Spatial data reallocation based on multidimensional range queries. A contribution to data management for the earth sciences

Earth scientists, by definition, work in an interdisciplinary environment and therefore collect and disseminate data using distinct methods, depending on whether the associated information arises during field measurements, arrives via remote sensing, or represents simulation results. When calculating the global radiation over one of the oceans, for instance, it is essential that cloud data from at least three different sources can be accessed based on one and the same geographic grid. Differently gridded source data must therefore be reorganized through interpolation for example. This can be done in different ways and we investigate a method whose practicality depends on fast spatial range queries, but in turn provides a flexibility that makes it particularly easy to accommodate differently organized data sets-a valuable feature when unanticipated grid organizations show up