Author:
Publisher:
ISBN:
Category : Cartography
Languages : en
Pages : 506

View

Book Description

Author: Joseph A. Salem
Publisher: Association of Research Libr
ISBN:
Category : Geographic information systems
Languages : en
Pages : 148

View

Book Description

Author: S.C. Guptill
Publisher: Elsevier
ISBN: 1483287947
Category : Technology & Engineering
Languages : en
Pages : 219

View

Book Description
Elements of Spatial Data Quality outlines the need and suggests potential categories for the content of a comprehensive statement of data quality that must be imbedded in the metadata that accompanies the transfer of a digital spatial data file or is available in a separate metadata catalog. Members of the International Cartographic Association's Commission on Spatial Data Quality have identified seven elements of data quality: positional accuracy, attribute accuracy, completeness, logical consistency, lineage, semantic accuracy and temporal information. In the book the authors describe: components of each data quality element, possible metrics that can be used to measure the quality of each criteria, possible testing and rating schemes, and how these parameters might differ from a producer or user point of view. Finally no volume of this nature would be complete without a chapter devoted to necessary future research in this subject area. The chapter points out areas in need of further investigation and speculates about the use and transfer of digital spatial data in tomorrow's electronic world and at developments in presenting specified data quality information in a visualization. This book will be of interest to all of those individuals involved in geographical information systems and spatial data handling.

Author: Lex Comber
Publisher: SAGE
ISBN: 1526485435
Category : Science
Languages : en
Pages : 460

View

Book Description
We are in an age of big data where all of our everyday interactions and transactions generate data. Much of this data is spatial – it is collected some-where – and identifying analytical insight from trends and patterns in these increasing rich digital footprints presents a number of challenges. Whilst other books describe different flavours of Data Analytics in R and other programming languages, there are none that consider Spatial Data (i.e. the location attached to data), or that consider issues of inference, linking Big Data, Geography, GIS, Mapping and Spatial Analytics. This is a ‘learning by doing’ textbook, building on the previous book by the same authors, An Introduction to R for Spatial Analysis and Mapping. It details the theoretical issues in analyses of Big Spatial Data and developing practical skills in the reader for addressing these with confidence.

Author: R. S. Sonenshein
Publisher:
ISBN:
Category : Broward County (Fla.)
Languages : en
Pages : 68

View

Book Description

Author: Brian Dean Hoolihan
Publisher:
ISBN:
Category : Geographic information systems
Languages : en
Pages : 222

View

Book Description

Author: Earl F. Burkholder
Publisher: CRC Press
ISBN: 1498722172
Category : Computers
Languages : en
Pages : 492

View

Book Description
Traditional methods for handling spatial data are encumbered by the assumption of separate origins for horizontal and vertical measurements, but modern measurement systems operate in a 3-D spatial environment. The 3-D Global Spatial Data Model: Principles and Applications, Second Edition maintains a new model for handling digital spatial data, the global spatial data model or GSDM. The GSDM preserves the integrity of three-dimensional spatial data while also providing additional benefits such as simpler equations, worldwide standardization, and the ability to track spatial data accuracy with greater specificity and convenience. This second edition expands to new topics that satisfy a growing need in the GIS, professional surveyor, machine control, and Big Data communities while continuing to embrace the earth center fixed coordinate system as the fundamental point of origin of one, two, and three-dimensional data sets. Ideal for both beginner and advanced levels, this book also provides guidance and insight on how to link to the data collected and stored in legacy systems.

Author: Paul A. Longley
Publisher: John Wiley & Sons
ISBN: 0470236159
Category : Technology & Engineering
Languages : en
Pages : 413

View

Book Description
Spatial Analysis: Modelling in a GIS Environment Edited by PaulLongley and Michael Batty Digital data and information are usedincreasingly by academics, professionals, local authorities, andgovernment departments. Powerful new technologies, such asgeographic information systems (GIS), are being developed toanalyse such data, and GIS technologies are rapidly becoming partof the emergent world digital infrastructure. This book shows howcomputer methods of analysis and modelling, built around GIS, canbe used to identify ways in which our cities and regions might bebetter planned and understood. The contributors to this book areall actively involved in research using geographic informationsystems. This book will be valuable reading for: * Geographers, researchers, and regional analysts * Population theorists and regional economists with interests inlarge-scale demographic and employment data * Planners and policy-makers who wish to use GIS to improve theirdecision making * Business analysts who wish to explore markets using the mostrecent advances in digital spatial data technology * All those interested in geodemographics Paul Longley is Professor of Geography at the Department ofGeography, University of Bristol, United Kingdom. Michael Batty isProfessor of Spatial Analysis and Planning at the UniversityCollege London. United Kingdom.

Author:
Publisher:
ISBN:
Category : Cartography
Languages : en
Pages : 510

View

Book Description

Author: Peggy Agouris
Publisher: Taylor & Francis
ISBN: 0203088514
Category : Technology & Engineering
Languages : en
Pages : 198

View

Book Description
With the turn of the century our ability to collect and store geospatial information has increased considerably. This has resulted in ever-increasing amounts of heterogeneous geospatial data, an issue that poses new challenges and opportunities. As these rich sources of data are made available, users rely, now more than ever, on the geospatial data