The price for a single-family house depends both on the characteristics of the building and on its location. We propose a novel semiparametric method to extract location values from house prices. After splitting house prices into building and land components, location values are estimated with adaptive weight smoothing. The adaptive estimator requires neither strong smoothness assumptions nor local symmetry. We apply the method to house transactions from Berlin, Germany. The estimated surface of location values is highly correlated with expert-based land values and location ratings. The semiparametric method can therefore be used for applications where no other location value information exists or where this information is not reliable.