Our contribution is dedicated to geographic information contained in unstructured textual documents. The main focus of this article is to propose a general indexing strategy that is dedicated to spatial information, but which could be applied to temporal and thematic information as well. More specifically, we have developed a process flow that indexes the spatial information contained in textual documents. This process flow interprets spatial information and computes corresponding accurate footprints. Our goal is to normalize such heterogeneous grained and scaled spatial information (points, polylines, polygons). This normalization is carried out at the index level by grouping spatial information together within spatial areas and by using statistics to compute frequencies for such areas and weights for the retrieved documents.