Spatial statistics & geostatistics: theory and applications for geographic information science & technology
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Los Angeles [u.a.]
SAGE
2013
|
| Ausgabe: | 1. publ. |
| Schriftenreihe: | GIST
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIV, 181 S. Ill., graph. Darst., Kt. |
| ISBN: | 9781446201749 9781446201732 |
Internformat
MARC
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| 100 | 1 | |a Chun, Yongwan |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Spatial statistics & geostatistics |b theory and applications for geographic information science & technology |c Yongwan Chun & Daniel A. Griffith |
| 250 | |a 1. publ. | ||
| 264 | 1 | |a Los Angeles [u.a.] |b SAGE |c 2013 | |
| 300 | |a XIV, 181 S. |b Ill., graph. Darst., Kt. | ||
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Datensatz im Suchindex
| _version_ | 1804148807897710592 |
|---|---|
| adam_text | Table of Contents
About the Authors
xi
Preface
xiii
1
Introduction
1
1.1.
Spatial statistics and geostatistics
1
1.2.
R
basics
4
2
Spatial Autocorrelation
8
2.1.
Indices measuring spatial dependency
9
2.1.1.
Important properties of
MC 11
2.1.2.
Relationships between
MC
and GR, and
MC
and join count statistics
12
2.2.
Graphic portrayals: the
Moran scatterplot
and
the semi-variogram plot
15
2.3.
Impacts of spatial autocorrelation
17
2.4.
Testing for spatial autocorrelation in regression residuals
17
2.5.
R
code for concept implementations
19
3
Spatial Sampling
23
3.1.
Selected spatial sampling designs
24
3.2.
Puerto Rico DEM data
26
3.3.
Properties of the selected sampling designs: simulation
experiment results
29
3.3.1.
Sampling simulation experiments on a unit square
landscape
30
3.3.2.
Sampling simulation experiments on a hexagonal
landscape structure
33
3.4.
Resampling techniques: reusing sampled data
35
3.4.1.
The bootstrap
35
3.4.2.
The jackknife
36
3.5.
Spatial autocorrelation and effective sample size
38
3.6.
R
code for concept implementations
40
viii Contents
4
Spatial Composition and Configuration
44
4.1.
Spatial
heterogeneity: mean and variance
44
4.1.1. ANOVA 46
4.1.2.
Testing for heterogeneity over a plane: regional
supra-partitionings
46
4.1.2.1.
Establishing a relationship to the
superpopulation
50
4.1.2.2.
A null hypothesis rejection case with heterogeneity
50
4.1.3.
Testing for heterogeneity over a plane:
directional supra-partitionings
52
4.1.4.
Covariates across a geographic landscape
54
4.2.
Spatial weight matrices
57
4.2.1.
Weight matrices for geographic distributions
58
4.2.2.
Weight matrices for geographic flows
59
4.3.
Spatial heterogeneity: spatial autocorrelation
59
4.3.1.
Regional differences
60
4.3.2.
Directional
différences:
anisotropy
61
4.4.
R
code for concept implementations
65
5
Spatially Adjusted Regression and Related Spatial Econometrics
68
5.1.
Linear regression
69
5.2.
Nonlinear regression
72
5.2.1.
Binomial/logistic regression
74
5.2.2.
Poisson/negative
binomial regression
76
5.2.2.1.
Geographic distributions
76
5.2.2.2.
Geographic flows: a journey-to-work example
80
5.3.
R
code for concept implementations
83
6
Local Statistics: Hot and Cold Spots
92
6.1.
Multiple testing with positively correlated data
93
6.2.
Local indices of spatial association
94
6.3.
Getis-Ord statistics
97
6.4.
Spatially varying coefficients
98
6.5.
R
code for concept implementations
Ю0
7
Analyzing Spatial Variance and Covariance with Geostatistics
and Related Techniques
103
7.1.
Semi-variogram models
104
7.2.
Co-kriging
106
7.2.1.
DEM elevation as a covariate
106
7.2.2.
Landsat
7
ETM-t- data as a covariate
108
Contents
¡χ
7.3.
Spatial
linear
operators
109
7.3.1. Multivariate
geographic data 111
7.4.
Eigenvector spatial filtering: correlation coefficient
decomposition
116
7.5.
R
code for concept implementations
118
8
Methods for Spatial Interpolation in Two Dimensions
127
8.1.
Kriging: an algebraic basis
128
8.2.
The EM algorithm
132
8.3.
Spatial autoregression: a spatial EM algorithm
134
8.4.
Eigenvector spatial filtering: another spatial EM algorithm
137
8.5.
R
code for concept implementations
140
9
More Advanced Topics in Spatial Statistics
149
9.1.
Bayesian methods for spatial data
150
9.1.1.
Markov chain Monte Carlo techniques
152
9.1.2.
Selected Puerto Rico examples
154
9.2.
Designing Monte Carlo simulation experiments
161
9.2.1.
A Monte Carlo experiment investigating eigenvector
selection when constructing a spatial filter
162
9.2.2.
A Monte Carlo experiment investigating eigenvector
selection from a restricted candidate set of vectors
163
9.3.
Spatial error: a contributor to uncertainty
165
9.4.
R
code for concept implementations
166
References
169
Index
174
|
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| discipline | Geographie |
| edition | 1. publ. |
| format | Book |
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| id | DE-604.BV039867552 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T00:13:01Z |
| institution | BVB |
| isbn | 9781446201749 9781446201732 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-024726957 |
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| physical | XIV, 181 S. Ill., graph. Darst., Kt. |
| publishDate | 2013 |
| publishDateSearch | 2013 |
| publishDateSort | 2013 |
| publisher | SAGE |
| record_format | marc |
| series2 | GIST |
| spelling | Chun, Yongwan Verfasser aut Spatial statistics & geostatistics theory and applications for geographic information science & technology Yongwan Chun & Daniel A. Griffith 1. publ. Los Angeles [u.a.] SAGE 2013 XIV, 181 S. Ill., graph. Darst., Kt. txt rdacontent n rdamedia nc rdacarrier GIST R Programm (DE-588)4705956-4 gnd rswk-swf Geostatistik (DE-588)4020279-3 gnd rswk-swf Statistik (DE-588)4056995-0 gnd rswk-swf Geowissenschaften (DE-588)4020288-4 gnd rswk-swf Mathematik (DE-588)4037944-9 gnd rswk-swf Geostatistik (DE-588)4020279-3 s DE-604 Geowissenschaften (DE-588)4020288-4 s Mathematik (DE-588)4037944-9 s Statistik (DE-588)4056995-0 s R Programm (DE-588)4705956-4 s Griffith, Daniel A. 1948- Verfasser (DE-588)124843697 aut Digitalisierung UB Bayreuth application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024726957&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Chun, Yongwan Griffith, Daniel A. 1948- Spatial statistics & geostatistics theory and applications for geographic information science & technology R Programm (DE-588)4705956-4 gnd Geostatistik (DE-588)4020279-3 gnd Statistik (DE-588)4056995-0 gnd Geowissenschaften (DE-588)4020288-4 gnd Mathematik (DE-588)4037944-9 gnd |
| subject_GND | (DE-588)4705956-4 (DE-588)4020279-3 (DE-588)4056995-0 (DE-588)4020288-4 (DE-588)4037944-9 |
| title | Spatial statistics & geostatistics theory and applications for geographic information science & technology |
| title_auth | Spatial statistics & geostatistics theory and applications for geographic information science & technology |
| title_exact_search | Spatial statistics & geostatistics theory and applications for geographic information science & technology |
| title_full | Spatial statistics & geostatistics theory and applications for geographic information science & technology Yongwan Chun & Daniel A. Griffith |
| title_fullStr | Spatial statistics & geostatistics theory and applications for geographic information science & technology Yongwan Chun & Daniel A. Griffith |
| title_full_unstemmed | Spatial statistics & geostatistics theory and applications for geographic information science & technology Yongwan Chun & Daniel A. Griffith |
| title_short | Spatial statistics & geostatistics |
| title_sort | spatial statistics geostatistics theory and applications for geographic information science technology |
| title_sub | theory and applications for geographic information science & technology |
| topic | R Programm (DE-588)4705956-4 gnd Geostatistik (DE-588)4020279-3 gnd Statistik (DE-588)4056995-0 gnd Geowissenschaften (DE-588)4020288-4 gnd Mathematik (DE-588)4037944-9 gnd |
| topic_facet | R Programm Geostatistik Statistik Geowissenschaften Mathematik |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024726957&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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