Surv-Lukmon/Crop-Classification
Crop type classification with 10m spatial resolution using Random Forest Machine Learning Algorithm and time-series sentinel-2 images in Google Earth Engine Python API.
This tool helps agricultural analysts and researchers create detailed maps showing different crop types in a specific area. By using satellite images taken over several months, it takes raw image data and produces high-resolution crop classification maps. This allows users to accurately identify and distinguish between various crops across large agricultural regions.
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Use this if you need to generate precise, high-resolution maps of crop distribution for agricultural planning, land use analysis, or environmental monitoring.
Not ideal if you require real-time crop monitoring or need to classify crops in regions where consistent, cloud-free satellite imagery is unavailable.
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Last pushed
Aug 07, 2024
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