Learn machine learning, big data and land use land cover classification using Google Earth Engine cloud API
Do you want to implement a land cover classification algorithm on the cloud?
Do you want to quickly gain proficiency in digital image processing and classification?
Do you want to become a spatial data scientist?
Enroll in this Remote Sensing for Land Cover Mapping in Google Earth Engine course and master land use land cover classification on the cloud.
In this course, we will cover the following topics:
Unsupervised Classification (Clustering)
Training Reference data
Supervised Classification with Landsat
Supervised Classification with Sentinel
Supervised Classification with MODIS
Change Detection Analysis (Water and Forest Change Analysis)
Global Land Cover Products (NLCD, Globe Cover, and MODIS Land Cover)
I will provide you with hands-on training with example data, sample scripts, and real-world applications. Â
By taking this course, you will take your spatial data science skills to the next level by gaining proficiency in processing satellite data, applying classification algorithms, and assessing classification accuracy using a confusion matrix. We will apply classification using various satellites including Landsat, MODIS, and Sentinel. When you are done with this course, you will master methods on how to apply machine learning and supervised classification algorithm using cloud computing and big geospatial data.
Jump in right now to enroll. To get started click the enroll button.
Learn to apply land use land cover classification using satellite data
Land use land cover change detection analysis
Perform accuracy assessment of land use classifications
2 Lectures
1 Lectures
1 Lectures
1 Lectures
Dr. Alemayehu Midekisa is a geospatial data scientist with over 15 years of professional experience in academia and industry. His research focus is on leveraging geospatial AI, big Earth observation data, and cloud computing to monitor environmental changes. Dr. Midekisa is particularly interested in applying machine learning models, large-scale remote sensing data, and cloud computing such as Google Earth Engine...
Spatial eLearning provides online courses teaching remote sensing, GIS, machine learning, cloud computing, and spatial data science skills. Our mission is to make highly valuable geospatial data science skills accessible and affordable to anyone and anywhere around the world. We teach 20,000 plus students in over 170 countries around the world. Spatial eLearning’s valuable learning resources include webinars, books, free...
Achei bem informativo, porém faltou mais detalhamento com os códigos, a disponibilização dos scripts utilizados e talvez diferentes formas de análises
Great content, but quite repetitive for the ones who've previously attended the "GEE Mega Course'
very good course
As a Beginner, it was a good experience with three lectures.
It is a good course for anyone who interested to know more about classification using Landsat, Sentinel and MODIS. It is useful as the instructor explain the process step by step.
Next, I am interested to learn about land change detection. Thank you for this course.
it would be better If code was provided
Scripts not shared. Can't copy everything while following lecture.
yes definitely
understandable .
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Gabriel S.
Just started well