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The Earth’s land surface is a key component of its climate system. Terrestrial plants, animals and human beings rely on the land surface for sustenance and existence; as such, its prevailing conditions and properties are essential to terrestrial life.
Land use/cover changes are pervasive with no clear understanding of their spatial extends, drivers and impacts to society. Land-use changes have become a key component in the current strategies for managing and monitoring the natural resources and environment changes.
In this paper, we present an optimized Machine Learning (ML) algorithm for predicting land suitability for crop (sorghum) production, given soil properties information.
Governments have power to compulsorily acquire land or other interest in land for a public purpose subject to prompt payment of the compensation to the affected persons.
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