Supervised Classification in GEE | Sentinel-2 LULC Classification and Mapping in 5+5 Minutes! скачать в хорошем качестве

Supervised Classification in GEE | Sentinel-2 LULC Classification and Mapping in 5+5 Minutes!

Code : https://code.earthengine.google.com/5... In this quick and powerful tutorial, learn how to perform Supervised Classification using Sentinel-2 imagery in Google Earth Engine (GEE) to create a Land Use Land Cover (LULC) map of your study area. 🚀 This is the fastest and most efficient method for beginners and professionals to create high-quality classification maps using open-source satellite data. 📌 What You’ll Learn: How to access and preprocess Sentinel-2 data in GEE How to define training samples for supervised classification Applying classification algorithms (like CART, SVM, or Random Forest) Visualizing and exporting your final LULC map ✅ Keywords Covered: Supervised Classification, Google Earth Engine Tutorial, Sentinel-2 Land Cover, LULC Mapping, Remote Sensing, GIS, Machine Learning, Land Cover Classification, Earth Observation, GEE for Beginners, Satellite Image Classification 🔍 Perfect for students, researchers, GIS analysts, and remote sensing enthusiasts working on land cover classification using satellite imagery. 📥 Download code & datasets: [Insert GitHub or GEE script link if available] 👉 Don’t forget to like, subscribe, and comment if you find this helpful! #GoogleEarthEngine #SupervisedClassification #Sentinel2 #LULC #RemoteSensing #GIS #GEEtutorial