Google Earth Engine for Machine Learning & Change Detection

Become Expert in Spatial analysis & Remote Sensing for machine learning in land use / land cover in Google Earth Engine

Ratings 4.51 / 5.00

Google Earth Engine for Machine Learning & Change Detection

What You Will 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

Description

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!