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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.
List of contents
Chapter 1. Introduction.- Chapter 2. Spatial Interpolation.- Chapter 3. Spatial Semantic Kriging.- Chapter 4. Fuzzy Bayesian Semantic Kriging.- Chapter 5. Spatio-temporal Reverse Semantic Kriging.- Chapter 6. Summary and Future Research.
About the author
Dr. Shrutilipi Bhattacharjee is a Postdoctoral Fellow (PDF) in the Department of Electrical and Computer Engineering, Technical University of Munich, Germany. She completed her B.Tech. from West Bengal University of Technology, India; M.Tech. from National Institute of Technology, Durgapur, India, and Ph.D. from Indian Institute of Technology, Kharagpur, India. Her research interests include geoscience, remote sensing, environmental modelling, semantic analysis, spatial data mining, and spatial statistics. She has published numerous papers in international journals and at conferences. She is also a reviewer for a number of journals and conferences. She is a young professional member of IEEE (including GRSS and WIE) and ACM.
Prof. Soumya K. Ghosh is a Professor in the Department of Computer Science and Engineering, Indian Institute of Technology (IIT) Kharagpur, India. He has been awarded the National Geospatial Chair Professorship by the Department of Science and Technology, Government of India in 2017. He completed his M.Tech. and Ph.D. in Computer Science and Engineering at IIT Kharagpur. Prior to IIT Kharagpur, he worked for Indian Space Research Organization, Government of India, as Scientist in the area of Satellite Remote Sensing and GIS. He has more than 15 years of teaching experience and supervised more than 10 Ph.D. theses. His research interests include spatial informatics, spatial data science, geographic information systems, and cloud computing. He has published numerous papers in international journals and conference proceedings. He is a member of IEEE and ACM.
Dr. Jia Chen is a Professor at the Technical University of Munich and an Associate in the Department of Earth and Planetary Sciences at Harvard University. She completed her Master’s degree in Engineering at University Karlsruhe and Ph.D. at the Technical University of Munich, after which she also worked as Postdoctoral Fellow in Environmental Science & Engineering at Harvard University. She has published over 100 papers in international journals and conferences and has also filed 12 patents. She is also an active reviewer for several international journals and a member of IEEE Photonics Society, EGU, VDE and VDI.
Summary
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.
