Sensitivity Analysis in Earth Observation Modelling

Sensitivity Analysis in Earth Observation Modelling

By: George P. Petropoulos (editor), Prashant K. Srivastava (editor)Paperback

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Sensitivity Analysis in Earth Observation Modeling highlights the state-of-the-art in ongoing research investigations and new applications of sensitivity analysis in earth observation modeling. In this framework, original works concerned with the development or exploitation of diverse methods applied to different types of earth observation data or earth observation-based modeling approaches are included. An overview of sensitivity analysis methods and principles is provided first, followed by examples of applications and case studies of different sensitivity/uncertainty analysis implementation methods, covering the full spectrum of sensitivity analysis techniques, including operational products. Finally, the book outlines challenges and future prospects for implementation in earth observation modeling. Information provided in this book is of practical value to readers looking to understand the principles of sensitivity analysis in earth observation modeling, the level of scientific maturity in the field, and where the main limitations or challenges are in terms of improving our ability to implement such approaches in a wide range of applications. Readers will also be informed on the implementation of sensitivity/uncertainty analysis on operational products available at present, on global and continental scales. All of this information is vital in the selection process of the most appropriate sensitivity analysis method to implement.

About Author

Dr. Petropoulos' research work focuses on exploiting Earth Observation (EO) data alone or synergistically with land surface process models in deriving regional estimates of key state variables of the Earth's energy and water budget, including energy fluxes and soil surface moisture. He is also conducting research on the use of remote sensing technology in obtaining information about the land cover and if changes occurred from either anthropogenic activities (e.g. urbanization, mining activity) or natural hazards (mainly floods and fires). In this framework, he is researching and optimizing new image processing techniques to recently launched EO satellites, with a large part of his work focusing on the development and enhancement of EO-based operational products. As part of this research he is also conducting all-inclusive benchmarking studies to EO products or land surface models, including advanced sensitivity analysis techniques. Dr. Srivastava is working in Hydrological Sciences, NASA Goddard Space Flight Center on SMAP satellite soil moisture retrieval algorithm development, instrumentation and simulation for various applications, and affiliated with IESD, Banaras Hindu University as a faculty. He received his PhD degree from Department of Civil Engineering, University of Bristol, Bristol, UK. He has published 100+ papers in peer-reviewed journals, published 4 books with reputed publishing houses and authored several book chapters and conference papers.


Section I: Introduction to SA in Earth Observation (EO) 1. Overview of Sensitivity Analysis Methods in Earth Observation Modeling L. Lee, P.K. Srivastava, G.P. Petropoulos 2. Model Input Data Uncertainty and its Potential Impact on Soil Properties T. Mannschatz, P. Dietrich Section II : Local SA Methods: Case Studies 3. Local Sensitivity Analysis of the LandSoil Erosion Model Applied to a Virtual Catchment R. Caimpalini, S. Follain, B. Cheviron, Y. Le Bissonnais, A. Couturier 4. Sensitivity of Vegetation Phenological Parameters from Satellite Sensors to Spatial Resolution and Temporal Compositing Period G.L. Mountford, P.M. Atkinson, J. Dash, T. Lankester, S. Hubbard 5. Radar Rainfall Sensitivity Analysis Using Multivariate Distributed Ensemble Generator Q. Dai, D. Han, P.K. Srivastava 6. Field-Scale Sensitivity of Vegetation Discrimination to Hyperspectral Reflectance and Coupled Statistics K. Manevski, M. Jabloun, M. Gupta, C. Kalaitzidis Section III: Global (or Variance)-Based SA Methods: Case Studies 7. A Multimethod Global Sensitivity Analysis Approach to Support the Calibration and Evaluation of Land Surface Models F. Pianosi, J. Iwema, R. Rosolem, T. Wagener 8. Global Sensitivity Analysis for Supporting History Matching of Geomechanical Reservoir Models Using Satellite InSAR Data: A Case Study at the CO2 Storage Site of In Salah, Algeria J. Rohmer, A. Loschetter, D. Raucoules 9. Artificial Neural Networks for Spectral Sensitivity Analysis to Optimize Inversion Algorithms for Satellite-Based Earth Observation: Sulfate Aerosol Observations with High-Resolution Thermal Infrared Sounders P. Sellitto 10. Global Sensitivity Analysis for Uncertain Parameters, Models, and Scenarios M. Ye, M.C. Hill Section IV: Other SA Methods: Case Studies 11. Sensitivity and Uncertainty Analyses for Stochastic Flood Hazard Simulation Z. Micovic, M.G. Schaefer, B.L. Barker 12. Sensitivity of Wells in a Large Groundwater Monitoring Newtork and Its Evaluation Using GRACE Satellite Derived Information V. Uddameri, A. Karim, E.A. Hernandez, P.K. Srivastava 13. Making the Most of the Earth Observation Data Using Effective Sampling Techniques J. Indu, D. Nagesh Kumar 14. Ensemble-Based Multivariate Sensitivity Analysis of Satellite Rainfall Estimates Using Copula Model S. Moazami, S. Golian Section V: Software Tools in SA for EO 15. Efficient Tools for Global Sensitivity Analysis Based on High-Dimensional Model Representation T. Ziehn, A.S. Tomlin 16. A Global Sensitivity Analysis Toolbox to Quantify Drivers of Vegetation Radiative Transfer Models J. Verrelst, J.P. Rivera 17. GEM-SA: The Gaussian Emulation Machine for Sensitivity Analysis M.C. Kennedy, G.P. Petropoulos 18. An Introduction to The SAFE Matlab Toolbox with Practical Examples and Guidelines F. Sarrazin, F. Pianosi, T. Wagener Section VI: Challenges and Future Outlook 19. Sensitivity in Ecological Modeling: From Local to Regional Scales X. Song, B.A. Bryan, L. Gao, G. Zhao, M. Dong 20. Challenges and Future Outlook of Sensitivity Analysis H. Gupta, S. Razavi

Product Details

  • ISBN13: 9780128030110
  • Format: Paperback
  • Number Of Pages: 448
  • ID: 9780128030110
  • weight: 910
  • ISBN10: 0128030119

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