Zhang / Atkinson / Goodchild Scale in Spatial Information and Analysis

Erscheinungsjahr 2012
ISBN: 978-1-4398-2938-7
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 367 Seiten

Essential to the comprehension of spatial phenomena and application of spatial information, scale dependencies, along with their representations and analyses, must be properly and usefully incorporated for better-informed spatial problem-solving. This book provides a coherent synthesis of past and current research on scale issues in spatial information and analysis. Within a clear geostatistical framework, it describes those fundamental concepts, theories, and techniques essential for scale-dependent and sensitive handling of multi-source spatial data. It includes examples and illustrations for mathematical detail and outlines potential future developments in the field.

Zielgruppe

Graduates, researchers, and geospatial professionals who work in remote sensing, GIS, spatial analysis, environmental modeling; engineers and specialists using spatial data in civil engineering, forestry, earth sciences, biology, medicine, history, and other fields; and government employees using spatial data for decision making.

Autoren/Hrsg.

Zhang, Jingxiong

Atkinson, Peter

Goodchild, Michael

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Geowissenschaften Geographie | Raumplanung Humangeographie

Inhaltsverzeichnis

Introduction
Scale issues
Models and methods
The book chapters
Scale in representations and measurements
Data modeling incorporating scale
Multi-scale data acquisition
Scale models
Geostatistical models
Convolution and de-convolution
Extensions
Spatial prediction and scaling
Fundamentals of kriging
Geostatistical scaling
Indicator approaches
Multi-scale data integration
Multivariate geostatistics
Handling multi-scale data
Scale mismatch and its effects
Scale and uncertainty characterization
Accuracy metrics and spatial assessment
Validation across scales
Scale-explicit stochastic simulation
Scale in terrain analysis
Digital terrain analysis
Scale sensitivity in derivatives
Terrain data fusion
Scale effects in uncertainty modeling
Scale in categorical mapping
Spatial and categorical scales
Scalable models for area classes
Area-class map conflation
Discriminant models of uncertainty
Scale in landscape dynamics
Scale effects in change detection
Scaling of predicted changes
Scale in objects
Methods for scaling of discrete objects
Merging objects
Uncertainty analysis in scaling and conflation
Multi-scale data assimilation
Kalman filters
Multi-scale methods
Prospects