Local models for spatial analysis:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boca Raton, Fla. [u.a.]
CRC Press
2011
|
| Ausgabe: | 2. ed. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Klappentext |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | XV, 336 S. Ill., graph. Darst., Kt. |
| ISBN: | 9781439829196 |
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| 100 | 1 | |a Lloyd, Christopher D. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Local models for spatial analysis |c Christopher D. Lloyd |
| 250 | |a 2. ed. | ||
| 264 | 1 | |a Boca Raton, Fla. [u.a.] |b CRC Press |c 2011 | |
| 300 | |a XV, 336 S. |b Ill., graph. Darst., Kt. | ||
| 336 | |b txt |2 rdacontent | ||
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| 500 | |a Includes bibliographical references and index | ||
| 650 | 4 | |a Mathematisches Modell | |
| 650 | 4 | |a Geographic information systems |x Mathematical models | |
| 650 | 4 | |a Spatial analysis (Statistics) | |
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Datensatz im Suchindex
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|---|---|
| adam_text | Contents
Preface to the second edition
...................... xiii
Acknowledgements
............................ xv
Introduction
1
1.1
Remit of this book
........................ 2
1.2
Local models and methods
.................... 2
1.3
What is local?
.......................... 4
1.4
Spatial dependence and autocorrelation
............ 5
1.5
Spatial scale
............................ 7
1.5.1
Spatial scale in geographical applications
........ 8
1.6
Stationarity
............................ 9
1.7
Spatial data models
....................... 9
1.7.1
Grid data
......................... 9
1.7.2
Areal
data
......................... 10
1.7.3
Geostatistical data
.................... 10
1.7.4
Point patterns
...................... 10
1.8
Datasets
used for illustrative purposes
............. 11
1.8.1
Monthly precipitation in Great Britain in
1999 .... 11
1.5.2 A digital elevation model (DEM) of Great Britain
. . 13
1.8.3
Positions of minerals in a slab of granite
........ 13
1.5.4 Landcover in Turkey
................... 13
1.8.5
Digital
orthophoto
of Newark. New Jersey
....... 17
l.S.tì
Population of Northern Ireland in
2001......... 17
1.8.7
Other
datasets
...................... 19
1.9
A note on notation
........................ 20
1.10
Overview
............................. 21
Local Modelling
23
2.1
Standard methods and local variations
............. 23
2.2
Approaches to local adaptation
................. 23
2.3
Stratification or segmentation of spatial data
......... 27
2.4
Moving window
;
kernel methods
................. 28
2.5
Locally-varying model parameters
................ 30
2.6
Transforming and
det
rending spatial data
........... 30
2.7
Categorising local statistical models
.............. 30
2.7.1
The nature of spatial subsets
.............. 31
vii
viii Local
Models
for Spatial Analysis
2.7.2
The relationship of spatial subsets to the complete
dataset
........................... 32
2.7.3
The relationship between a global statistic and the
corresponding local statistic
............... 32
2.8
Local models and methods and the structure of the book
... 34
2.9
Overview
............................. 35
3
Grid Data
37
3.1
Exploring spatial variation in gridded variables
........ 37
3.2
Global univariate statistics
.................... 38
3.3
Local univariate statistics
.................... 38
3.4
Analysis of grid data
....................... 38
3.5
Moving windows for grid analysis
................ 39
3.5.1
Image smoothing: Low pass filtering
.......... 41
3.5.2
High pass filters
...................... 42
3.5.3
Edge detectors
...................... 44
3.5.4
Texture
.......................... 44
3.5.5
Other approaches
..................... 47
3.6
Wavelets
.............................. 48
3.6.1
Fourier transforms and wavelet transforms
....... 48
3.6.2
Continuous wavelet transform
.............. 50
3.6.3
Discrete wavelet transform (DWT)
........... 50
3.6.4
Wavelet basis functions
................. 51
3.6.5
Implementation of the DWT
.............. 53
3.6.6
Fast wavelet transform: Illustrated example
...... 54
3.6.7
Two-dimensional (2D) wavelet transforms
....... 56
3.6.8
Other issues
........................ 60
3.6.9
Applications of wavelets
................. 61
3.7
Segmentation
........................... 62
3.8
Analysis of digital elevation models
............... 65
3.9
Overview
............................. 71
4
Spatial Patterning in Single Variables
73
4.1
Local summary statistics
..................... 73
4.2
Geographically weighted statistics
................ 74
4.3
Spatial autocorrelation: Global measures
............ 80
4.3.1
Testing for spatial autocorrelation
........... 83
4.4
Spatial autocorrelation: Local measures
............ 85
4.4.1
Local indicators of spatial association
......... 86
4.4.2
Use of different approaches
............... 97
4.5
Spatial association and categorical data
............ 98
4.6
Other issues
............................ 98
4.7
Overview
............................. 98
Contents ix
5
Spatial Relations
101
5.1
Global
regression .........................
101
5.2
Spatial and local
regression
................... 103
5.3
Regression
and spatial data
................... 105
5.4
Spatial
autoregressive
models ..................
106
5.5
Multilevel modelling
....................... 108
5.6
Allowing for local variation in model parameters
....... 109
5.6.1
Spatial expansion method
................
Ill
5.6.2
Spatially varying coefficient processes
......... 116
5.7
Moving window regression (MWR)
............... 122
5.8
Geographically weighted regression (GWR)
.......... 122
5.8.1
Illustrated application of MWR and GWR
....... 124
5.8.2
Selecting a spatial bandwidth
.............. 126
5.8.3
Testing the significance of the GWR model
...... 127
5.8.4
Geographically weighted regression and collmearity
. . 128
5.8.5
Casestudy:
MWR and GWR
.............. 135
5.8.6
Other geographically weighted statistics
........ 138
5.9
Spatially weighted classification
................. 138
5.10
Local regression methods: Some pros and cons
........ 142
5.11
Overview
............................. 142
6
Spatial Prediction
1:
Deterministic Methods, Curve Fitting,
and Smoothing
145
6.1
Point interpolation
........................ 146
6.2
Global methods
.......................... 147
6.3
Local methods
.......................... 148
6.3.1
Thiessen polygons: Nearest neighbours
......... 148
6.3.2 Triangulation....................... 151
6.3.3
Natural neighbours
.................... 151
6.3.4
Trend surface analysis and local polynomials
..... 153
6.3.5
Linear regression
..................... 153
6.3.6
Inverse distance weighting (IDW)
............ 154
6.3.7
Thin plate splines
..................... 158
6.3.8
Thin plate splines case study
.............. 167
6.3.9
Generalised additive models and penalised regression
splines
........................... 168
6.3.10
Finite difference methods
................ 171
6.3.11
Locally adaptive approaches for constructing digital
elevation models
..................... 171
6.4
Areał
interpolation
........................ 173
6.5
General approaches: Overlay
.................. 175
6.6
Local models and local data
................... 177
6.6.1
Generating surface models from
areał
data
....... 177
6.6.2
Population surface case study
.............. 180
6.6.3
Local volume preservation
................ 181
Local
Models for Spatial Analysis
6.6.4
Making use of prior knowledge
.............184
6.6.5
Uncertainty in
areal
interpolation
............189
6.7
Limitations: Point and
areal
interpolation
...........189
6.8
Overview
.............................190
Spatial Prediction
2:
Geostatistics
191
7.1
Random function models
.....................192
7.2
Stationary
............................193
7.2.1
Strict stationarity
.....................193
7.2.2
Second-order stationarity
................193
7.2.3
Intrinsic stationarity
...................194
7.2.4
Quasi-intrinsic stationarity
...............194
6.2.
б
Nonstationarity
......................194
7.3
Global models
...........................194
7.4
Exploring spatial variation
....................195
7.4.1
The covariance and correlogram
.............195
7.4.2
The variogram
......................197
7.4.3
The cross-variogram
...................198
7.4.4
Variogram models
....................198
7.5
Kriging
..............................204
7.6
Globally constant mean: Simple kriging
............206
7.7
Locally constant mean models
..................208
7.8
Ordinary kriging
.........................208
7.9
Cokriging
.............................212
7.9.1
Linear model of coregionalisation
............212
7.9.2
Applying cokriging
....................213
7.10
Equivalence of splines and kriging
................215
7.11
Conditional simulation
......................215
7.12
The change of support problem
.................216
7.13
Other approaches
.........................216
7.14
Local approaches: Xonstationary models
............217
7.15
Xonstationary mean
.......................220
7.15.1
Trend or drift?
......................220
7.15.2
Modelling and removing large scale trends
.......220
7.16
Xonstationary models for prediction
..............222
7.16.1
Median polish kriging
..................222
7.16.2
Kriging with a trend model
...............222
7.16.3
Intrinsic model of order
к
................225
7.16.4
Use of secondary data
..................226
7.16.5
Locally varying anisotropy
................233
7.
IT Xonsrationary variogram
.....................233
7.
IS Variograms in texture analysis
.................240
7.19
Summary
.............................241
Contents
xi
8
Point Patterns and Cluster Detection
243
8.1
Point patterns
...........................243
8.2
Visual examination of point patterns
..............244
8.3
Measuring event intensity and distance methods
.......245
8.4
Statistical tests of point patterns
................246
8.5
Global methods
..........................246
8.6
Measuring event intensity
....................247
8.6.1
Quadrat count methods
.................247
8.6.2
Quadrat counts and testing for complete spatial
randomness (GSR)
....................248
8.7
Distance methods
.........................249
8.7.1
Nearest neighbour methods
...............250
8.7.2
The A function
......................251
8.8
Other issues
............................255
8.9
Local methods
..........................256
8.10
Measuring event intensity locally
................256
8.10.1
Quadrat count methods
.................256
8.10.2
Kernel estimation
.....................256
8.11
Accounting for the population at risk
..............261
8.12
The local
К
function
.......................261
8.13
Point patterns and detection of clusters
............264
8.14
Overview
.............................270
9
Summary: Local Models for Spatial Analysis
271
9.1
Review
...............................271
9.2
Key issues
.............................272
9.3
Software
..............................272
9.4
Future developments
.......................273
9.5
Summary
.............................274
A Software
275
References
277
Index
307
ENVIRONMENTAL ENGINEERING
LOCAL MODELS FOR SPATIAL ANALYSIS
Written in recognition of developments in spatial data analysis that focused on
differences between places, the first edition of Local Models for Spatial
Analysis broke new ground with its focus on local modelling methods. Reflecting
the continued growth and increased interest in this area, the second edition
describes a wide range of methods which account for local variations in
geographical properties.
What s new in the Second Edition:
•
Additional material on geographically weighted statistics and
local regression approaches
•
A fuller overview of local models with reference to recent critical reviews
about the subject area
•
Expanded coverage of individual methods and connections between
them
•
Restructured chapters that clarify the distinction between global and
local methods
•
New material in each chapter references key studies or other accounts
that support the book
•
Access to online resources that support learning
An introduction to the methods and their underlying concepts, the book uses
worked examples and case studies to demonstrate how the algorithms work,
their practical utility, and range of applications. Starting with first principles,
the author introduces users of Geographical Information Systems to the principles
and applications of some widely used local models for the analysis of spatial
data, including methods being developed and employed in geography and
cognate disciplines. The book discusses the relevant software packages that
can aid in their implementation and provides a summary list in Appendix A.
Presenting examples from a variety of disciplines, the book demonstrates the
importance of local models for all who make use of
spatia!
data. Taking a
problem-driven approach, it provides extensive guidance on the selection and
application of local models.
|
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| discipline | Mathematik Geographie |
| edition | 2. ed. |
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| id | DE-604.BV037395044 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T23:23:23Z |
| institution | BVB |
| isbn | 9781439829196 |
| language | English |
| lccn | 2010027816 |
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| publisher | CRC Press |
| record_format | marc |
| spelling | Lloyd, Christopher D. Verfasser aut Local models for spatial analysis Christopher D. Lloyd 2. ed. Boca Raton, Fla. [u.a.] CRC Press 2011 XV, 336 S. Ill., graph. Darst., Kt. txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references and index Mathematisches Modell Geographic information systems Mathematical models Spatial analysis (Statistics) Geoinformationssystem (DE-588)4261642-6 gnd rswk-swf Regionalforschung (DE-588)4177424-3 gnd rswk-swf Mathematische Geografie (DE-588)4169101-5 gnd rswk-swf Mathematische Geografie (DE-588)4169101-5 s Geoinformationssystem (DE-588)4261642-6 s Regionalforschung (DE-588)4177424-3 s DE-604 Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=022547855&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=022547855&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Lloyd, Christopher D. Local models for spatial analysis Mathematisches Modell Geographic information systems Mathematical models Spatial analysis (Statistics) Geoinformationssystem (DE-588)4261642-6 gnd Regionalforschung (DE-588)4177424-3 gnd Mathematische Geografie (DE-588)4169101-5 gnd |
| subject_GND | (DE-588)4261642-6 (DE-588)4177424-3 (DE-588)4169101-5 |
| title | Local models for spatial analysis |
| title_auth | Local models for spatial analysis |
| title_exact_search | Local models for spatial analysis |
| title_full | Local models for spatial analysis Christopher D. Lloyd |
| title_fullStr | Local models for spatial analysis Christopher D. Lloyd |
| title_full_unstemmed | Local models for spatial analysis Christopher D. Lloyd |
| title_short | Local models for spatial analysis |
| title_sort | local models for spatial analysis |
| topic | Mathematisches Modell Geographic information systems Mathematical models Spatial analysis (Statistics) Geoinformationssystem (DE-588)4261642-6 gnd Regionalforschung (DE-588)4177424-3 gnd Mathematische Geografie (DE-588)4169101-5 gnd |
| topic_facet | Mathematisches Modell Geographic information systems Mathematical models Spatial analysis (Statistics) Geoinformationssystem Regionalforschung Mathematische Geografie |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=022547855&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=022547855&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT lloydchristopherd localmodelsforspatialanalysis |