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Mapping and modeling weather and climate with GIS / / edited by L. Armstrong [and four others]
| Mapping and modeling weather and climate with GIS / / edited by L. Armstrong [and four others] |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Redlands, California : , : Esri Press, , 2015 |
| Descrizione fisica | 1 online resource (336 pages) : color illustrations |
| Disciplina | 551.60285 |
| Soggetto topico |
Climatology - Data processing
Meteorology - Data processing Geographic information systems |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-58948-405-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910463713403321 |
| Redlands, California : , : Esri Press, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Mapping and modeling weather and climate with GIS / / edited by L. Armstrong [and four others]
| Mapping and modeling weather and climate with GIS / / edited by L. Armstrong [and four others] |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Redlands, California : , : Esri Press, , 2015 |
| Descrizione fisica | 1 online resource (336 pages) : color illustrations |
| Disciplina | 551.60285 |
| Soggetto topico |
Climatology - Data processing
Meteorology - Data processing Geographic information systems |
| ISBN | 1-58948-405-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | pt. 1. Representations of atmospheric phenomena -- pt. 2. Observations -- pt. 3. Models -- pt. 4. Integrated analyses of models and observations -- pt. 5. Web services -- pt. 6. Tools and resources. |
| Record Nr. | UNINA-9910788028603321 |
| Redlands, California : , : Esri Press, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Mapping and modeling weather and climate with GIS / / edited by L. Armstrong [and four others]
| Mapping and modeling weather and climate with GIS / / edited by L. Armstrong [and four others] |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Redlands, California : , : Esri Press, , 2015 |
| Descrizione fisica | 1 online resource (336 pages) : color illustrations |
| Disciplina | 551.60285 |
| Soggetto topico |
Climatology - Data processing
Meteorology - Data processing Geographic information systems |
| ISBN | 1-58948-405-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | pt. 1. Representations of atmospheric phenomena -- pt. 2. Observations -- pt. 3. Models -- pt. 4. Integrated analyses of models and observations -- pt. 5. Web services -- pt. 6. Tools and resources. |
| Record Nr. | UNINA-9910816665803321 |
| Redlands, California : , : Esri Press, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Patterns identification and data mining in weather and climate / / Abdelwaheb Hannachi
| Patterns identification and data mining in weather and climate / / Abdelwaheb Hannachi |
| Autore | Hannachi Abdelwaheb |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XXIV, 600 p. 201 illus., 79 illus. in color.) |
| Disciplina | 551.60285 |
| Collana | Springer Atmospheric Sciences |
| Soggetto topico | Climatology - Data processing |
| ISBN | 3-030-67073-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1 Introduction -- Chapter 2 General Setting and Basic Terminology -- Chapter 3 Empirical Orthogonal Functions -- Chapter 4 Rotated and Simplified EOFs -- Chapter 5 Complex/Hilbert EOFs -- Chapter 6 Principal Oscillation Patterns and their extension -- Chapter 7 Extended EOFs and SSA -- Chapter 8 Persistent, Predictive, and Interpolated Patterns -- Chapter 9 Principal Coordinates or Multidimensional Scaling -- Chapter 10 Factor Analysis -- Chapter 11 Projection Pursuit -- Chapter 12 Independent Component Analysis -- Chapter 13 Kernel EOFs -- Chapter 14 Functional and Regularised EOFs -- Chapter 15 Methods for Coupled Patterns -- Chapter 16 Further topics -- Chapter 17 Machine Learning -- Appendix A Smoothing Techniques -- Appendix B Introduction to Probability and Random Variables.-Appendix C Stationary Time Series Analysis.-Appendix D Matrix Algebra and Matrix Function -- Appendix E Optimisation Algorithms -- Appendix F Hilbert Space -- Appendix G Systems of Linear Ordinary Differential Equations -- Appendix H Links for Software Resource Material -- Index. |
| Record Nr. | UNINA-9910484531203321 |
Hannachi Abdelwaheb
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| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Spatial interpolation for climate data [[electronic resource] ] : the use of GIS in climatology and meterology / / edited by Hartwig Dobesch, Pierre Dumolard, Izabela Dyras
| Spatial interpolation for climate data [[electronic resource] ] : the use of GIS in climatology and meterology / / edited by Hartwig Dobesch, Pierre Dumolard, Izabela Dyras |
| Pubbl/distr/stampa | London ; ; Newport Beach, CA, : ISTE, 2007 |
| Descrizione fisica | 1 online resource (304 p.) |
| Disciplina | 551.60285 |
| Altri autori (Persone) |
DobeschHartwig
DumolardPierre DyrasIzabela |
| Collana | Geographical information systems series |
| Soggetto topico |
Climatology - Data processing
Meteorology - Data processing Geospatial data - Mathematical models Geographic information systems Spatial data infrastructures |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-84783-2
9786610847839 0-470-39491-9 0-470-61226-6 1-84704-620-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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. 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 |
| Record Nr. | UNINA-9910144653903321 |
| London ; ; Newport Beach, CA, : ISTE, 2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Spatial interpolation for climate data [[electronic resource] ] : the use of GIS in climatology and meterology / / edited by Hartwig Dobesch, Pierre Dumolard, Izabela Dyras
| Spatial interpolation for climate data [[electronic resource] ] : the use of GIS in climatology and meterology / / edited by Hartwig Dobesch, Pierre Dumolard, Izabela Dyras |
| Pubbl/distr/stampa | London ; ; Newport Beach, CA, : ISTE, 2007 |
| Descrizione fisica | 1 online resource (304 p.) |
| Disciplina | 551.60285 |
| Altri autori (Persone) |
DobeschHartwig
DumolardPierre DyrasIzabela |
| Collana | Geographical information systems series |
| Soggetto topico |
Climatology - Data processing
Meteorology - Data processing Geospatial data - Mathematical models Geographic information systems Spatial data infrastructures |
| ISBN |
1-280-84783-2
9786610847839 0-470-39491-9 0-470-61226-6 1-84704-620-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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. 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 |
| Record Nr. | UNISA-996206952403316 |
| London ; ; Newport Beach, CA, : ISTE, 2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Spatial interpolation for climate data [[electronic resource] ] : the use of GIS in climatology and meterology / / edited by Hartwig Dobesch, Pierre Dumolard, Izabela Dyras
| Spatial interpolation for climate data [[electronic resource] ] : the use of GIS in climatology and meterology / / edited by Hartwig Dobesch, Pierre Dumolard, Izabela Dyras |
| Pubbl/distr/stampa | London ; ; Newport Beach, CA, : ISTE, 2007 |
| Descrizione fisica | 1 online resource (304 p.) |
| Disciplina | 551.60285 |
| Altri autori (Persone) |
DobeschHartwig
DumolardPierre DyrasIzabela |
| Collana | Geographical information systems series |
| Soggetto topico |
Climatology - Data processing
Meteorology - Data processing Geospatial data - Mathematical models Geographic information systems Spatial data infrastructures |
| ISBN |
1-280-84783-2
9786610847839 0-470-39491-9 0-470-61226-6 1-84704-620-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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. 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 |
| Record Nr. | UNINA-9910830606003321 |
| London ; ; Newport Beach, CA, : ISTE, 2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Spatial interpolation for climate data : the use of GIS in climatology and meterology / / edited by Hartwig Dobesch, Pierre Dumolard, Izabela Dyras
| Spatial interpolation for climate data : the use of GIS in climatology and meterology / / edited by Hartwig Dobesch, Pierre Dumolard, Izabela Dyras |
| Pubbl/distr/stampa | London ; ; Newport Beach, CA, : ISTE, 2007 |
| Descrizione fisica | 1 online resource (304 p.) |
| Disciplina | 551.60285 |
| Altri autori (Persone) |
DobeschHartwig
DumolardPierre DyrasIzabela |
| Collana | Geographical information systems series |
| Soggetto topico |
Climatology - Data processing
Meteorology - Data processing Geospatial data - Mathematical models Geographic information systems Spatial data infrastructures |
| ISBN |
1-280-84783-2
9786610847839 0-470-39491-9 0-470-61226-6 1-84704-620-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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. 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 |
| Record Nr. | UNINA-9911019957603321 |
| London ; ; Newport Beach, CA, : ISTE, 2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||