Temporal GIs,9783540414766

Temporal GIs

by ; ;
ISBN13: 9783540414766
ISBN10: 3540414762
Format: Hardcover
Pub. Date: 2002-03-01
Publisher(s): Springer Nature
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Summary

The book focuses on the development of advanced functions for field-based Temporal Geographical Information Systems (TGIS). These fields describe natural, epidemiological, economic, and social phenomena distributed across space and time. The book is organized around 4 main themes: concepts, mathematical tools, computer programs, and applications. The reader is also familiarized with the TGIS toolbox of advanced functions and the associated library of comprehensive computer programs, BMElib. A CD-ROM is included with the book, so that the reader can readily use the computerized advanced TGIS functions of the BMElib to reconstruct many of the numerical applications discussed in the book.

Table of Contents

A BME View to the New Realities of TGIS
1(16)
Introducing a Temporal Geographical Information System (TGIS)
1(3)
Purposefulness, Content, and Context
1(1)
Synthesis, Organization, and Visualization
2(1)
Action - Oriented
3(1)
Field -Based TGIS
4(4)
TGIS Functions
8(2)
Novel Contribution to TGIS
10(4)
BME-Based Advanced Functions
11(1)
Stochastic Modelling
11(1)
BMElib Software
12(1)
Epistemic Viewpoint
12(1)
Scientific Hypothesis Testing and Explanation
13(1)
Revisionistic Paradigm
13(1)
Concluding Remarks
14(3)
Spatiotemporal Modelling
17(16)
Spatiotemporal Continuum
17(7)
The Random Field Model
24(3)
The Role of Metaphors in TGIS
27(1)
The Importance of Physical Geometry
28(4)
Synopsis
32(1)
Knowledge Bases Integration
33(20)
Integrating Knowledge Bases (KB) into TGIS
33(2)
General KB and the Associated Physical Constraints
35(9)
Space/Time Correlation Functions Between Two or More Points (Multiple-Point Statistics)
36(5)
Physical Models
41(3)
Specificatory KB
44(7)
Hard and Soft Data
45(5)
The Effect of Soft Data on The Calculation of the Space/Time Correlation Functions
50(1)
Accommodating Knowledge Needs
51(2)
Knowledge Classification
51(1)
Model Building and Reality Check
51(2)
Spatiotemporal Mapping
53(30)
A Formulation of the Spatiotemporal Mapping Problem
53(3)
Formal BME Analysis and Mapping
56(17)
The Basic BME Procedure
57(2)
The Advantage of Composite Space/Time Mapping
59(4)
Continuous-Valued Map Reconstruction
63(1)
Modifications of the BME Procedure
64(2)
Spatiotemporal Filtering
66(2)
Spatiotemporal Mapping and Change-of-Scale Procedures
68(5)
Other Mapping Techniques
73(8)
Wiener-Kolmogorov Stochastic Interpolation
73(1)
Geostatistical Kriging
74(2)
Kalman-Bucy Filtering
76(1)
Some Comparisons
77(4)
Concluding Remarks
81(2)
Interpretive BME
83(14)
Interpretive Issues
83(1)
An Epistemic Analysis of the BME Approach
84(3)
Non-Bayesian Conditionalization
87(8)
Material Biconditionalization
88(6)
Material Conditionalization
94(1)
By Way of a Summary
95(2)
The BME Toolbox in Action
97(46)
The Fundamental KB Operators
97(1)
Step-by-Step BME
98(5)
The Formal Representation
98(2)
The Diagrammatic Representation
100(3)
Analytic and Synthetic Case-Studies
103(17)
Some Commonly Encountered Situations
103(1)
Spatiotemporal Filtering
104(1)
Exogenous Information
105(5)
Physical Laws
110(3)
Using Soft Data to Improve TGIS Mapping
113(6)
Non-Bayesian Analysis
119(1)
Quantifying the Mapping Efficiency of Soft Data
120(2)
Numerical Investigations of Popular Techniques
122(16)
The Use and Misuse of Soft Data by Statistical Regression-Based Techniques
122(9)
The Inadequacy of Indicator Kriging
131(7)
Merging Maps with BME
138(3)
Synopsis
141(2)
The BME Computer Library
143(46)
Computational BME Analysis and the BMElib
143(1)
Getting Started
144(5)
Notational Convenience
144(1)
Getting Started with MatLab
144(1)
Getting Started with BMElib
145(4)
The iolib Directory
149(4)
The readGeoEAS.m and writeGeoEAS.m Functions
150(1)
The readProba.m and writeProba.m Functions
151(2)
The readBMEproba.m and WriteBMEproba.m Functions
153(1)
The graphlib Directory
153(3)
The scatterplot.m function
153(1)
The colorplot.m function
154(1)
The marketplot.m function
154(1)
The valplot.m function
155(1)
A tutorial Use of the graphlib Directory
155(1)
The modelslib Directory
156(3)
The *C.m and *V.m Functions
156(2)
The modelplot.m Function
158(1)
A Tutorial Use of the modelslib Directory
159(1)
The statlib Directory
159(5)
The kerneldensity.m Function
161(1)
The pdf2cdf.m Function
161(1)
The covario.m Function
162(1)
The crosscovario.m Function
163(1)
The crosscovarioST.m Function
163(1)
A Tutorial Use of the statlib Directory
164(1)
The bmeprobalib Directory
164(11)
The proba*.m Function
165(1)
The BMEprobaMoments.m Function
165(5)
The BMEprobaMode.m Function
170(1)
The BMEprobaPdf.m Function
170(1)
The BMEprobaCI.m Function
171(1)
The BMEprobaTMode.m, BMEprobaTPdf.m and BMEprobaTCI.m Functions
172(1)
Working With Files
173(2)
A Tutorial Use of the bmeprobalib Directory
175(1)
The bmeintlib Directory
175(4)
The BMEintervalMode.m Function
176(1)
The BMEintervalPdf.m Function
176(1)
The BMEintervalTMode.m Function
177(1)
The BMEintervalTPdf.m Function
178(1)
A Tutorial Use of the bmeintlib Directory
179(1)
The bmehrlib Directory
179(2)
The Kriging.m Function
179(1)
The Krigingfilter.m Function
180(1)
A Tutorial Use of the bmehrlib Directory
181(1)
Simulations
181(2)
The simuchol.m Function
181(1)
The simuseq.m Function
182(1)
A Tutorial Use of the simulib Directory
183(1)
The genlib Directory
183(3)
The aniso2iso.m Function
183(1)
The iso2aniso.m Function
184(1)
The coord2dist.m Function
184(1)
The coord2K.m Function
185(1)
The kernelsmoothing.m Function
185(1)
A Tutorial Use of the genlib Directory
186(1)
The mvnlib Directory
186(1)
The mvnlibcompile.m Function
187(1)
Testing the mvnlib Directory
187(1)
BMElib Tutorials, Examples, and Tests
187(2)
The tutorlib Directory
187(1)
The exlib Directory
187(1)
The testslib Directory
188(1)
Scientific Hypothesis Testing, Explanation, and Decision Making
189(20)
On Scientific Methodology
189(4)
Hypothesis Testing
193(4)
Scientific Explanation
197(3)
Geographotemporal Decision Making
200(5)
Prelude
205(4)
References 209(6)
Index 215

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