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Cassava Yield Prediction via Geospatial Analysis by 24070146005 is a document available to read on EtoBox.
This research develops a yield prediction model for cassava in Indonesia using geospatial fuzzy expert systems and remote sensing data. The study identifies suitable land areas for cassava production through land suitability analysis (LSA) and employs vegetation indices from Sentinel-2 datasets to predict yields. Results indicate that 42.17% of the land is highly suitable for cassava, with the combined model achieving a prediction accuracy of R2 = 0.77, which can aid in regional food security management.
- Author
- 24070146005
- Language
- EN