Use of geotechnologies to obtain planted area of soybeans and corn in Santa Catarina
Authors
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Tarik Cuchi
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Haroldo Tavares Elias
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João Rogério Alves
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Bruna Parente Porto
Abstract
Monitoring soybean and corn crops is essential for agribusiness in Santa Catarina. This study, an ongoing work presenting promising results, trained an artificial intelligence (AI) algorithm to classify soybeans, grain corn, and silage corn and estimate the net planted area for the 2023/2024 harvest. Time series of orbital images, spectral indices, and terrain data were used. The classifier achieved an overall accuracy of 92% and a Kappa of 0.88, proving to be effective, auditable, and promising for agricultural monitoring in the state , serving as a basis for future improvements.
References
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Keywords
- Remote Sensing
- Artificial Intelligence
- Machine Learning
- Google Earth Engine