PRINCIPLES OF MODELING UNCERTAINTIES IN SPATIAL DATA AND SPATIAL ANALYSES

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Principles Of Modeling Uncertainties In Spatial Data And Spatial Analyses

Author : Wenzhong Shi
ISBN : 1420059289
Genre : Technology & Engineering
File Size : 71.23 MB
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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.
Category: Technology & Engineering

Uncertainty Modelling And Quality Control For Spatial Data

Author : Shi Wenzhong
ISBN : 9781498733342
Genre : Mathematics
File Size : 57.6 MB
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Offers New Insight on Uncertainty Modelling Focused on major research relative to spatial information, Uncertainty Modelling and Quality Control for Spatial Data introduces methods for managing uncertainties—such as data of questionable quality—in geographic information science (GIS) applications. By using original research, current advancement, and emerging developments in the field, the authors compile various aspects of spatial data quality control. From multidimensional and multi-scale data integration to uncertainties in spatial data mining, this book launches into areas that are rarely addressed. Topics covered include: New developments of uncertainty modelling, quality control of spatial data, and related research issues in spatial analysis Spatial statistical solutions in spatial data quality Eliminating systematic error in the analytical results of GIS applications A data quality perspective for GIS function workflow design Data quality in multi-dimensional integration Research challenges on data quality in the integration and analysis of data from multiple sources A new approach for imprecision management in the qualitative data warehouse A multi-dimensional quality assessment of photogrammetric and LiDAR datasets based on a vector approach An analysis on the uncertainty of multi-scale representation for street-block settlement Uncertainty Modelling and Quality Control for Spatial Data serves university students, researchers and professionals in GIS, and investigates the uncertainty modelling and quality control in multi-dimensional data integration, multi-scale data representation, national or regional spatial data products, and new spatial data mining methods.
Category: Mathematics

Comprehensive Geographic Information Systems

Author :
ISBN : 9780128047934
Genre : Science
File Size : 21.37 MB
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Geographical Information Systems is a computer system used to capture, store, analyze and display information related to positions on the Earth’s surface. It has the ability to show multiple types of information on multiple geographical locations in a single map, enabling users to assess patterns and relationships between different information points, a crucial component for multiple aspects of modern life and industry. This 3-volumes reference provides an up-to date account of this growing discipline through in-depth reviews authored by leading experts in the field. Covers a rapidly expanding discipline, providing readers with a detailed overview of all aspects of geographic information systems, principles and applications Emphasizes the practical, socioeconomic applications of GIS Provides readers with a reliable, one-stop comprehensive guide, saving them time in searching for the information they need from different sources
Category: Science

Spatial Uncertainty In Ecology

Author : Carolyn T. Hunsaker
ISBN : 9781461302094
Genre : Science
File Size : 77.87 MB
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This is one of the first books to take an ecological perspective on uncertainty in spatial data. It applies principles and techniques from geography and other disciplines to ecological research, and thus delivers the tools of cartography, cognition, spatial statistics, remote sensing and computer sciences by way of spatial data. After describing the uses of such data in ecological research, the authors discuss how to account for the effects of uncertainty in various methods of analysis.
Category: Science

Spatial Analysis

Author : Tonny J. Oyana
ISBN : 9781498707640
Genre : Mathematics
File Size : 38.48 MB
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An introductory text for the next generation of geospatial analysts and data scientists, Spatial Analysis: Statistics, Visualization, and Computational Methods focuses on the fundamentals of spatial analysis using traditional, contemporary, and computational methods. Outlining both non-spatial and spatial statistical concepts, the authors present practical applications of geospatial data tools, techniques, and strategies in geographic studies. They offer a problem-based learning (PBL) approach to spatial analysis—containing hands-on problem-sets that can be worked out in MS Excel or ArcGIS—as well as detailed illustrations and numerous case studies. The book enables readers to: Identify types and characterize non-spatial and spatial data Demonstrate their competence to explore, visualize, summarize, analyze, optimize, and clearly present statistical data and results Construct testable hypotheses that require inferential statistical analysis Process spatial data, extract explanatory variables, conduct statistical tests, and explain results Understand and interpret spatial data summaries and statistical tests Spatial Analysis: Statistics, Visualization, and Computational Methods incorporates traditional statistical methods, spatial statistics, visualization, and computational methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis. Topics covered include: spatial descriptive methods, hypothesis testing, spatial regression, hot spot analysis, geostatistics, spatial modeling, and data science.
Category: Mathematics

Handbook Of Applied Spatial Analysis

Author : Manfred M. Fischer
ISBN : 3642036473
Genre : Business & Economics
File Size : 34.8 MB
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The Handbook is written for academics, researchers, practitioners and advanced graduate students. It has been designed to be read by those new or starting out in the field of spatial analysis as well as by those who are already familiar with the field. The chapters have been written in such a way that readers who are new to the field will gain important overview and insight. At the same time, those readers who are already practitioners in the field will gain through the advanced and/or updated tools and new materials and state-of-the-art developments included. This volume provides an accounting of the diversity of current and emergent approaches, not available elsewhere despite the many excellent journals and te- books that exist. Most of the chapters are original, some few are reprints from the Journal of Geographical Systems, Geographical Analysis, The Review of Regional Studies and Letters of Spatial and Resource Sciences. We let our contributors - velop, from their particular perspective and insights, their own strategies for m- ping the part of terrain for which they were responsible. As the chapters were submitted, we became the first consumers of the project we had initiated. We gained from depth, breadth and distinctiveness of our contributors’ insights and, in particular, the presence of links between them.
Category: Business & Economics

Science In China

Author :
ISBN : CHI:82278455
Genre : Engineering
File Size : 64.36 MB
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Category: Engineering

Uncertainty Management In Remote Sensing Of Climate Data

Author : Board on Atmospheric Sciences and Climate
ISBN : 9780309139588
Genre : Science
File Size : 54.12 MB
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Great advances have been made in our understanding of the climate system over the past few decades, and remotely sensed data have played a key role in supporting many of these advances. Improvements in satellites and in computational and data-handling techniques have yielded high quality, readily accessible data. However, rapid increases in data volume have also led to large and complex datasets that pose significant challenges in data analysis. Uncertainty characterization is needed for every satellite mission and scientists continue to be challenged by the need to reduce the uncertainty in remotely sensed climate records and projections. The approaches currently used to quantify the uncertainty in remotely sensed data lack an overall mathematically based framework. An additional challenge is characterizing uncertainty in ways that are useful to a broad spectrum of end-users. In December 2008, the National Academies held a workshop, summarized in this volume, to survey how statisticians, climate scientists, and remote sensing experts might address the challenges of uncertainty management in remote sensing of climate data. The workshop emphasized raising and discussing issues that could be studied more intently by individual researchers or teams of researchers, and setting the stage for possible future collaborative activities.
Category: Science