Abstract
The international risk that stands out since the depletion of land and loss of carbon posed as the most challenging issue of all, is food safety, climate health, and the safety of metropolitan regions. We have developed a civil infrastructure, architecture, and AI drone-combined approach to restore degraded land efficiently and effectively. Using smart drones, we enhance biochar usage, smart irrigation, and soil building, leading to soil health improvement, hydric soil formation, and increased carbon collection in the soil. Besides ecological restoration, this study further addresses architectural sustainability by designing green infrastructure on vertically combined structures incorporated in the city and transforming city and agricultural lands to climb. In landscape and environmental science, self-sustaining ecosystems that modify climates are called climate-adaptive ecosystems. We use LiDAR, spectra imaging, and AI inspection to have real-time data on the restoration success which guarantees accuracy and the possibility for automation. With these measures, we achieve remarkable outcomes that stand at 20% drop in soil erosion, 120% rise in carbon collection, and a high percentage of 98% improvement in the preservation of moisture in the soil. It is a sustainable farming strategy model powered by AIenhancing engineering and construction architectural degradation that is easier, faster, and more effective than current standards. In the end, these measures unite technology with nature to create a world where rural regions and infrastructural zones operate in sync and can be replicated easily without extra expenditure. Ideally, it is a sustainable strategy for managing land resources. Forthcoming research will focus on AI-based optimization for land rehabilitation, communal implementation methods, and policies capable of fostering mass adoption.

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