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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.
| Autorius: | Shrutilipi Bhattacharjee, Jia Chen, Soumya Kanti Ghosh, |
| Serija: | Studies in Computational Intelligence |
| Leidėjas: | Springer Nature Singapore |
| Išleidimo metai: | 2019 |
| Knygos puslapių skaičius: | 156 |
| ISBN-10: | 9811386633 |
| ISBN-13: | 9789811386633 |
| Formatas: | 241 x 160 x 15 mm. Knyga kietu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Semantic Kriging for Spatio-temporal Prediction“
