We applied a spatial approach to detect regions of the genome of the common frog (Rana temporaria) which are possibly selected along an altitude gradient. The identification of selected regions in the genome is important as it gives the possibility to understand which genes are driven by natural selection. In the field of population genetics, several statistical methods using molecular data were developed to reveal genomic regions under selection. Here, we tackled the issue from an environmental point of view by using a spatial analysis method (SAM) recently developed. The method is based on the spatial coincidence concept and has recourse to GIS, environmental data and molecular data to simultaneously process many univariate logistic regression models. This research showed that there is a strong correspondence between spatial analysis results and those obtained with a standard population genomics approach.