Google Earth Engine: Change detection analysis using near real-time Dynamic Global Land cover data

In this tutorial I will show how to access the Dymanic World Landcover dataset and further how to do the change detection analysis using the data
Dynamic World is a near realtime 10m resolution global land use land cover dataset based on Sentinel-2 satellite Images, produced using deep learning, freely available and openly licensed. It is the result of a partnership between Google and the World Resources Institute, to produce a dynamic dataset of the physical material on the surface of the Earth. Dynamic World is intended to be used as a data product for users to add custom rules with which to assign final class values, producing derivative land cover maps.
This data is available under a Creative Commons BY-4.0 license and requires the following attribution: This dataset is produced for the Dynamic World Project by Google in partnership with National Geographic Society and the World Resources Institute.
Earth Engine script used in video:
Accessing Landcover data: code.earthengine.google.com/b...
Change Detection Analysis: code.earthengine.google.com/0...
Resources:
www.dynamicworld.app/
www.dynamicworld.app/about
earthoutreach.users.earthengi...
developers.google.com/earth-e...
github.com/google/dynamicworld
Timeline of the video:
00:00 Introduction
03:27 Accessing the near real-time Dynamic World Global Lancover data in GEE
16:15 How to do change detection analysis using the data

[@OpenGeoLab]

Zoom to any part of area of interest hillshade layer will load...

[@patrichpapilaya6845]

thanks Bro.. it is very useful

[@masengoilunga6591]

very exciting

[@aidosmakhanov8]

Hello. Can we identify the deforestation area by this methodology? If yes can you share the conditional statement for this logic?

[@prof.biplabbiswas5576]

Great Tutorials. Thanks. How can we export the LULC layer with the classified code as unique pixel value - if you please reply, that would be very helpful. Thanks

[@prajwalparmar4168]

What is the timeline of this dataset?

[@indrajitpoddar2777]

Probability Hillshade: Tile error: Output of image computation is too large (9 bands for 198723105 pixels = 13645.2 MiB > 80.0 MiB).
If this is a reduction, try specifying a larger 'tileScale' parameter.
Kindly fixed this Error in LULC Code......

[@OpenGeoLab]

Zoom to any part of area of interest hillshade layer will load...