Sensitivity Analysis in Earth Observation Modelling

Dr. George P. Petropoulos is Assistant Professor in Geoinformatics at the Department of Geography, Harokopio University of Athens Greece. His research focuses on the exploitation of geoinformation technology & geospatial data analysis techniques in geographical and environmental applications. He is author/co-author of over 110 articles, 40 book chapters, and has edited 6 books. He has developed collaborations with key scientists in his area of specialisation globally and his research & teaching work has received international recognition via several significant awards and research funding. Prashant K. Srivastava obtained his PhD from the Department of Civil Engineering at the University of Bristol in Bristol, UK, and currently serves on the faculty at the Institute of Environment and Sustainable Development at Banaras Hindu University in Varanasi, India. He formerly worked in the Hydrological Sciences Department at the NASA Goddard Space Flight Center and is currently an investigator for several national and international projects. He has published 100+ papers, many books, and several book chapters. He is also acting as an editorial board member of several reputed journals.

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