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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, approaches, and system considerations
necessary to take full advantage of the abundant hydrological data
available today. Linking hydrological science with computer
engineering, networking, and database science, this book lays a
pedagogical foundation in the concepts underlying developments in
hydroinformatics. It begins with an introduction to data
representation through Unified Modeling Language (UML), followed by
digital libraries, metadata, the basics of data models, and
Modelshed, a new hydrological data model. Building on this
platform, the book discusses integrating and managing diverse data
in large datasets, data communication issues such as XML and Grid
computing, the basic principles of data processing and analysis
including feature extraction and spatial registration, and modern
methods of soft computing such as neural networks and genetic
algorithms. Today, hydrological data are increasingly rich,
complex, and multidimensional. Providing a thorough compendium of
techniques and methodologies, Hydroinformatics: Data Integrative
Approaches in Computation, Analysis, and Modeling is the first
reference to supply the tools necessary to confront these
challenges successfully.
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, approaches, and system considerations
necessary to take full advantage of the abundant hydrological data
available today. Linking hydrological science with computer
engineering, networking, and database science, this book lays a
pedagogical foundation in the concepts underlying developments in
hydroinformatics. It begins with an introduction to data
representation through Unified Modeling Language (UML), followed by
digital libraries, metadata, the basics of data models, and
Modelshed, a new hydrological data model. Building on this
platform, the book discusses integrating and managing diverse data
in large datasets, data communication issues such as XML and Grid
computing, the basic principles of data processing and analysis
including feature extraction and spatial registration, and modern
methods of soft computing such as neural networks and genetic
algorithms. Today, hydrological data are increasingly rich,
complex, and multidimensional. Providing a thorough compendium of
techniques and methodologies, Hydroinformatics: Data Integrative
Approaches in Computation, Analysis, and Modeling is the first
reference to supply the tools necessary to confront these
challenges successfully.
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