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You're building a model to predict housing prices using a dataset that includes various features about real estate properties. One of the available features is the latitude and longitude of each property. Domain experts have confirmed that a property's geographic location strongly impacts its value, so you'd like to engineer a feature that effectively captures this spatial relationship in your fully connected neural network. What is the best way to incorporate the location feature to improve model performance?