Petropoulos, George P. Srivastava, Prashant K. text Electronic books. ne Amsterdam, Netherlands Elsevier 2016 monographic eng

electronic resource

1 online resource (448) Front Cover; Sensitivity Analysis in Earth Observation Modelling; Sensitivity Analysis in Earth Observation Modelling; Copyright; Dedication; Contents; List of Contributors; Preface; ABOUT THE COVER; 1 -- INTRODUCTION TO SA IN EARTH OBSERVATION (EO); 1 -- OVERVIEW OF SENSITIVITY ANALYSIS METHODS IN EARTH OBSERVATION MODELING; 1. INTRODUCTION; 1.1 DEFINING THE MODEL OUTPUTS AND INPUTS FOR SENSITIVITY ANALYSIS; 1.1.1 Defining Factor (or Parametric) Uncertainty; 2. LOCAL SENSITIVITY ANALYSIS; 2.1 CORRELATION ANALYSIS; 2.2 REGRESSION ANALYSIS; 3. GLOBAL SENSITIVITY ANALYSIS. 3.1 ONE-AT-A-TIME SENSITIVITY ANALYSIS METHODS3.2 THE MORRIS METHOD FOR FACTOR SCREENING; 3.3 VARIANCE-BASED SENSITIVITY ANALYSIS; 3.4 SAMPLING METHODS FOR GLOBAL SENSITIVITY ANALYSIS; 3.4.1 Random Sampling; 3.4.2 Stratified Sampling and the Latin Hypercube; 3.4.3 Sampling for Sensitivity Indices; 3.5 SURROGATE MODELS FOR GLOBAL SENSITIVITY ANALYSIS; 3.5.1 Generalized Linear Modeling; 3.5.2 Neural Networks; 3.5.3 Direct Sensitivity Analysis of Surrogate Models; 3.6 POLYNOMIAL CHAOS; 3.7 GAUSSIAN PROCESS AND BAYES LINEAR EMULATION; 4. GRAPHICAL METHODS FOR GLOBAL SENSITIVITY ANALYSIS. 4.1 SCATTER PLOTS4.2 PLOTTING THE RESPONSE SURFACE; 4.3 PLOTTING THE SENSITIVITY INDICES; 5. CONCLUSIONS; REFERENCES; 2 -- MODEL INPUT DATA UNCERTAINTY AND ITS POTENTIAL IMPACT ON SOIL PROPERTIES; 1. INTRODUCTION; 2. A WORLD OF MODELS -- HOW CAN THEY BE CLASSIFIED?; 3. CAN WE TRUST MODELS? -- MODEL ACCURACY AND THEIR SENSITIVITY TO INPUT DATA UNCERTAINTY; 4. SELECTING THE MOST APPROPRIATE MODEL; 5. WHY AND HOW TO ACCOUNT FOR MODELING UNCERTAINTIES CAUSED BY DIFFERENT INPUT DATA SOURCES; 6. ASSESSING SENSITIVITY OF ENVIRONMENTAL MODELS. 7. HOW SOIL TEXTURE MEASURED WITH VISIBLE-NEAR-INFRARED SPECTROSCOPY AFFECTS HYDROLOGICAL MODELING: A CASE STUDY7.1 STUDY SITES AND INSTRUMENTS; 7.2 SOIL SAMPLES; 7.3 CHEMOMETRICS; 7.4 IMPACT OF CHEMOMETRIC METHOD ON SOIL PREDICTION; 7.5 DIFFERENT INSTRUMENTS, DIFFERENT SOIL PREDICTIONS? WHAT WAS FINALLY THE BEST SOIL PREDICTION ACCURACY?; 7.6 WHAT DOES THIS FINALLY MEAN FOR OUR ENVIRONMENTAL MODELING?; 8. WHAT DID WE LEARN?; REFERENCES; 2 -- LOCAL SA METHODS: CASE STUDIES; 3 -- LOCAL SENSITIVITY ANALYSIS OF THE LANDSOIL EROSION MODEL APPLIED TO A VIRTUAL CATCHMENT; 1. INTRODUCTION. 2. MATERIALS AND METHODS2.1 MODEL DESCRIPTION; 2.2 SENSITIVITY ANALYSIS; 2.2.1 Parameters; 2.2.2 Virtual Catchment; 2.2.3 Sensitivity Calculation; 3. RESULTS AND DISCUSSION; 3.1 LINEAR HILLSLOPE; 3.1.1 Aggregated Parameters; 3.2 COMPLEX HILLSLOPES; 4. CONCLUDING REMARKS; Acknowledgments; REFERENCES; 4 -- SENSITIVITY OF VEGETATION PHENOLOGICAL PARAMETERS: FROM SATELLITE SENSORS TO SPATIAL RESOLUTION AND TEMPORAL CO ... ; 1. INTRODUCTION; 2. MONITORING VEGETATION PHENOLOGY; 3. SENSITIVITY ANALYSIS; 4. SENSITIVITY OF REMOTELY SENSED PHENOLOGICAL PARAMETERS; 4.1 SATELLITE SENSOR. edited by George F. Petropoulous, Prashant K. Srivastava. Earth sciences Remote sensing Earth sciences Remote sensing QE33.2.R4 550.285 Amsterdam, Netherlands : Elsevier, 2016 (OCoLC)949749831 9780128030318 0128030313 http://www.sciencedirect.com/science/book/9780128030110 http://www.sciencedirect.com/science/book/9780128030110 IDEBK 161014 20190328114817.0 ocn960719028 eng