La valeur économique des paysages des villes périurbanisées

In this research, we propose a method for describing rural landscapes in peri urban areas and evaluating their impact on house and land prices. This method matches quantitative geography and econometric methods used for hedonic analysis. A geographical model is used for producing variables describing the landscape an observer can look at when located in a specific house or a land parcel. This model takes account of these parts of the landscape that are hidden by houses, buildings, hills, forests,. . . The variables produced by the model describe the size of the area that can be seen and its repartition across various types of land use (agriculture, forest, buildings, roads, water,. . . ). They are used as explanatory factors for the price paid for buying the house or land parcel, using hedonic regression. This method has been simultaneously used in six areas: the periurban areas of the cities of Dijon, Besançon, Lyon, Marseille and Brest and the whole Nord-Pas de Calais region. We are then able to compare results obtained using the same methodology for various areas, with various types of landscapes. Moreover, for Dijon, Besançon and the Nord-Pas de Calais regions, we can compare variables produced using different sources of information. For Dijon and Besançon, they differ with respect to the thinness and the quality of the satellite images used for analysing landcapes, the best one being much more expansive. For the Nord-Pas de Calais, we compared two types of geographical information systems. Our results confirm that the quality of the landscape that can be seen when located at a house or in a land parcel significantly influences its price. A landscape, with notably green areas, has a value that is capitalized into house and land prices. However, the measure of this value is highly variable across regions and is highly sensitive to the quality of the data used by the geographical model. Therefore, at this stage of the research work, our results cannot be used for operational purposes.