Keywords : Geostatistics, Remote Sensing, Data Fusion



- Word cloud generated from titles of publications and research projects -


  • Spatial Analysis using GeostatisticsGeostatistics is a collection of statistical tools for analyzing spatio-temporal data and "Spatial Thinking". It has been widely used for spatial prediction or interpolation of sparsely sampled data. However, geostatisics can also be used for data integration, uncertainty modeling, and risk analysis as well as spatial prediction. Please keep in mind geostatistics is NOT merely an advanced interpolation algorithm! We are trying to develop advanced geostatsitical algorithms and to apply them to environmental problems for supporting decision-makings
    • Integration of sparsely sampled hard data with auxiliary soft data for environmental thematic mapping
    • Uncertainty modeling for supporting decision-makings
    • Value of information and risk analyses using stochastic simulation
    • Across-space-time-scale integration with a geostatistical framework
    • Spatial analysis of disease data for medical geoinformatics
    • Applications : Read more

  • Remote Sensing of Environment Remote sensing is the science of obtaining information through the analysis of data acquired from various man-made satellites and airplanes without making physical contact with the objects of interest. Our research focuses on environmental monitoring and thematic mapping with advanced methodological developments
    • Feature extraction and classification using statistical pattern recognition and machine learning algorithms
    • Environmental thematic mapping and change detection
    • Applications : Read more

  • Multi-source/sensor Geospatial Data Fusion New advances in various data acquistion techniques have made it possible to rapidly collect large volumes of data sets. To make optimized decisions, better use must be made of all available information acquired from different sources or sensors. Data fusion or integration aims that 1 + 1 is more than 2! Multi-soruce data analysis, however, cannot be handled using the single source data processing and requires a new data analysis concept. We are developing efficient data integration models for various application fields 
    • Development of data fusion models and systems (Bayesian probabilistic model, generalized linear/additive models, fuzzy logic, Dempster-Shafer theory of evidence, maximum entropy model, machine learning algorithms, etc)
    • Applications : Read more