Geographical Machine Learning for Temperature Forecasting

In this short communication we present the results taken from the real-time weather dataset of Tabouk City, Saudi Arabia. In the results we have applied machine learning techniques to predict the future air temperature of the region. This dataset's results have informed in the creation of determinants driving agricultural and urban expansion contribute to the analysis of the main causes of land use change. This kind of datasets can assist policymakers to understand the importance of a wide range of depleting resources (e.g., groundwater) on the associated agricultural and urban land use change, particularly in arid regions of Saudi Arabian Peninsula.