Quantifying Spatial Uncertainty in Natural Resources: Theory and Applications for GIS and Remote Sensing

, by Congalton; Russell G.

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ISBN: 9781575041315 | 1575041316
Cover: Hardcover
Copyright: 3/1/2000

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Summary

Supplemental Materials

This book will be useful both to those new to spatial uncertainty assessment and to experienced practitioners.

Introduction: The Past, Present, and Future of Uncertainty Analysis

H. Todd Mowrer

Russell G. Congalton

Section I. Accuracy Assessment Issues

Communicating the Results of Accuracy Assessment: Metadata, Digital Libraries, and Assessing Fitness for Use

(14)

Michael F. Goodchild

From Data Accuracy to Data Quality: Using Spatial Statistics to Predict the Implications of Spatial Error in Point Data

(20)

Adam Lewis

Michael F. Hutchinson

Generalized Linear Mixed Models for Analyzing Error in a Satellite-Based Vegetation Map of Utah

(8)

Gretchen G. Moisen

D. Richard Cutler

Thomas C. Edwards

Increasing Spatial Precision and Accuracy for Monitoring Peatlands in Switzerland by Remote Sensing Techniques

(8)

Michael Kohl

Hans Jorg Schnellbacher

Andreas Grunig

The Effect of Uncertain Locations on Disease Cluster Statistics

(12)

Geoffrey M. Jacquez

Lance A. Waller

Double Sampling for Area Estimation and Map Accuracy Assessment

(14)

Francisco Javier Gallego

Accuracy Assessments and Areal Estimates Using Two-Phase Stratified Random Sampling, Cluster Plots, and the Multivariate Composite Estimator

(24)

Raymond L. Czaplewski

Section II. Modeling Spatial and Temporal Uncertainty

Acquisition of Spatial Data by Forest Management Agencies

103

(8)

Michael J.C. Weir

Choosing Between Abrupt and Gradual Spatial Variation?

111

(8)

Gerard B.M. Heuvelink

Johan A. Huisman

Modeling the Spatial Distribution of Ten Tree Species in Pennsylvania

119

(18)

Rachel Riemann Hershey

Realistic Spatial Models: The Accurate Mapping of Environmental Factors Based on Synecological Coordinates

137

(14)

Margaret R. Holdaway

Gary J. Brand

Discrete Polygons or a Continuous Surface: Which is the Appropriate Way to Model Forests Cartographically?

151

(10)

Kim Lowell

Statistical Models of Landscape Pattern and the Effects of Coarse Spatial Resolution on Estimation of Area with Satellite Imagery

161

(10)

Christine A. Hlavka

The Simultaneous Nature of Tree Growth Models

171

(12)

Hubert Hasenauer

Robert A. Monserud

Timothy G. Gregoire

Incorporating Soil Variability into a Spatially Distributed Model of Percolate Accounting

183

(20)

Andrew S. Rogowski

Analyzing Spatiotemporal Dynamics of Plant Populations and Vegetation

203

(10)

Paul Braun

Heiko Balzter

Wolfgang Kohler

Space-Time Statistical Modeling of Environmental Data

213

(24)

Christopher K. Wikle

Noel Cressie

Index

237

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Quantifying Spatial Uncertainty in Natural Resources: Theory and Applications for GIS and Remote Sensing

Summary

Table of Contents

Supplemental Materials