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Spatial modeling in GIS and R for earth and environmental sciences /
"Spatial Modeling in GIS and R for Earth and Environmental Sciences offers an integrated approach to spatial modelling using both GIS and R. Given the importance of Geographical Information Systems and geostatistics across a variety of applications in Earth and Environmental Science, a clear li...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Amsterdam, Netherlands :
Elsevier,
[2019]
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Front Cover; Spatial Modeling in GIS and R for Earth and Environmental Sciences; Copyright Page; Dedication; Contents; List of Contributors; 1 Spatial Analysis of Extreme Rainfall Values Based on Support Vector Machines Optimized by Genetic Algorithms: The Case of ... ; 1.1 Introduction; 1.2 The Study Area; 1.3 Methodology and Data; 1.4 Results; 1.5 Performance Criteria; 1.6 Discussion; 1.7 Conclusions; References; 2 Remotely Sensed Spatial and Temporal Variations of Vegetation Indices Subjected to Rainfall Amount and Distribution Prope ... ; 2.1 Introduction; 2.2 Materials and Methods
- 2.2.1 Study Area2.2.2 Data; 2.2.3 Vegetation Indices; 2.2.4 Rainfall Distribution Parameters; 2.3 Results and Discussion; 2.3.1 Vegetation Indices; 2.3.1.1 Normalized Difference Vegetation Index; 2.3.1.2 Spatial Variations of the Normalized Difference Vegetation Index; 2.3.1.3 Green Normalized Difference Vegetation Index; 2.3.1.4 Global Environmental Monitoring Index; 2.3.2 Spatial Normalized Differential Reflectance and Shortwave Crop Reflectance Index; 2.3.3 Rainfall Properties Versus Normalized Difference Vegetation Index, Green Normalized Difference Vegetation Index, Glob ...
- 2.3.3.1 Prespring Rainfall2.3.3.2 Cumulative Rainfall; 2.3.3.3 Rainfall Distribution; 2.4 Conclusion; References; Further Reading; 3 Numerical Recipes for Landslide Spatial Prediction Using R-INLA: A Step-by-Step Tutorial; 3.1 Introduction; 3.2 Dataset Description and Preparation; 3.2.1 Multiple Occurrence Regional Landslide Event, Messina, 2009; 3.2.2 Computing Slope Units in GIS; 3.3 Point Process Modeling and Estimation Using R-INLA; 3.3.1 Preprocessing; 3.3.2 Fitting a Cox Point Process Model Using R-INLA; 3.4 Results; 3.4.1 Estimated Fixed and Random Effects
- 3.4.2 Estimated Landslide Intensity at Various Spatial Resolutions3.4.3 Model Checking and Goodness-of-Fit Assessment; 3.4.4 Cross-Validation Study and Out-of-Sample Predictive Skill; 3.5 Discussion; 3.6 Conclusion; References; 4 Geospatial Multicriteria Decision Analysis in Forest Operational Planning; 4.1 Introduction; 4.1.1 Multicriteria Decision Elements; 4.1.1.1 Decision-Maker Analysis; 4.1.1.2 Hierarchical Structure; 4.1.1.3 Decision Elements; Criteria and Subcriteria; Decision Alternatives; 4.1.1.4 Interpretation Findings; 4.1.2 Classification of Spatial Decision Support System
- 4.1.2.1 Geostatistical Analysis With R packages4.1.2.2 Forest Management Hierarchy; Strategic Planning; Tactical Planning; Operational Planning; 4.1.3 A Perspective of Forest Resource Management in Iran; 4.1.3.1 General Information; 4.1.3.2 The Role of Decision Support Systems in Iranian Forestry; 4.2 Planning Problems; 4.3 Methods; 4.3.1 Multicriteria Decision Analysis; 4.3.2 Geostatistical Analysis; 4.3.3 Spatial Modeling Procedure; 4.3.4 Model Application; 4.4 Results; 4.4.1 The Current Conditions of the Terrain; 4.5 Discussion; 4.6 Conclusions; Acknowledgments; References; Further Reading