Introduction to Google Earth Engine (GEE)
What you'll learn
- Google Earth Engine (GEE)
- Basics of Google Earth Engine oriented JavaScript (JS) Programming language
- Working with vector and raster datasets
- Reducing and Clipping image collectionFiltering the feature or image collection
- Automation
Requirements
- Geographic information basics
Description
Google Earth Engine is a platform for scientific analysis and visualization of geospatial datasets, for academic, non-profit, business and government users.
Google Earth Engine hosts satellite imagery and stores it in a public data archive that includes historical earth images going back more than forty years. The images, ingested on a daily basis, are then made available for global-scale data mining.
Earth Engine also provides APIs and other tools to enable the analysis of large datasets.
Google Earth enables you to travel, explore, and learn about the world by interacting with a virtual globe. You can view satellite imagery, maps, terrain, 3D buildings, and much more.
Earth Engine, on the other hand, is a tool for analyzing geospatial information. You can analyze forest and water coverage, land use change, or assess the health of agricultural fields, among many other possible analyses.
While the two tools rely on some of the same data, only some of Google Earth's imagery and data is available for analysis in Earth Engine.
#AulaGEO
In this course you will learn:
Google Earth Engine Course overview
Introduction
GEE background
GEE applications
GEE Pre-requirements
Basics of Google Earth Engine oriented JavaScript (JS) Programming language
Basic programming concepts
Mostly used GEE JS API syntax
How to write efficient code guide
Working with vector and raster datasets
Where to get different datasets for GEE
How to import and visualize vector datasets
How to import and visualize raster datasets
How to import your own vector or raster dataset in GEE
Filtering the feature or image collection
The need for filtering datasets
Different types of filters
When and where to use filters
Reducing and Clipping image collection
The role of reducers
Different types of reducers
Converting image collections into single image
Operators
Use of operators in programming
Efficient use of Operators in GEE
Evaluating NDVI using operators
Automating the analysis in GEE
The need of automation in GEE
The concept of For-Loops (with reference to Python)
Implementation of For-Loops in GEE using “.Map” function.
Who this course is for:
- GIS users
- GIS developers
- Dadabase managers
- Geospatial enthusiasts
- Developers
Instructors
![AulaGEO Academy](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.0 Instructor Rating
- 2,277 Reviews
- 23,072 Students
- 128 Courses
We choose the best courses and make them available to new audiences.
Our training offer covers the entire spectrum of data intelligence:
Art - Capture - Modeling - Design - Construction - Operation. Using technological development and process improvement as a transverse thread.
The creators of courses with which we have decided to work have been carefully selected, to offer a complementary set of knowledge. We firmly believe that today people do not seek courses to fill their walls with diplomas; but to make their abilities more productive.
- 4.3 Instructor Rating
- 49 Reviews
- 1,375 Students
- 3 Courses
Waleed is a Ph.D. student in Geography at HKBU, Hong Kong. He has been working in the Remote Sensing domain for the last four years focusing on Google Earth Engine, Geospatial Data Science, and Machine/Deep Learning. His research interests include but are not limited to 1) Hazard Risk-Resilience studies, 2) Monitoring rapid urbanization/urban sprawl patterns, 3) Forecasting future land use and land surface temperature patterns, 4) Applications of Google Earth Engine in ecology, Paleoclimatology, and Microclimate (UHI).
His research activities primarily revolve around the use of GEE, RS workflow automation through GEE, Python, ArcGIS Pro, QGIS, TerrSet, PowerBi, and Python-based Geospatial Modules.
He’s focusing on regional/national/global scale studies involving GEE and is also available for working and collaboration opportunities in the aforementioned domains.