in the course to monitor the effectiveness of environmental protection measures and restoration projects.

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Disaster Response Coordinator

A Disaster Response Coordinator manages and coordinates relief efforts during and after natural disasters. This course will provide you with valuable skills in disaster mapping and analysis using satellite imagery. The course covers flood analysis, forest fire mapping, and landslide susceptibility mapping, all of which are crucial for assessing risks and planning effective response strategies. Learning to use Google Earth Engine (GEE) and AI for rapid disaster assessment will enable a Disaster Response Coordinator to make informed decisions and allocate resources efficiently during crisis situations.

See salaries and explore the career path for Disaster Response Coordinator

Conservation Planner

As a Conservation Planner, your work involves developing strategies for protecting and managing natural resources and biodiversity. This course directly helps you use Google Earth Engine (GEE) and AI to analyze satellite imagery for conservation planning. The course’s coverage of Land Use and Land Cover (LULC) mapping and change detection techniques are valuable for assessing habitat loss, monitoring deforestation, and identifying areas for conservation. The modules on forest fire mapping and landslide susceptibility mapping can help inform strategies for managing natural hazards and protecting vulnerable ecosystems.

See salaries and explore the career path for Conservation Planner

GIS Specialist

A Geographic Information System (GIS) Specialist manages and analyzes spatial data to create maps and visualizations for various applications. This course can help you enhance your GIS skills by introducing you to Google Earth Engine (GEE) and teaching you how to process and analyze satellite imagery. Learning about Land Use and Land Cover (LULC) mapping, time-series image visualization, and disaster mapping will enable you to create more informative and dynamic maps. A GIS Specialist will find the skills taught in this course especially useful for environmental monitoring and urban planning projects.

See salaries and explore the career path for GIS Specialist

Image Analyst

As an Image Analyst, you interpret and analyze images from various sources, including satellite imagery, to extract valuable information. This course offers practical skills for performing geospatial analysis using Google Earth Engine (GEE) and AI. The course’s coverage of Land Use and Land Cover (LULC) mapping, disaster mapping, and change detection techniques are directly relevant to your work. The ability to process and analyze satellite imagery efficiently will enable an Image Analyst to provide critical insights in fields such as environmental monitoring, urban planning, and disaster management.

See salaries and explore the career path for Image Analyst

Cartographer

As a Cartographer, you design and create maps for various purposes, including navigation, education, and urban planning. This course helps enhance your cartographic skills by introducing you to Google Earth Engine (GEE) and AI for analyzing satellite imagery. The course’s coverage of Land Use and Land Cover (LULC) mapping and time-series image visualization are valuable for creating dynamic and informative maps. The abilities to process satellite imagery and incorporate environmental data will enable a Cartographer to create maps that are both visually appealing and scientifically accurate.

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Urban Planner

As an Urban Planner, you are responsible for developing strategies and plans for the sustainable development of urban areas. This course will help you analyze land use changes and environmental impacts using satellite imagery and AI. The course's modules on Land Use and Land Cover (LULC) mapping and change detection techniques are particularly valuable for assessing urban sprawl, monitoring green spaces, and planning infrastructure development. By understanding these techniques, an Urban Planner can make data-driven decisions that promote sustainable and resilient urban environments.

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Environmental Monitoring Technician

As an Environmental Monitoring Technician, your role involves collecting and analyzing environmental data to monitor pollution and assess environmental conditions. This course will help you with the skills to analyze satellite imagery and detect environmental changes using Google Earth Engine (GEE) and AI. The course's modules on flood analysis, forest fire mapping, and change detection techniques are valuable for assessing environmental risks and monitoring the effectiveness of environmental protection measures. An Environmental Monitoring Technician can use these techniques to support environmental monitoring programs and contribute to pollution control efforts.

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Environmental Scientist

An Environmental Scientist studies the interactions between humans and the environment, seeking solutions to environmental problems. This course may be useful, because it will help you with using Google Earth Engine (GEE) and AI to analyze satellite imagery for environmental monitoring. The course covers a variety of topics, including Land Use and Land Cover (LULC) mapping, disaster mapping, and change detection techniques. The course will provide you with the skills to assess environmental impacts, monitor pollution, and develop sustainable practices within the work of an Environmental Scientist.

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Geospatial Data Scientist

A Geospatial Data Scientist uses spatial data and statistical methods to solve complex problems related to geography. This course may be useful because it introduces you to Google Earth Engine (GEE) and covers machine learning and deep learning techniques for geospatial analysis. The skills acquired will help you work with geographic information systems and use remote sensing data. The course's focus on time-series image visualization and real-world environmental applications like landslide susceptibility mapping will allow you to contribute to advanced analytics projects within the geospatial domain.

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Agricultural Analyst

An Agricultural Analyst studies agricultural practices and land use to improve crop yields and sustainability. This course may be useful, as it introduces you to using Google Earth Engine (GEE) and AI for analyzing satellite imagery of agricultural lands. By learning about Land Use and Land Cover (LULC) mapping and time-series image visualization, you can monitor crop health, assess irrigation needs, and detect changes in agricultural land use. An Agricultural Analyst can apply the skills to optimize farming practices and promote sustainable agriculture.

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Remote Sensing Technician

A Remote Sensing Technician assists in the collection, processing, and analysis of remote sensing data. This course may be helpful, as it introduces you to Google Earth Engine (GEE) and the basics of remote sensing. The course will teach you how to access and process satellite imagery, create time-series visualizations, and perform change detection analysis. A Remote Sensing Technician can use these skills to support remote sensing projects and contribute to environmental monitoring and resource management efforts.

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Geospatial Software Developer

A Geospatial Software Developer creates and maintains software applications for analyzing and visualizing spatial data. This course may be useful, because it introduces you to Google Earth Engine (GEE) and its capabilities for processing and analyzing satellite imagery. The course covers various applications, including Land Use and Land Cover (LULC) mapping, disaster mapping, and change detection techniques. A Geospatial Software Developer can use this knowledge to develop innovative geospatial applications for environmental monitoring, urban planning, and disaster management.

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Mastering Earth Observation with AI & Google Earth Engine

What's inside

Learning objectives

Syllabus

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Reviews summary

Applying ai and gee to earth observation

Activities

Career center

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