Hydroinformatics: Data Integrative Approaches in Computation, Analysis, and ModelingModern 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 |
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Page 1
... requires identifying key linkages and feedback between them. A significant step in this direction has been a migration from a traditional laboratory approach to a natural laboratory approach. The former consists of studying processes in ...
... requires identifying key linkages and feedback between them. A significant step in this direction has been a migration from a traditional laboratory approach to a natural laboratory approach. The former consists of studying processes in ...
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... requires data integration processing and the data transformations necessary to enable this integration (Figure 3.2). However, every step in this processing chain of transformation and integration has great potential for introducing ...
... requires data integration processing and the data transformations necessary to enable this integration (Figure 3.2). However, every step in this processing chain of transformation and integration has great potential for introducing ...
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... require attention and may be benefited from a method that helps to: 1. Ensure the self-consistency of source data. 2. Ensure the self-consistency of composite data (i.e., integrated) derived from multiple source data. 3. Reproduce ...
... require attention and may be benefited from a method that helps to: 1. Ensure the self-consistency of source data. 2. Ensure the self-consistency of composite data (i.e., integrated) derived from multiple source data. 3. Reproduce ...
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... require curation and therefore they are allowed to be cast into an L0 object. The challenge is to maintain the heritage of the object in an effective manner. 3.1.2.3 Quality Control Processing Quality Control (QC) is generally an ...
... require curation and therefore they are allowed to be cast into an L0 object. The challenge is to maintain the heritage of the object in an effective manner. 3.1.2.3 Quality Control Processing Quality Control (QC) is generally an ...
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... requires confidentiality and the ability to remove an ADO if not accepted for peer-reviewed publication. A looser deletion policy would allow deletion of data if it had never been copied. The persistent name (i.e., accession number in ...
... requires confidentiality and the ability to remove an ADO if not accepted for peer-reviewed publication. A looser deletion policy would allow deletion of data if it had never been copied. The persistent name (i.e., accession number in ...
Contents
7 | |
Managing and Accessing Large Datasets | 101 |
Data Communication | 161 |
Data Processing and Analysis | 257 |
Soft Computing | 379 |
Appendices | 477 |
Index | 529 |
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Common terms and phrases
algorithm analysis application approach associated attributes bands boundary called Center chapter clusters complex component contains coordinate create data model data structures database datasets defined described distance distributed elements Engineering Equation error example extraction feature field Figure format function fuzzy geographic given grid HDF5 hydrologic illustrated implementation important input integration interface logical mean measurements metadata methods Modelshed multiple Name node objects operations optimization organized original output parameters perform prediction presented problem projection properties query raster records References relationship represent requires Research rules schema segment selection sensor shown simple sources spatial specific standard step storage stored structure transformation tree University values variables vector visualization xs:element