In this video, we take you step-by-step through a fascinating process of historical climate classification using Google Earth Engine (GEE). We'll dive into the ERA5-Land and MODIS Terra datasets, applying a K-Means clustering model to uncover climate patterns over time (2000-2020).
✨ Key Highlights:
• Define a region of interest with coordinates.
• Load and combine climate variables (temperature & precipitation).
• Train a K-Means clustering model to classify the climate data.
• Visualize and export the classified climate map.
• Perform area and temperature calculations for each climate class.
• Analyse NDVI time series for the climate class with MODIS data.
📊 Charts & Visualization:
• Climate classification map with color-coded clusters.
• NDVI time series for detailed vegetation insights.
• Temperature statistics and area distribution per climate class
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🚀 Useful link:
Code link: https://code.earthengine.google.com/4...
ERA5 Dataset: https://developers.google.com/earth-e...
MODIS Terra: https://developers.google.com/earth-e...
🚀 Whether you're a climate enthusiast or a GEE pro, this video is packed with techniques to enhance your Earth observation projects!
🔔 Don't forget to like, share, and subscribe for more tutorials on climate analysis, remote sensing, and GEE!
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#climateclassification #googleearthengine #k-mean #clusteringmodel #modis #ERA5