Satellite image crop classification utilizes remote sensing technology for efficient monitoring and analysis of agricultural land. By acquiring satellite data at different times and spectral bands, the spectral characteristics of crops can be extracted to identify different crop types. In recent years, with the development of machine learning and deep learning algorithms, classification accuracy has significantly improved.

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[1] yao liu, "agriculture", IEEE Dataport, 2025. [Online]. Available: http://dx.doi.org/10.21227/w28w-9x25. Accessed: Mar. 16, 2025.
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title = {agriculture},
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yao liu. (2025). agriculture. IEEE Dataport. http://dx.doi.org/10.21227/w28w-9x25
yao liu, 2025. agriculture. Available at: http://dx.doi.org/10.21227/w28w-9x25.
yao liu. (2025). "agriculture." Web.
1. yao liu. agriculture [Internet]. IEEE Dataport; 2025. Available from : http://dx.doi.org/10.21227/w28w-9x25
yao liu. "agriculture." doi: 10.21227/w28w-9x25