Burrough, P., A. and McDonnell, R., 1998. Principles of Geographical Information Systems. Oxford University Press. Home/Search Document Not in Database Summary Related Articles Check |
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Object calculus and the object-oriented analysis and design of an .. - Duckham (2001) (Correct)
....example would be the alteration of the length method in the Edge class to derive both Euclidean length and the standard deviation of that length. The calculation for standard deviation of length can, in this case, be derived from standard variance propagation techniques not discussed here (see [13]) Edge ## [length = #(s) s.n 1 .x , # = s.n 1 .get rep.#) s.n 2 .get rep.#) Given the term for Edge ## in Definition 18, it is now possible to write terms for a simple object system capable of both storage and propagation of error, as in Equation 12. Invocation of ....
P.A. Burrough and R.A. McDonnell. Principles of geographical information systems. Clarendon: Oxford, second edition, 1998.
Functional vs Object-Oriented Distributed Languages - Pointon, Priebe, Loidl.. (2001) (Correct)
....is coordinated. All players must make a move within a given time period, introducing soft realtime limits on the application. As players place troops and search, they interact with a world map. The data model itself is based on standard multi layered Geographic Information Systems (GIS) maps [BM98] Several layers, representing di erent aspects of the same geographic area, are used in an overlayed fashion to represent the world. The data is stored in a spatial data structure, a quad tree [Sam90] and therefore the data transferred to a players machine re ects their interest in speci c ....
P. Burrough and R. McDonnell. Principles of Geographical Information Systems. Oxford University Press, 1998.
A Software System for Spatial Data Analysis and Modeling - Lazarevic, Fiez, Obradovic (Correct)
....interpolation techniques such as inverse distance [19] and triangulation [20] can be used but they do not take into account a model of the spatial process, or variograms. Interpolation techniques appropriate for spatial data such as kriging [19] and interpolation using the minimum curvature method [21], are often preferable and are provided in the software system in addition to the regular interpolation techniques mentioned above. Data Normalization. The SDAM software system supports two normalization methods: the transformation of data to a normal distribution and the scaling of data to a ....
Burrough, P. A., McDonnell, R. A., Principles of Geographical Information Systems, Oxford University Press, 1998.
Fuzzy Inference Applied to Spatial Load Forecasting - Miranda, Monteiro (Correct)
.... methodology is particularly suited to high spatial resolution for long range forecasting and multi scenario planning [4] Several models have been used to simulate load growth and improve the performance of distribution load forecasting [5, 6] The Geographical Information System (GIS) technology [7] and its spatial analysis capabilities [8] provides an excellent platform to implement spatial load forecasting techniques. Spatial load forecasting (SLF) based on land use is a modeling technique that consists on identifying and mapping areas with similar growth pattern for each customer class. ....
P. A. Burrough, Principles of Geographical Information Systems, Oxford University Press, New York, 1996. ISBN: 019 -854592-4
A Generalized Modeling Framework for Schema Versioning.. - Grandi, Mandreoli, Scalas (2000) (Correct)
....can be branching, in order to represent alternatives, and also, sometimes, merging. In the following, we will refer to this approach as branching schema versioning. Lately, schema versioning has also proved useful for other typical object oriented applications, like multimedia ones [KB96] and GIS [BM98] Such applications often have temporal requirements, as the evolution of objects has to be tracked and documented. In this context, the temporal aspect of versioning has thus to be considered and temporal schema versioning is required in order to represent the history of changes in the object ....
P. A. Burrough and R. A. McDonnell. Principles of Geographical Information Systems. Oxford University Press, New York, NY, 1998.
Implementation Of Progressive Transmission Algorithms For - Vector Map Data (2004) (Correct)
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Burrough, P., A. and McDonnell, R., 1998. Principles of Geographical Information Systems. Oxford University Press.
Existing Approaches to Software Integration - and a Challenge .. - Land, Crnkovic (Correct)
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Burrough P. A. and McDonnell R., Principles of Geographical Information Systems (2nd edition), ISBN 01982.
Geospatial Information Utility: An Estimation of the.. - Meeks, Dasgupta (2003) (Correct)
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P.A. Burrough, R.A. McDonnell, Principles of geographical information systems, in: P.A. Burrough, et al. (Eds.), Spatial Information Systems and Geostatistics, Oxford Univ. Press, Oxford, 1998, p. 333.
A Generalized Modeling Framework for Schema Versioning.. - Grandi, Mandreoli, Scalas (2000) (Correct)
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P. A. Burrough and R. A. McDonnell. Principles of Geographical Information Systems. Oxford University Press, New York, NY, 1998.
A Quadtree Approach to Domain Decomposition - For Spatial Interpolation (Correct)
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P.A. Burrough, R.A. McDonnell, Principles of Geographical Information Systems, Oxford University Press, 1998. http://www.nsf-middleware.org/. http://www.cs.wisc.edu/condor/condorg/.
Assessing the Thematic Accuracy of Area-Class Soil Maps - Rossiter (2001) (Correct)
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P A Burrough and R A McDonnell. Principles of geographical information systems. Oxford University Press, Oxford, 1998.
Integrating Geostatistical Tools in Geographical.. - Felgueiras.. (Correct)
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P. A. Burrough and R. A. McDonnell, Principles of Geographical Information Systems, Oxford University Press, 1998
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