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Precision Agriculture: Crop Mapping using Machine Learning and Sentinel-2 Satellite Imagery
March 18, 2024, 4:44 a.m. | Kui Zhao, Siyang Wu, Chang Liu, Yue Wu, Natalia Efremova
cs.CV updates on arXiv.org arxiv.org
Abstract: Food security has grown in significance due to the changing climate and its warming effects. To support the rising demand for agricultural products and to minimize the negative impact of climate change and mass cultivation, precision agriculture has become increasingly important for crop cultivation. This study employs deep learning and pixel-based machine learning methods to accurately segment lavender fields for precision agriculture, utilizing various spectral band combinations extracted from Sentinel-2 satellite imagery. Our fine-tuned final …
abstract agriculture arxiv become change climate climate change cs.cv demand eess.iv effects food impact machine machine learning mapping negative precision products satellite security sentinel significance support type
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