In geospatial applications with heterogeneous classification schemes that describe related domains, an ontology-driven approach to data sharing and interoperability relies on the alignment of concepts across different ontologies. To enable scalability both in the size and the number of the ontologies involved, the alignment method should be automatic. In this paper, we propose two fully automatic alignment methods that use the structure of the ontology graphs for contextual information, thus providing the matching process with more semantics. We have tested our methods on a set of geospatial ontologies pertaining to the domain of wetlands and on four sets that belong to an ontology repository that is becoming the standard for testing ontology alignment techniques. We have compared the effectiveness and efficiency of the proposed methods against two previous approaches. The effectiveness results that we have obtained with at least one of the new methods are as good or better than the results obtained with the previously proposed methods.