LULC Satellite Image Classification Using Machine Learning: How to Prepare Dataset, Data Preparation

In this video, we will prepare our dataset for the land use land cover classification task using Sentinel-2 satellite data and machine learning algorithms. This tutorial will help you understand how to prepare satellite data for an image classification task using machine learning algorithms.
The code examples are available on our GitHub page:
github.com/BEEILAB/LULC-Class...
The dataset can be found in the following link:
github.com/iremozcann/Land-Co...
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[@Imrantigers446]

Another great video! You always deliver quality content.

[@BEEiLabTV]

Thank you!

[@itcclalian]

Great video! Keep up the good work.

[@BEEiLabTV]

Thanks so much!

[@rac_dev]

You have a real talent for making engaging and informative videos. Fantastic job!

[@BEEiLabTV]

Thanks for your kind words!

[@MathsMadeEasy1]

Your enthusiasm is infectious! Keep making great content.

[@BEEiLabTV]

Thanks!

[@sugatube777]

This video was so well-produced! Absolutely love your content.

[@BEEiLabTV]

Glad to hear!

[@youtubshort672]

Your videos are so refreshing! Love your content.

[@BEEiLabTV]

Thanks!

[@vimalshrivastava6586]

Please could you make a video on how to prepare the ground truth image?

[@BEEiLabTV]

Sure, we will make asap!

[@chiranjitsingha7787]

How to out put as export full prediction map....

[@haseebhabeebulla2200]

How to collect ground truth data for this LULC

[@BEEiLabTV]

Others collect this ground truth and is public to use now! But if you need to collect the ground truth for your study, you can use GPS and other surveying instruments to collect precise ground truth! And if you are not looking for precise ground truth, you can use Google Earth or a high-resolution satellite to label the land uses.