Comparing regression and neural net based approaches to modelling of scenic beauty

Many studies have used multiple linear regression to develop a model linking landscape variables to perceived scenic beauty. This paper uses a single data set to generate both a regression based model and a model using artificial neural nets. The results of the two models are compared in terms of their predictive capability, their residuals and maps of scenic beauty produced by extending each model across the study area. The results show considerable similarities in the preferred predictor variables.