Modern hydrology is more interdisciplinary than ever. Staggering amounts and varieties of information pour in from GIS and remote sensing systems every day, and this information must be collected, interpreted, and shared efficiently. Hydroinformatics: Data Integrative Approaches in Computation, Analysis, and Modeling introduces the tools, approache
Data Integrative Studies in Hydroinformatics. DATA DRIVEN INVESTIGATION IN HYDROLOGY. Unified Modeling Language. Digital Library Technology. Hydrologic Metadata. Hydrologic Data Models. Modelshed Data Model. MANAGING AND ACCESSING LARGE DATASETS. Data Models for Storage and Retrieval. Data Formats. HDF5. DATA COMMUNICATION. Web Services. XML. Grid Computing. Integrated Data Management. DATA PROCESSING AND ANALYSIS. Introduction to Data Processing. Understanding Data Sources. Data Representation. Spatial Registration. Georeferencing. Data Integration. Feature Extraction. Feature Selection and Analysis. SOFT COMPUTING. Statistical Data Mining. Neural Networks. Genetic Algorithms. Fuzzy Logic. APPENDICES. INDEX.