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1. |
Record Nr. |
UNISALENTO991000648219707536 |
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Titolo |
Advances in the theory of Riemann surfaces : proceedings of the 1969 Stony Brook conference / edited by Lars V. Ahlfors...[et al.] |
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Pubbl/distr/stampa |
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Princeton : Princeton Univ. Press, 1971 |
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ISBN |
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Descrizione fisica |
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Collana |
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Annals of mathematics studies ; 66 |
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Classificazione |
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QA333.A35 |
AMS 30-06 |
AMS 30F |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Functions of a complex variable - Congresses |
Riemann surfaces - Congresses |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Proceedings of the 2nd of a series of meetings; proceedings of the 3rd are entered under Conference on Discontinuous Groups and Riemann Surfaces, University of Maryland, 1973. |
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Nota di bibliografia |
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Includes bibliographical references |
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2. |
Record Nr. |
UNINA9910830606003321 |
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Titolo |
Spatial interpolation for climate data [[electronic resource] ] : the use of GIS in climatology and meterology / / edited by Hartwig Dobesch, Pierre Dumolard, Izabela Dyras |
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Pubbl/distr/stampa |
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London ; ; Newport Beach, CA, : ISTE, 2007 |
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ISBN |
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1-280-84783-2 |
9786610847839 |
0-470-39491-9 |
0-470-61226-6 |
1-84704-620-7 |
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Descrizione fisica |
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1 online resource (304 p.) |
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Collana |
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Geographical information systems series |
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Altri autori (Persone) |
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DobeschHartwig |
DumolardPierre |
DyrasIzabela |
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Disciplina |
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Soggetti |
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Climatology - Data processing |
Meteorology - Data processing |
Geospatial data - Mathematical models |
Geographic information systems |
Spatial data infrastructures |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Spatial Interpolation for Climate Data; Table of Contents; Preface; Part 1. GIS to Manage and Distribute Climate Data; Chapter 1. GIS, Climatology and Meteorology; 1.1. GIS technology and spatial data (working group 1); 1.1.1. Introduction; 1.1.2. Weather and GIS; 1.1.3. Geographical data, environmental data and weather data; 1.1.4. A GIS approach to access weather data; 1.2. Data and metadata; 1.2.1. Introduction; 1.2.2. Important datasets; 1.2.3. Metadata; 1.2.4. Open Geospatial Consortium; 1.2.5. EU strategies for data handling and standards |
1.2.6. Meteorological datasets, important projects and programs1.2.7. Projects using Earth Observation satellites; 1.3. Interoperability; 1.3.1. |
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Introduction; 1.3.2. Technology for service-oriented architectures; 1.3.3. Interoperability in GIS; 1.3.4. Open Geospatial Consortium foundation ideas; 1.3.5. Standardized geospatial Web services; 1.3.6. GIS and AS interoperability potential: data model and formats; 1.3.7. Atmospheric data model; 1.3.8. Support from GIS for atmospheric data formats; 1.4. Conclusions; 1.5. Bibliography; Chapter 2. SIGMA: A Web-based GIS for Environmental Applications |
2.1. Introduction2.2. CPTEC-INPE; 2.3. SIGMA; 2.3.1. Basic functions; 2.4. Impacts of weather conditions on the economy; 2.5. Severe Weather Observation System (SOS); 2.5.1. Tracking of convective clouds; 2.5.2. Risk of lightning occurrence; 2.6. SOS interface; 2.7. Conclusions; 2.8. Acknowledgements; 2.9. Bibliography; Chapter 3. Web Mapping: Different Solutions using GIS; 3.1. Introduction; 3.2. Examples of Web mapping based on the usage of GIS technology in offline mode; 3.3. Examples of Web mapping using GIS tools in online mode; 3.4. Conclusion; 3.5. Bibliography |
Chapter 4. Comparison of Geostatistical and Meteorological Interpolation Methods (What is What?)4.1. Introduction; 4.2. Mathematical statistical model of spatial interpolation; 4.2.1. Statistical parameters; 4.2.2. Linear meteorological model for expected values; 4.2.3. Linear regression formula; 4.3. Geostatistical interpolation methods; 4.3.1. Ordinary kriging formula; 4.3.2. Universal kriging formula; 4.3.3. Modeling of unknown statistical parameters in geostatistics; 4.4. Meteorological interpolation; 4.4.1. Meteorological interpolation formula |
4.4.2. Possibility of modeling unknown statistical parameters in meteorology4.4.3. Difference between geostatistics and meteorology; 4.5. Software and connection of topics; 4.6. Example of the MISH application; 4.7. Bibliography; Chapter 5. Uncertainty from Spatial Sampling: A Case Study in the French Alps; 5.1. Introduction; 5.2. The sample as a whole; 5.3. Looking in detail where the sample is not representative; 5.4. Summarizing the sampling uncertainty; 5.4.1. 2D simplification; 5.4.2. 3D generalization; 5.4.3. Geographic homogenous sub-regions of the sample |
5.4.4. Interpolation of a climate parameter |
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Sommario/riassunto |
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This title gives an authoritative look at the use of Geographical Information Systems (GIS) in climatology and meterology. GIS provides a range of strategies, from traditional methods, such as those for hydromet database analysis and management, to new developing methods. As such, this book will provide a useful reference tool in this important aspect of climatology and meterology study. |
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