| Series introduction |
|
vii | (2) |
| Foreword |
|
ix | (4) |
| Preface |
|
xiii | (2) |
| Glossary |
|
xv | (2) |
|
|
|
xvii | |
|
|
|
1 | (8) |
|
1.1 Error sources in GIS data |
|
|
4 | (1) |
|
1.2 The propagation of errors through GIS operations |
|
|
5 | (1) |
|
1.3 Objectives of this study |
|
|
5 | (4) |
|
2 Definition and identification of an error model for quantitative spatial attributes |
|
|
9 | (16) |
|
2.1 A first look at quantitative errors |
|
|
9 | (1) |
|
2.2 Definition of the error model |
|
|
10 | (3) |
|
2.3 Identification of the error model |
|
|
13 | (7) |
|
2.3.1 Three models of spatial variation |
|
|
14 | (2) |
|
2.3.2 Error identification under the three models of spatial variation |
|
|
16 | (4) |
|
2.4 Multivariate extension |
|
|
20 | (2) |
|
2.5 Change of support issues |
|
|
22 | (3) |
|
3 Identification of the error model: a case study |
|
|
25 | (8) |
|
3.1 Mapping the mean highest water table in the Ooypolder |
|
|
25 | (4) |
|
3.2 Comparison of mapping results for the three models of spatial variation |
|
|
29 | (2) |
|
3.3 Discussion and implications for error propagation analysis |
|
|
31 | (2) |
|
4 Error propagation with local GIS operations: theory |
|
|
33 | (18) |
|
4.1 Error propagation with point operations |
|
|
34 | (2) |
|
4.2 Four techniques of error propagation |
|
|
36 | (9) |
|
4.2.1 First order Taylor method |
|
|
36 | (2) |
|
4.2.2 Second order Taylor method |
|
|
38 | (1) |
|
4.2.3 Rosenblueth's method |
|
|
39 | (1) |
|
|
|
40 | (2) |
|
4.2.5 Evaluation and comparison of the four error propagation techniques |
|
|
42 | (3) |
|
4.3 Error propagation with neighbourhood operations |
|
|
45 | (1) |
|
4.4 Sources of error contributions |
|
|
46 | (5) |
|
5 Error propagation with local GIS operations: applications |
|
|
51 | (26) |
|
5.1 Predicted lead consumption in the Geul river valley |
|
|
51 | (5) |
|
5.2 Slope and aspect of the Balazuc digital elevation model |
|
|
56 | (4) |
|
5.3 Predicting soil moisture content with linear regression for the Allier floodplain soils |
|
|
60 | (7) |
|
5.4 Selection of suitable soils in the Lacombe agricultural research station using Boolean and continuous classification |
|
|
67 | (10) |
|
6 Error propagation with global GIS operations: the use of multidimensional simulation |
|
|
77 | (12) |
|
6.1 Monte Carlo method for global operations |
|
|
78 | (1) |
|
6.2 Stochastic simulation of the input random field |
|
|
78 | (2) |
|
6.3 An iterative method for simulating autoregressive random fields |
|
|
80 | (4) |
|
6.4 Numerical experiments with iterative autoregressive simulation |
|
|
84 | (5) |
|
7 Implementation of error propagation techniques in GIS |
|
|
89 | (8) |
|
7.1 Starting points for adding error propagation functionality to an existing GIS |
|
|
89 | (1) |
|
7.2 The ADAM error propagation software tool |
|
|
90 | (3) |
|
7.3 Running the Allier case study with ADAM |
|
|
93 | (4) |
|
8 Summary and conclusions |
|
|
97 | (12) |
|
8.1 Summary of research results: the list of nine research questions |
|
|
97 | (6) |
|
8.2 Summary of research results: additional results |
|
|
103 | (2) |
|
8.3 Towards a full grown error handling capability of GIS |
|
|
105 | (4) |
| References |
|
109 | (12) |
| Author index |
|
121 | (4) |
| Subject index |
|
125 | |
Rohkem infot Taylor & Francis e-raamatute kohta