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ARCGIS9用户手册Geostatistical Analyst
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ArcGIS
®
9
Using ArcGIS
®
Geostatistical Analyst
Copyright © 2001, 2003 ESRI
All Rights Reserved.
Printed in the United States of America.
The information contained in this document is the exclusive property of ESRI. This work is protected under United States copyright law and the copyright
laws of the given countries of origin and applicable international laws, treaties, and/or conventions. No part of this work may be reproduced or transmitted
in any form or by any means, electronic or mechanical, including photocopying or recording, or by any information storage or retrieval system, except as
expressly permitted in writing by ESRI. All requests should be sent to Attention: Contracts Manager, ESRI, 380 New York Street, Redlands, CA 92373-
8100, USA.
The information contained in this document is subject to change without notice.
DATA CREDITS
Carpathian Mountains data supplied by USDA Forest Service, Riverside, California, and is used here with permission.
Radioceasium data supplied by International Sakharov Environmental University, Minsk, Belarus, and is used here with permission. Copyright © 1996.
Air quality data for California supplied by California Environmental Protection Agency, Air Resource Board, and is used here with permission.
Copyright © 1997.
Radioceasium contamination in forest berries data supplied by the Institute of Radiation Safety “BELRAD”, Minsk, Belarus, and is used here with
permission. Copyright © 1996.
CONTRIBUTING WRITERS
Kevin Johnston, Jay M. Ver Hoef, Konstantin Krivoruchko, and Neil Lucas
DATA DISCLAIMER
THE DATA VENDOR(S) INCLUDED IN THIS WORK IS AN INDEPENDENT COMPANY AND, AS SUCH, ESRI MAKES NO GUARANTEES AS TO THE
QUALITY, COMPLETENESS, AND/OR ACCURACY OF THE DATA. EVERY EFFORT HAS BEEN MADE TO ENSURE THE ACCURACY OF THE DATA
INCLUDED IN THIS WORK, BUT THE INFORMATION IS DYNAMIC IN NATURE AND IS SUBJECT TO CHANGE WITHOUT NOTICE. ESRI AND
THE DATA VENDOR(S) ARE NOT INVITING RELIANCE ON THE DATA, AND ONE SHOULD ALWAYS VERIFY ACTUAL DATA AND INFORMATION.
ESRI DISCLAIMS ALL OTHER WARRANTIES OR REPRESENTATIONS, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
THE IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. ESRI AND THE DATA VENDOR(S) SHALL
ASSUME NO LIABILITY FOR INDIRECT, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES, EVEN IF ADVISED OF THE POSSIBILITY
THEREOF.
U. S. GOVERNMENT RESTRICTED/LIMITED RIGHTS
Any software, documentation, and/or data delivered hereunder is subject to the terms of the License Agreement. In no event shall the U.S. Government acquire
greater than RESTRICTED/LIMITED RIGHTS. At a minimum, use, duplication, or disclosure by the U.S. Government is subject to restrictions as set forth in
FAR §52.227-14 Alternates I, II, and III (JUN 1987); FAR §52.227-19 (JUN 1987) and/or FAR §12.211/12.212 (Commercial Technical Data/Computer
Software); and DFARS §252.227-7015 (NOV 1995) (Technical Data) and/or DFARS §227.7202 (Computer Software), as applicable. Contractor/Manufacturer
is ESRI, 380 New York Street, Redlands, CA 92373-8100, USA.
ESRI, SDE, the ESRI globe logo, ArcGIS, ArcInfo, ArcCatalog, ArcMap, 3D Analyst, and GIS by ESRI are trademarks, registered trademarks, or service marks
of ESRI in the United States, the European Community, and certain other jurisdictions.
Other companies and products mentioned herein are trademarks or registered trademarks of their respective trademark owners.
Attribution.pmd 11/25/2003, 4:46 PM1
iii
Contents
1 Welcome to ArcGIS Geostatistical Analyst 1
Exploratory spatial data analysis 2
Semivariogram modeling 3
Surface prediction and error modeling 4
Threshold mapping 5
Model validation and diagnostics 6
Surface prediction using cokriging 7
Tips on learning Geostatistical Analyst 8
2 Quick-start tutorial 11
Introduction to the tutorial 12
Exercise 1: Creating a surface using default parameters 14
Exercise 2: Exploring your data 19
Exercise 3: Mapping ozone concentration 26
Exercise 4: Comparing models 38
Exercise 5: Mapping the probability of ozone exceeding a critical threshold 39
Exercise 6: Producing the final map 42
3 The principles of geostatistical analysis 49
Understanding deterministic methods 50
Understanding geostatistical methods 53
Working through a problem 54
Basic principles behind geostatistical methods 59
Modeling a semivariogram 61
Kriging 74
A guide to the Geostatistical Analyst extension 78
4 Exploratory Spatial Data Analysis 81
What is Exploratory Spatial Data Analysis? 82
Exploratory Spatial Data Analysis 83
Exploratory Spatial Data Analysis tools 84
Examining the distribution of the data 95
TOC.p65 03/07/2001, 4:00 PM3
iv USING A RCGIS GEOSTATISTICAL A NALYST
12
Examining the distribution of your data 98
Looking for global and local outliers 99
Identifying global and local outliers 101
Looking for global trends 103
Looking for global trends 105
Examining spatial autocorrelation and directional variation 106
Examining spatial structure and directional variation 108
Understanding covariation among multiple datasets 109
Understanding spatial covariation among multiple datasets 111
5 Deterministic methods for spatial interpolation 113
How Inverse Distance Weighted interpolation works 114
Creating a map using IDW 118
How global polynomial interpolation works 120
Creating a map using global polynomial interpolation 122
How local polynomial interpolation works 123
Creating a map using local polynomial interpolation 125
How radial basis functions work 126
Creating a map using RBFs 129
6 Creating a surface with geostatistical techniques 131
What are geostatistical interpolation techniques? 132
Understanding the different kriging models 133
Understanding output surface types 135
Creating a kriging map using defaults 136
Understanding transformations and trends 137
Understanding ordinary kriging 138
Creating a map using ordinary kriging 139
Understanding simple kriging 143
Creating a map using simple kriging 144
Understanding universal kriging 150
TOC.p65 03/07/2001, 4:00 PM4
CONTENTS v
Creating a map using universal kriging 151
Understanding thresholds 153
Understanding indicator kriging 154
Creating a map using indicator kriging 155
Understanding probability kriging 156
Creating a map using probability kriging 157
Understanding disjunctive kriging 159
Creating a map using disjunctive kriging 160
Understanding cokriging 165
Creating a map using cokriging 166
7 Using analytical tools when generating surfaces 167
Investigating spatial structure: variography 168
Modeling semivariograms and covariance functions 175
Determining the neighborhood search size 181
Determining the neighborhood search size 185
Performing cross-validation and validation 189
Performing cross-validation to assess parameter selections 193
Assessing decision protocol using validation 195
Comparing one model with another 197
Comparing one model with another 199
Modeling distributions and determining transformations 200
Using transformations (log, BoxCox, and arcsine) 204
Using the normal score transformation 205
Checking for the bivariate normal distribution 206
Checking for bivariate distribution 209
Implementing declustering to adjust for preferential sampling 211
Declustering to adjust for preferential sampling 214
Removing trends from the data 216
Removing global and local trends from the data: detrending 218
TOC.p65 03/07/2001, 4:00 PM5
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