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This paper presents the results of our initial experiments in the monolingual English task and the Bilingual Spanish → English task. We used the Terrier Information Retrieval Platform to run experiments for both tasks using the Inverse Document Frequency model with Laplace after-effect and normalization 2. Additional experiments were run with Indri, a retrieval engine that combines inference networks with language modelling. For the bilingual task we developed a component to first translate the topics from Spanish into English. No spatial analysis was carried out for any of the tasks. One of our goals is to have a baseline to compare further experiments with term translation of georeferences and spatial analysis. Another goal is to use ontologies for Integrated Geographic Information Systems adapted to the IR task. Our initial results show that the geographic information as provided does not improve significantly retrieval performance. We included the geographical terms appearing in all the fields. Duplication of terms might have decreased gain of information and affected the ranking.