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Satellite Agricultural Productivity Index (SAPI-X)

The SAPI-X experiment focused on creating an advanced Satellite Agricultural Productivity Index (SAPI) to assess the productivity of farmlands. This project aimed to increase agricultural production by 70% to meet the demands of a growing global population. By integrating satellite, soil, and climate data with AI methods, SAPI-X sought to offer a scalable and accurate solution for assessing farmland at a high resolution. This would enable optimized decisions regarding fertilizer and pesticide application, crop choice, and other agricultural practices, incorporating factors like soil potential, climate, and farmer efficiency. The project's approach involved machine learning algorithms applied to satellite images, soil maps, and climate records, with a final goal of developing a comprehensive productivity index that factors in soil, climate, equipment, and farmer efficiency.

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