Principles of modeling uncertainties in spatial data and spatial analysis:
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CRC Press
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| Physical Description: | XXV, 412 S. Ill., graph. Darst., Kt. 23 cm |
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| 100 | 1 | |a Shi, Wenzhong John |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Principles of modeling uncertainties in spatial data and spatial analysis |c Wenzhong Shi |
| 264 | 1 | |a Boca Raton, Fla. [u.a.] |b CRC Press |c 2010 | |
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| 650 | 0 | |a Geographic information systems / Mathematical models | |
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| 650 | 4 | |a Geographic information systems |x Data processing | |
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| adam_text | Titel: Principles of modeling uncertainties in spatial data and spatial analyses
Autor: Shi, Wenzhong
Jahr: 2010
Contents
Foreword.................................................................................................................xix
Michael F. Goodchild
Preface.....................................................................................................................xxi
Acknowledgments..................................................................................................xxv
SECTION I Overview
Chapter 1 Introduction..........................................................................................3
1.1 Uncertainty................................................................................3
1.1.1 The Concept of Uncertainty.........................................3
1.1.2 The Concept of Errors..................................................5
1.1.2.1 Random Error...............................................5
1.1.2.2 Systematic Error...........................................5
1.1.2.3 Gross Errors..................................................6
1.2 Universality of Uncertainty.......................................................6
1.3 Uncertainty in Spatial Data.......................................................8
1.3.1 Dimensions of Spatial Data..........................................8
1.3.2 Spatial Data Quality.....................................................9
1.3.2.1 Quality Components.....................................9
1.3.2.2 Elements of Spatial Data Quality...............10
1.4 Summary.................................................................................12
References..........................................................................................12
Chapter 2 Sources of Uncertainty in Spatial Data and Spatial Analysis............15
2.1 Introduction.............................................................................15
2.2 Uncertainties Inherent in the Natural World...........................17
2.3 Uncertainty Resulting from Human Cognition
Limitations...............................................................................18
2.4 Uncertainty Resulting from Measurement..............................18
2.4.1 Spatial Data................................................................18
2.4.2 Spatial Data Measurement Methods..........................19
2.4.3 Uncertainties in Spatial Data Capture........................20
2.4.3.1 Map Digitization.........................................21
2.4.3.2 Aerial Photogrammetry..............................21
2.4.3.3 The Total Station........................................21
2.4.3.4 Satellite Positioning Technology................22
2.4.3.5 Laser Scanner.............................................23
2.4.3.6 Remote Sensing Technology.......................23
vi Contents
2.5 Uncertainties in Spatial Analyses and Data Processing..........24
2.5.1 Uncertainties in Spatial Analyses..............................24
2.5.2 Uncertainty in Spatial Data Processing.....................25
2.5.2.1 Uncertainty Introduced from
Computation and Equipment......................25
2.5.2.2 Uncertainty Due to Heterogeneous
Data Fusion.................................................26
2.6 Summary.................................................................................26
References..........................................................................................26
Chapter 3 Mathematical Foundations.................................................................27
3.1 Introduction.............................................................................27
3.2 Probability Theory..................................................................27
3.2.1 Probability of a Random Event..................................28
3.2.1.1 Operations of Events...................................28
3.2.1.2 Definition of Probability.............................28
3.2.1.3 Basic Axioms of Probability.......................29
3.2.1.4 General Formula of Probability..................29
3.2.2 Random Variable and Distribution Function.............32
3.2.2.1 Random Variable and Its Probability
Distribution Function..................................32
3.2.2.2 Properties of the Distribution Function......32
3.2.2.3 The Distribution Function of a
Function of the Random Variable...............32
3.2.3 Statistical Properties of the Random Variable...........33
3.2.3.1 Expectation and Variance...........................33
3.2.3.2 Properties of the Expectation and the
Variance......................................................34
3.2.3.3 Chebyshev s Inequality...............................34
3.2.3.4 Median and Mode.......................................35
3.2.3.5 Covariance and Correlation Coefficient.....35
3.2.4 Laws of Large Numbers and Central Limit Theory.....35
3.2.4.1 Laws of Large Numbers.............................35
3.2.4.2 The Central Limit Theorem........................36
3.3 Statistics...................................................................................37
3.3.1 Introduction of Statistics............................................37
3.3.2 Distribution Function of the Random Variable..........37
3.3.2.1 Commonly Used Discrete Distribution......37
3.3.2.2 Commonly Used Continuous
Distribution.................................................40
3.3.3 Estimation of a Population Parameter........................40
3.3.3.1 Population and Sample...............................40
3.3.3.2 Statistic of the Population and the
Sample........................................................40
3.3.3.3 Population Parameter Estimation...............42
Contents
3.3.4 Tests of Statistical Hypotheses...................................46
3.3.4.1 General Procedure for the Hypothesis
Test..............................................................46
3.3.4.2 Statistical Hypothesis about
Distribution Function..................................46
3.3.5 Statistics for Spatial Data...........................................47
3.3.5.1 Geostatistical Data......................................47
3.3.5.2 Lattice Data................................................47
3.3.5.3 Point Patterns..............................................48
3.3.5.4 Objects........................................................48
3.4 The Dempster-Shafer Theory of Evidence.............................48
3.4.1 Terminologies and Symbols.......................................48
3.4.2 Nonspecificity Measure..............................................50
3.4.3 Discord Measure........................................................52
3.4.4 Measure of Total Uncertainty....................................53
3.4.5 Application of the Evidence Theory for Spatial
Data............................................................................53
3.5 Fuzzy Theory..........................................................................54
3.5.1 Introduction................................................................54
3.5.2 Fuzzy Set and Its Operations.....................................54
3.5.2.1 Fuzzy Set....................................................54
3.5.2.2 Operations of Fuzzy Sets............................56
3.5.3 Relationships Between the Fuzzy Set and the
Classical Set...............................................................57
3.5.3.1 Definition of Level Set................................57
3.5.4 Fuzzy Sets in a Real Universe....................................58
3.5.4.1 Left-Shouldered Membership Function......58
3.5.4.2 Right-Shouldered Membership
Function......................................................59
3.5.4.3 Middle Membership Function....................60
3.5.5 Fuzzy Topology..........................................................61
3.5.5.1 Fuzzy Projection and Its Properties............62
3.5.5.2 Fuzzy Topological Space............................62
3.6 Rough Sets...............................................................................64
3.6.1 Definitions and Properties..........................................64
3.6.2 Approximation and Membership Relation.................65
3.6.3 Characteristic of Inaccuracy......................................66
3.6.3.1 Numerical Characteristic............................66
3.6.3.2 Topological Characteristic..........................67
3.6.4 Approximation for Classification...............................68
3.6.5 Rough Equality and Rough Inclusion........................69
3.6.5.1 Rough Equality of a Set..............................69
3.6.5.2 Rough Inclusion of a Set.............................69
3.7 Information Theory and Entropy............................................70
3.7.1 Mathematical Information Source Model..................70
3.7.2 Amount of Self-Information.......................................71
Contents
3.7.3 Entropy of Information...............................................72
3.7.4 Algebraic and Analytical Properties of Entropy........73
3.8 Summary.................................................................................76
References..........................................................................................76
SECTION II Modeling Uncertainties in Spatial Data
Chapter 4 Modeling Positional Uncertainty in Spatial Data..............................81
4.1 Introduction.............................................................................81
4.2 A Review of Existing Error Models........................................82
4.2.1 Positional Error for a Point on a Line Segment..........82
4.2.2 Positional Error Distribution of Spatial Features.......83
4.2.3 Error-Band Model for Line Features..........................83
4.3 Definition of Spatial Features in Geographic Information
Science.....................................................................................84
4.3.1 One-Dimensional Spatial Features............................85
4.3.2 Two-Dimensional Spatial Features............................86
4.3.3 «-Dimensional Spatial Features.................................87
4.4 Modeling Positional Uncertainty for a Point...........................89
4.5 Confidence Region Models......................................................91
4.5.1 Confidence Interval Model for Spatial Features
in One-Dimensional Space.........................................91
4.5.1.1 Confidence Interval of a Point in a
One-Dimensional Space.............................92
4.5.1.2 Confidence Interval of a Line Segment
in a One-Dimensional Space......................92
4.5.1.3 Confidence Interval of a One-
Dimensional Polyline..................................93
4.5.2 Confidence Region Model for Spatial Features in
Two-Dimensional Space.............................................94
4.5.2.1 Confidence Region Model for a Point
in Two-Dimensional Space.........................94
4.5.2.2 Confidence Region Model for a Line
Segment in Two-Dimensional Space..........95
4.5.2.3 A Confidence Region Model for a
Polyline in Two-Dimensional Space...........97
4.5.3 Confidence Space Model for Spatial Feature in
an rc-Dimensional Space...........................................100
4.5.3.1 Confidence Space for a Point in an
n-Dimensional Space................................100
4.5.3.2. Confidence Space for a Line Segment
in an «-Dimensional Space.......................101
4.5.3.3 Confidence Space for an
n-Dimensional Polyline............................101
Contents ix
4.6 Probability Distribution Model for Line Segment.................103
4.7 g-Band Error Model for Line Segment..................................107
4.7.1 Error Distribution and Probability Density
Functions..................................................................107
4.7.2 Error Information of a Line Segment.......................109
4.7.3 The G-Band Model...................................................109
4.7.4 Statistical Characteristics of G-Band.......................Ill
4.7.4.1 Directional Independence.........................Ill
4.7.5 Note on the G-Band Error Model.............................115
4.8 Modeling Positional Uncertainty of a Curve.........................115
4.8.1 Positional Error at Any Point on a Curve.................115
4.8.2 The £„ Error Model...................................................118
4.8.3 The £m Error Model..................................................119
4.8.4 An Error Model for Irregular Curve: Third-
Order Spline Curve..................................................122
4.8.5 Case Study and Analysis..........................................125
4.8.6 Note on Curve Error Models....................................127
4.9 Modeling Polygon Positional Uncertainty.............................128
4.9.1 Error Modeling Based on Its Component Vertices.... 128
4.9.2 Error Modeling Based on Its Composing Line
Segments..................................................................129
4.9.3 Case Study and Analysis..........................................130
4.10 Summary and Comment........................................................132
References........................................................................................132
Chapter 5 Modeling Attribute Uncertainty.......................................................135
5.1 Introduction...........................................................................135
5.1.1 Attribute and Attribute Data....................................135
5.1.2 Attribute Uncertainty...............................................136
5.1.3 Sources of Attribute Uncertainty.............................136
5.1.4 Relationship Between Attribute and Positional
Uncertainties............................................................139
5.1.5 Uncertainty in Classification....................................139
5.2 Methods for Modeling Attribute Uncertainties.....................140
5.2.1 Sampling Methods...................................................140
5.2.2 Internal and External Testing...................................141
5.2.3 Error Matrix Method................................................142
5.2.4 Probability Vector and the Four Parameters............145
5.2.4.1 Maximum Likelihood Classification........145
5.2.4.2 Probability Vector.....................................146
5.2.4.3 The Four Parameters................................146
5.2.5 The Incidence of Defects Method............................148
5.2.6 Modeling Error Propagation for Continuous
Attribute Data...........................................................151
5.2.7 Sensitivity Analysis..................................................154
x Contents
5.3 Summary and Comment........................................................154
References........................................................................................155
Chapter 6 Modeling Integrated Positional and Attribute Uncertainty.............157
6.1 Introduction...........................................................................157
6.2 Problem Definition................................................................159
6.3 The S-Band Model................................................................160
6.4 Probability Theory-Based Solution.......................................160
6.5 Certainty Factor-Based Solution...........................................161
6.5.1 The MYCIN Certainty Factor..................................161
6.5.2 Probabilistic Interpretation of Certainty Factors.....163
6.5.3 The Certainty Factor-Based Solution.......................164
6.5.4 Derivation of the Formulas......................................164
6.5.5 The Computational Procedure.................................166
6.6 An Example of Modeling Integrated Uncertainty.................166
6.6.1 Modeling Positional Uncertainty.............................167
6.6.2 Modeling Attribute Uncertainty...............................168
6.6.3 Modeling Integrated Positional and Attribute
Uncertainty...............................................................169
6.6.4 Visualization of Uncertainties..................................169
6.7 Summary and Comment........................................................172
References........................................................................................172
SECTION III Modeling Uncertainties in Spatial Model
Chapter 7 Modeling Uncertain Topological Relationships...............................175
7.1 An Overview of Topological Relationship Models...............175
7.1.1 The Four-Intersection Model....................................176
7.1.2 The Nine-Intersection Model...................................176
7.1.3 Algebraic Model.......................................................176
7.1.4 The Egg-Yolk Model.............................................177
7.1.5 A Nine-Intersection Model Between Simple
Fuzzy Regions..........................................................177
7.2 Modeling Topological Relationships Between Objects.........178
7.2.1 Representation of Spatial Objects............................178
7.2.1.1 W-Cell and/V-Cell Complex.....................178
7.2.1.2 The Definition of a Spatial Object............179
7.2.2 Topological Relationships Between Spatial
Objects......................................................................180
7.2.3 A Decision Algorithm for Topological
Relationship..............................................................181
7.3 Modeling Uncertain Topological Relationships....................182
Contents xi
7.3.1 Fuzzy Definition of GIS Elements...........................183
7.3.1.1 Fuzzy Point...............................................183
7.3.1.2 Simple Fuzzy Line....................................183
7.3.1.3 Fuzzy Region............................................183
7.3.2 Quasi Coincidence....................................................183
7.3.3 Quasi Difference......................................................186
7.3.4 Topological Relations Between Two Fuzzy Sets
in/?2..........................................................................188
7.4 An Application Example.......................................................190
7.4.1 Background..............................................................190
7.4.2 Fuzzy Topology for SARS Analysis........................190
7.4.2.1 Effect of an Infected Person on a
Community...............................................190
7.4.2.2 Effect of an Infected Region on
Neighboring Regions................................190
7.5 Summary...............................................................................192
References........................................................................................192
Chapter 8 Modeling Uncertainty in Digital Elevation Models.........................195
8.1 Introduction...........................................................................195
8.2 Surface Modeling..................................................................195
8.2.1 Common Interpolation Methods..............................196
8.2.2 Regular Grid Digital Elevation Model.....................199
8.2.3 A Triangulated Irregular Network Model................200
8.3 Error Sources of a DEM Model............................................200
8.4 Accuracy Estimation for a TIN Model..................................202
8.4.1 Mathematical Formula of TIN Accuracy
Estimation................................................................203
8.4.2 Experimental Validation of the Formula..................206
8.4.3 Theoretical Proof for the Mathematical Formula.... 207
8.4.4 A Note on the Derived Mathematical Formula........210
8.5 Accuracy Estimation of a Regular Grid DEM......................210
8.5.1 The Bicubic Interpolation.........................................211
8.5.1.1 Two-Dimensional Cubic Interpolation.....211
8.5.1.2 Three-Dimensional Cubic Interpolation....213
8.5.2 Accuracy Estimation for the DEM Generated
from the Bicubic Interpolation.................................215
8.5.2.1 The Average Elevation Error....................215
8.5.2.2 A Formula for the Average Elevation
Error..........................................................217
8.5.2.3 Error Measure for the Bicubic
Interpolation..............................................219
8.5.2.4 A Note.......................................................219
8.6 Summary...............................................................................219
References........................................................................................220
xii Contents
SECTION IV Modeling Uncertainties in Spatial
Analyses
Chapter 9 Modeling Positional Uncertainties in Overlay Analysis..................223
9.1 Introduction...........................................................................223
9.2 Review of the Existing Models..............................................224
9.3 Uncertainty Modeling for the Generated Polygon................225
9.3.1 Analytical Approach................................................225
9.3.1.1 Covariance Matrix of an Intersection
Point..........................................................225
9.3.1.2 Covariance Matrix of Vertices of the
Generated Polygon....................................228
9.3.1.3 Variances of Measurements of the
Generated Polygon....................................229
9.3.1.4 Uncertainty Interval for the Vertices of
the Generated Polygon..............................230
9.3.1.5 A Note on the Analytical Model..............231
9.3.2 Simulation Approach................................................232
9.3.2.1 A Simulated Sample Covariance
Matrix for the Generated Polygon............234
9.3.2.2 Simulated Sample Variances of
Measurements of the Generated Polygon. 235
9.3.2.3 Simulated Uncertainty Intervals of the
Generated Polygon....................................236
9.4 Summary and Comment........................................................237
References........................................................................................237
Chapter 10 Modeling Positional Uncertainty in Buffer Analysis.......................239
10.1 Introduction...........................................................................239
10.2 Existing Buffer Analysis Error Model..................................240
10.3 A Probability-Based Uncertainty Model for Buffer
Analysis.................................................................................241
10.3.1 Error of Commission and Error of Omission...........241
10.3.1.1 Buffer Around a Point..............................243
10.3.1.2 Buffer Around a Straight-Line
Segment....................................................244
10.3.1.3 Buffer Around a Polyline..........................246
10.3.1.4 Buffer Around a Polygon..........................248
10.3.1.5 Discussion of the Error of Commission
and the Error of Omission........................249
10.3.2 Normalized Discrepant Area...................................250
10.4 Summary and Comment........................................................255
References........................................................................................255
Contents xiü
Chapter 11 Modeling Positional Uncertainty in Line Simplification.................257
11.1 Introduction...........................................................................257
11.2 Uncertainties in Line Simplification.....................................258
11.3 Linear Attribute Measurement-Based Error Model..............259
11.3.1 Modeling Measurement Error of the Initial Line.....259
11.3.2 Modeling Line Simplification Error.........................260
11.3.3 Modeling the Total Error..........................................262
11.3.4 An Example..............................................................263
11.4 Summary...............................................................................265
References........................................................................................265
SECTION V Quality Control of Spatial Data
Chapter 12 Quality Control for Object-Based Spatial Data................................269
12.1 Introduction...........................................................................269
12.2 Adjustment Methods for Area Object Error Processing.......270
12.2.1 Conditional Equations of the Parcel Area................270
12.2.1.1 The Rectangular Conditional Equation.... 271
12.2.1.2 Conditional Equation for Arcs..................272
12.2.2 Estimation of Variance Components........................275
12.2.3 Area Adjustment with Scale Parameter...................277
12.2.3.1 Area Conditional Equation with Scale
Parameter..................................................277
12.2.3.2 The Effect of Scale Error and Its
Significance Test.......................................278
12.2.3.3 Variance Components Estimation for
the Conditional Adjustment with Scale
Parameter..................................................280
12.3 Quality Control Methods for Cadastral Data........................280
12.4 A Case Study.........................................................................283
12.4.1 Area Adjustment Neglecting Error of Registered
Parcel Area...............................................................283
12.4.2 Estimation of Variance Components with
Rectangular Constraints...........................................285
12.4.3 Area Adjustment with Scale Parameter and
Rectangular Constraints...........................................286
12.5 Summary...............................................................................289
References........................................................................................290
Chapter 13 Quality Control for Field-Based Spatial Data..................................291
13.1 Introduction...........................................................................291
13.2 Two-Dimensional Transformation Models............................292
xiv Contents
13.2.1 The Generic Two-Dimensional Polynomial
Transformation Model..............................................292
13.2.2 The Conformai Transformation Model....................293
13.2.3 The Two-Dimensional Affine Transformation
Model........................................................................293
13.2.4 The Projective Transformation Model.....................294
13.3 Three-Dimensional Image to Object SPACE
Transformation Models.........................................................294
13.3.1 Generic Three-Dimensional Polynomial Model......294
13.3.2 Affine Transformation Model..................................295
13.3.3 Rational Function Model..........................................295
13.4 Line-Based Transformation Model.......................................296
13.4.1 Relationship Defined by Unit Vector.......................296
13.4.2 Affine LBTM...........................................................298
13.5 Experimental Studies on Point-Based Models......................299
13.5.1 Data Set....................................................................299
13.5.2 Experiments Using the Two-Dimensional
Transformation Models............................................300
13.5.3 Experiments on the Three-Dimensional
Transformation Model..............................................301
13.6 An Experimental on Line-Based Transformation Model......302
13.6.1 Data Sets...................................................................303
13.6.2 Results and Analysis................................................304
13.7 Summary and Comment........................................................305
References........................................................................................306
Chapter 14 Improved Interpolation Methods for Digital Elevation Model........309
14.1 Introduction...........................................................................309
14.2 Hybrid Interpolation Method.................................................309
14.2.1 Mathematical Expression of Hybrid Interpolation... 310
14.2.2 Theoretical Interpretation of p.....................................311
14.2.3 Experimental Results...............................................313
14.2.3.1 Data Set A.................................................313
14.2.3.2 Data Set B.................................................316
14.3 Bidirectional Interpolation Method.......................................316
14.3.1 Mathematical Formula for Bidirectional
Interpolation.............................................................317
14.3.2 Slope Estimation......................................................318
14.3.3 Experimental Results...............................................319
14.3.3.1 Data Set A.................................................320
14.3.3.2 Data Set B.................................................322
14.4 Summary...............................................................................324
References........................................................................................324
Contents xv
SECTION VI Presentation of Data Quality
information
Chapter 15 Visualization of Uncertainties in Spatial Data.................................327
15.1 Introduction...........................................................................327
15.2 Error Ellipse Approach..........................................................328
15.2.1 Basic Equation..........................................................329
15.2.2 Confidence Region Model for Line Features...........330
15.2.3 An Analysis of the Error Ellipse..............................330
15.3 Arrow-Based Approach.........................................................330
15.3.1 An Example of Image Rectification.........................331
15.3.1.1 Conformai Transformation.......................331
15.3.1.2 Inverse Distance Interpolation..................334
15.3.1.3 Visualization of Uncertainty in a
Rectified Image.........................................335
15.3.2 Analysis of the Arrow-Based Approach..................335
15.4 Gray-Scale Map.....................................................................336
15.4.1 Maximum Likelihood Classification........................337
15.4.2 Single Class Mapping...............................................337
15.5 Color Map..............................................................................338
15.5.1 RGB Color Model.....................................................339
15.5.1.1 Pixel Mixture............................................340
15.5.1.2 Color Mixture...........................................340
15.5.2 HSI Color Model......................................................341
15.5.3 Analysis of the Color Approach...............................343
15.6 Other Symbol-Based Approaches.........................................344
15.7 Three-Dimensional Approach...............................................344
15.7.1 The 3D Approach for Vector Data...........................345
15.7.2 The 3D Approach for Raster Data............................346
15.7.3 An Analysis of Three-Dimensional Approach........347
15.8 Graphic Animation................................................................347
15.8.1 The Animation Approach for Vector Map...............347
15.8.2 Raster Image Animation Approach.........................347
15.8.3 An Analysis of the Animation Approach.................348
15.9 Summary and Comment........................................................348
References........................................................................................348
Chapter 16 Metadata on Spatial Data Quality....................................................351
16.1 Introduction...........................................................................351
16.1.1 The Federal Geographic Data Committee
Metadata Standard...................................................352
16.1.2 The ANZLIC Standard............................................353
xvi Contents
16.1.3 The CEN/TC287 Standard.......................................354
16.1.4 The ISO Metadata Standard.....................................354
16.2 Quality Indicators in Metadata..............................................356
16.2.1 Data Quality Classes and Subclasses.......................356
16.2.1.1 Lineage.....................................................356
16.2.1.2 Quality Information Report......................357
16.2.2 Completeness............................................................358
16.2.3 Logical Consistency.................................................359
16.2.3.1 Measures for Conceptual Consistency......359
16.2.3.2 Measures for Domain Consistency...........360
16.2.3.3 Measures for Format Consistency............360
16.2.3.4 Measures for Topological Consistency.....360
16.2.4 Positional Accuracy..................................................361
16.2.4.1 Absolute or External Accuracy.................361
16.2.4.2 Relative or Internal Accuracy...................364
16.2.4.3 Gridded Data Position Accuracy..............365
16.2.5 Temporal Accuracy..................................................365
16.2.5.1 Accuracy of a Time Measurement............365
16.2.5.2 Temporal Consistency...............................365
16.2.5.3 Temporal Validity.....................................366
16.2.6 Thematic Accuracy..................................................366
16.2.6.1 Classification Correctness........................366
16.2.6.2 Nonquantitative Attribute Accuracy.........367
16.2.6.3 Quantitative Attribute Accuracy...............367
16.3 An Object-Oriented Metadata System..................................367
16.3.1 Database Design.......................................................368
16.4 Summary and Comment........................................................369
References........................................................................................371
Chapter 17 The Web Service-Based Spatial Data Quality Information
System..............................................................................................373
17.1 Introduction...........................................................................373
17.2 Design of the System.............................................................374
17.2.1 Data Transformation Service...................................374
17.2.2 Service on Data Quality Information.......................376
17.2.3 The Client Design.....................................................376
17.3 Functions of the Data Quality Information System..............377
17.3.1 Quality Information of Point Objects.......................377
17.3.1.1 Definition of Interfaces.............................378
17.3.2 Quality Information of Line Objects........................379
17.3.3 Quality Information of Area Objects.......................380
17.3.4 Quality Information of Buffer Spatial Analysis.......381
17.3.5 Quality Information on Overlay Spatial Analysis.... 383
17.4 Summary and Comment........................................................385
Contents xvii
SECTION VII Epilogue
Chapter 18 Epilogue............................................................................................389
18.1 Research Issues for the Future...............................................389
18.1.1 Understanding More about the Complexity of the
Natural World...........................................................389
18.1.2 Investigation of Uncertainties in the Cognition of
Geographic Objects..................................................390
18.1.3 Modeling Integrated Measurement Errors...............391
18.1.4 Uncertainty Modeling for Complex Spatial
Analyses...................................................................391
18.1.5 Data Quality Control for GIS with Complex
Uncertainties............................................................391
18.1.6 Three Fundamental Issues.......................................392
18.2 More Mathematical Theories for Error Modeling................392
18.2.1 Geostatistics.............................................................392
18.2.2 Least Squares Adjustment........................................393
18.3 Implementation Issues...........................................................393
18.3.1 Error Awareness.......................................................393
18.3.2 Software for Data Quality Control...........................394
18.3.3 Quality Marks on GIS Dataproducts......................394
18.3.4 Data Quality Standards............................................395
18.4 Interaction with Other Disciplines........................................395
18.5 Concluding Remarks.............................................................396
Acknowledgment..............................................................................396
Index......................................................................................................................397
|
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| callnumber-label | G70 |
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| dewey-raw | 910.285 |
| dewey-search | 910.285 |
| dewey-sort | 3910.285 |
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| discipline | Geographie |
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| id | DE-604.BV036101504 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T22:11:37Z |
| institution | BVB |
| isbn | 1420059270 9780420059277 |
| language | English |
| lccn | 2008005717 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-018991861 |
| oclc_num | 192134357 |
| open_access_boolean | |
| owner | DE-706 DE-83 |
| owner_facet | DE-706 DE-83 |
| physical | XXV, 412 S. Ill., graph. Darst., Kt. 23 cm |
| publishDate | 2010 |
| publishDateSearch | 2010 |
| publishDateSort | 2010 |
| publisher | CRC Press |
| record_format | marc |
| spelling | Shi, Wenzhong John Verfasser aut Principles of modeling uncertainties in spatial data and spatial analysis Wenzhong Shi Boca Raton, Fla. [u.a.] CRC Press 2010 XXV, 412 S. Ill., graph. Darst., Kt. 23 cm txt rdacontent n rdamedia nc rdacarrier Geographic information systems / Data processing Geographic information systems / Mathematical models Datenverarbeitung Mathematisches Modell Geographic information systems Data processing Geographic information systems Mathematical models Geoinformationssystem (DE-588)4261642-6 gnd rswk-swf Mathematische Modellierung (DE-588)7651795-0 gnd rswk-swf Geoinformationssystem (DE-588)4261642-6 s Mathematische Modellierung (DE-588)7651795-0 s DE-604 DE-601 pdf/application http://www.gbv.de/dms/bowker/toc/9781420059274.pdf Inhaltsverzeichnis HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018991861&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Shi, Wenzhong John Principles of modeling uncertainties in spatial data and spatial analysis Geographic information systems / Data processing Geographic information systems / Mathematical models Datenverarbeitung Mathematisches Modell Geographic information systems Data processing Geographic information systems Mathematical models Geoinformationssystem (DE-588)4261642-6 gnd Mathematische Modellierung (DE-588)7651795-0 gnd |
| subject_GND | (DE-588)4261642-6 (DE-588)7651795-0 |
| title | Principles of modeling uncertainties in spatial data and spatial analysis |
| title_auth | Principles of modeling uncertainties in spatial data and spatial analysis |
| title_exact_search | Principles of modeling uncertainties in spatial data and spatial analysis |
| title_full | Principles of modeling uncertainties in spatial data and spatial analysis Wenzhong Shi |
| title_fullStr | Principles of modeling uncertainties in spatial data and spatial analysis Wenzhong Shi |
| title_full_unstemmed | Principles of modeling uncertainties in spatial data and spatial analysis Wenzhong Shi |
| title_short | Principles of modeling uncertainties in spatial data and spatial analysis |
| title_sort | principles of modeling uncertainties in spatial data and spatial analysis |
| topic | Geographic information systems / Data processing Geographic information systems / Mathematical models Datenverarbeitung Mathematisches Modell Geographic information systems Data processing Geographic information systems Mathematical models Geoinformationssystem (DE-588)4261642-6 gnd Mathematische Modellierung (DE-588)7651795-0 gnd |
| topic_facet | Geographic information systems / Data processing Geographic information systems / Mathematical models Datenverarbeitung Mathematisches Modell Geographic information systems Data processing Geographic information systems Mathematical models Geoinformationssystem Mathematische Modellierung |
| url | http://www.gbv.de/dms/bowker/toc/9781420059274.pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018991861&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT shiwenzhongjohn principlesofmodelinguncertaintiesinspatialdataandspatialanalysis |
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