Modeling and statistical analysis of geospatial and spatio-temporal data
The Geostatistics Community focuses on modeling and statistical analysis of spatio-temporal data, and on the quantitative expression and visualization of data accuracy, control of data quality, and error propagation.
We develop software for the modelling and statistical analysis of geospatial and spatio-temporal data. We do this by connecting the 52°North Sensor Web and Geoprocessing communities with analysis and modeling communities, including the community involved in the open source statistical computing environment R, and e.g. atmospheric dispersion modeling communities. One of our immediate goals is to interface the comprehensive statistical functionality of the popular open source R environment to the geospatial user world through open standards, such as those endorsed by the OGC.
Vision: to leverage open research via open source geostatistical tools which in turn help us understand our environment with in order to manage it in a sustainable way.
We focus on
- the integration of in situ sensing data from fixed or mobile sensors with earth observation (remote sensing) data,
- the integration of stochastic, statistics-based modelling with physics-based modelling (e.g. transport or diffusion modelling),
- the analysis of value of information and information deficit, to find out where additional data collection (or modelling) is most effective and needed,
- exploration and application of GRID, cloud and GPGPU computer infrastructures for high-performance and high-availability geospatial computing.
- interactive variogram diagnostics.
- PostgreSQL extension for temporal dimension.
Spatio-temporal Modeling @ ifgi
Institute for Geoinformatics (ifgi) of the University of Muenster is a strong partner of the Geostatistics community. The researchers of this group contribute their public work to the 52°North open source initiative to ensure a wide distribution of their work, and to benefit from the partner network and dissemination activities.
The spatio-temporal modeling lab at the