Semantic Kriging for Spatio-temporal Prediction

Description

This book identifies the need for modeling auxiliary knowledge of the terrain to enhance the prediction accuracy of meteorological parameters. The spatial and spatio-temporal prediction of these parameters are important for the scientific community, and the semantic kriging (SemK) and its variants facilitate different types of prediction and forecasting, such as spatial and spatio-temporal, a-priori and a-posterior, univariate and multivariate. As such, the book also covers the process of deriving the meteorological parameters from raw satellite remote sensing imagery, and helps understanding different prediction method categories and the relation between spatial interpolation methods and other prediction methods. The book is a valuable resource for researchers working in the area of prediction of meteorological parameters, semantic analysis (ontology-based reasoning) of the terrain, and improving predictions using auxiliary knowledge of the terrain. Front Matter ....Pages i-xxv Introduction (Shrutilipi Bhattacharjee, Soumya Kanti Ghosh, Jia Chen)....Pages 1-17 Spatial Interpolation (Shrutilipi Bhattacharjee, Soumya Kanti Ghosh, Jia Chen)....Pages 19-41 Spatial Semantic Kriging (Shrutilipi Bhattacharjee, Soumya Kanti Ghosh, Jia Chen)....Pages 43-71 Fuzzy Bayesian Semantic Kriging (Shrutilipi Bhattacharjee, Soumya Kanti Ghosh, Jia Chen)....Pages 73-95 Spatio-Temporal Reverse Semantic Kriging (Shrutilipi Bhattacharjee, Soumya Kanti Ghosh, Jia Chen)....Pages 97-121 Summary and Future Research (Shrutilipi Bhattacharjee, Soumya Kanti Ghosh, Jia Chen)....Pages 123-127