Achieving sustainable agricultural development, improving resource efficiency, and ensuring sustainable food security are among the fundamental goals of the general agricultural policies of the Islamic Republic of Iran. In this regard, the present study aims to design and develop a technological framework for modernizing the country's agricultural monitoring system. The proposed framework, titled "Agricultural Hybrid Network," is based on the integration of high-resolution drone data and multispectral satellite data, which, by utilizing deep learning algorithms and advanced transformer-based architectures, enables continuous monitoring of crop status in Iranian regions. In addition to providing a data-driven infrastructure for decision-making, this framework is aligned with the principles of general agricultural policies, including improving water and soil productivity, improving the exploitation system, sustainable rural development, and modernizing production based on indigenous knowledge and new technologies. The developed model enables offline and low-cost monitoring in areas without communication infrastructure. These achievements are a practical step towards realizing general agricultural policies, namely sustainable development, self-sufficiency, modernization of the knowledge base, improving productivity, and improving the livelihoods of rural people.