ISBN: 9781420059274 - principles of modeling uncertainties in spatial data and spatial analyses (5 Ergebnisse)

Zustand: Very Good. Very Good; Hardcover; Light wear to the covers; Unblemished textblock edges; The endpapers and all text pages are clean and unmarked; The binding is excellent with a straight spine; This book will be stored and delivered in a sturdy cardboard box with foam padding; Medium Format (8.5" - 9.75" tall); Dark gray covers with title in white lettering; 2009, CRC Press; 432 pages; "Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses," by Wenzhong Shi.…

Zustand: Good. Gift message on inside page Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.…

Zustand: As New. Unread book in perfect condition.

Gebunden. Zustand: New. Wenzhong ShiWhen 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 s.

Buch. Zustand: Neu. 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.…