Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses
Language: English
Published by CRC Press Okt 2009, 2009
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Add to basketItem description from seller
Neuware - When compared to classical sciences such as math, with roots in prehistory, and physics, with roots in antiquity, geographical information science (GISci) is the new kid on the block. Its theoretical foundations are therefore still developing and data quality and uncertainty modeling for spatial data and spatial analysis is an important branch of that theory. Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses outlines the foundational principles and supplies a firm grasp of the disciplines' theoretical underpinnings. Comprehensive, Systematic Review of Methods for Handling UncertaintiesThe book summarizes the principles of modeling uncertainty of spatial data and spatial analysis, and then introduces the developed methods for handling uncertainties in spatial data and modeling uncertainties in spatial models. Building on this foundation, the book goes on to explore modeling uncertainties in spatial analyses and describe methods for presentation of data as quality information. Progressing from basic to advanced topics, the organization of the contents reflects the four major theoretical breakthroughs in uncertainty modeling: advances in spatial object representation, uncertainty modeling for static spatial data to dynamic spatial analyses, uncertainty modeling for spatial data to spatial models, and error description of spatial data to spatial data quality control.Determine Fitness-of-Use for Your ApplicationsModeling uncertainties is essential for the development of geographic information science. Uncertainties always exist in GIS and are then propagated in the results of any spatial analysis. The book delineates how GIS can be a better tool for decision-making and demonstrates how the methods covered can be used to control the data quality of GIS products.…
Seller Inventory # 9781420059274
- Title
- Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses
- Author
- Wenzhong Shi
- Publisher
- CRC Press Okt 2009
- Publication year
- 2009
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 1420059270
- ISBN 13
- 9781420059274
- Item weight
- 764 grams
- Dimensions
- 238x161x32 mm
When compared to classical sciences such as math, with roots in prehistory, and physics, with roots in antiquity, geographical information science (GISci) is the new kid on the block. Its theoretical foundations are therefore still developing and data quality and uncertainty modeling for spatial data and spatial analysis is an important branch of that theory. Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses outlines the foundational principles and supplies a firm grasp of the disciplines’ theoretical underpinnings.
Comprehensive, Systematic Review of Methods for Handling Uncertainties
The book summarizes the principles of modeling uncertainty of spatial data and spatial analysis, and then introduces the developed methods for handling uncertainties in spatial data and modeling uncertainties in spatial models. Building on this foundation, the book goes on to explore modeling uncertainties in spatial analyses and describe methods for presentation of data as quality information. Progressing from basic to advanced topics, the organization of the contents reflects the four major theoretical breakthroughs in uncertainty modeling: advances in spatial object representation, uncertainty modeling for static spatial data to dynamic spatial analyses, uncertainty modeling for spatial data to spatial models, and error description of spatial data to spatial data quality control.
Determine Fitness-of-Use for Your Applications
Modeling uncertainties is essential for the development of geographic information science. Uncertainties always exist in GIS and are then propagated in the results of any spatial analysis. The book delineates how GIS can be a better tool for decision-making and demonstrates how the methods covered can be used to control the data quality of GIS products.
"Synopsis" may belong to another edition of this title.
About the Author
Wenzhong Shi
"About the title" may belong to another edition of this title.
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