Note: Front Cover -- Bio-optical Modeling and Remote Sensing of Inland Waters -- Copyright Page -- Contents -- List of Contributors -- Abbreviations and Notations -- Abbreviations -- Notations -- 1 Remote Sensing of Inland Waters: Background and Current State-of-the-Art -- 1.1 Inland Waters -- 1.2 Remote Sensing of Inland Waters -- 1.3 Fundamental Bio-Optical Properties -- 1.4 Bio-Optical Models -- 1.4.1 Classification of Bio-optical Models -- 1.4.2 Performance of Bio-optical Models -- 1.5 Book Content -- References -- 2 Radiative Transfer Theory for Inland Waters -- 2.1 Introduction -- 2.2 Basic Principles -- 2.2.1 Interaction of Light with Matter -- 2.2.2 Radiometric Quantities -- 2.2.3 Radiative Transfer Equation -- 2.2.4 Inherent Optical Properties -- 2.2.5 From Microscopic to Macroscopic Material Parameters -- 2.3 Bio-Optical Models -- 2.3.1 Water Composition -- 2.3.1.1 Phytoplankton -- 2.3.1.2 CDOM -- 2.3.1.3 Total Suspended Matter -- 2.3.2 Apparent Optical Properties -- 2.3.3 AOP Models -- 2.4 Light Field Models -- 2.4.1 Incident Radiation -- 2.4.2 Water Surface Effects -- 2.4.3 Underwater Light Field -- 2.4.4 Fluorescence -- 2.4.5 Polarization -- 2.5 Conclusions -- Acknowledgments -- References -- 3 Atmospheric Correction for Inland Waters -- 3.1 Introduction -- 3.2 Challenges -- 3.2.1 Challenges Due to Physical and Bio-optical Properties -- 3.2.1.1 High Turbidity and Floating Objects -- 3.2.1.2 Adjacency Effect -- 3.2.2 Challenges Due to Difficulties in Atmospheric Modeling -- 3.2.2.1 Optical Heterogeneity Due to Terrestrial Influence -- 3.2.2.2 Breakdown of Basic Assumptions -- 3.3 Existing Algorithms -- 3.3.1 Atmospheric Correction Algorithms -- 3.3.1.1 Algorithms Deriving Aerosol Information from Clear Water Pixels in the Image, Assuming Spatial Homogeneity. , 3.3.1.2 Algorithms Based on Extending the "Black-Pixel" Approach to the SWIR Region -- 3.3.1.3 Algorithms Based on Spatial Extension of Aerosol Information Retrieved from Nearby Land -- 3.3.1.4 Simultaneous Retrieval of Atmospheric and Water Components -- 3.3.1.5 Image-Based Algorithms -- 3.3.2 Adjacency Correction Algorithms -- 3.3.3 Case Study: Combined Atmospheric and Adjacency Correction -- 3.4 Conclusion -- Acknowledgments -- References -- 4 Bio-optical Modeling of Colored Dissolved Organic Matter -- 4.1 Carbon in Inland Waters -- 4.2 Optical Properties of CDOM -- 4.3 Remote Sensing of CDOM -- 4.4 CDOM Retrieval With Bio-Optical Models -- 4.5 Final Considerations -- References -- 5 Bio-optical Modeling of Total Suspended Solids -- 5.1 Introduction -- 5.2 Optical Properties of Particles -- 5.2.1 Relationship between IOPs and TSS -- 5.2.2 Remote Sensing Algorithms for TSS -- 5.3 Case Studies -- 5.3.1 MERIS Time-Series-Lake Garda -- 5.3.2 Airborne Imaging Spectrometry-Mantua Lakes -- 5.3.3 Multitemporal OLI Data-Po River -- 5.4 Conclusions -- Acknowledgments -- References -- Further Reading -- 6 Bio-optical Modeling of Phytoplankton Chlorophyll-a -- 6.1 Introduction -- 6.2 Chlorophyll-a: The Fundamental Measure of Phytoplankton Biomass and Production -- 6.3 Optical Pathways to Estimate Phytoplankton Chlorophyll-a -- 6.3.1 Phytoplankton Absorption -- 6.3.2 Phytoplankton Fluorescence -- 6.3.3 Phytoplankton Scattering -- 6.4 Conclusion -- Acknowledgments -- References -- 7 Bio-optical Modeling of Sun-Induced Chlorophyll-a Fluorescence -- 7.1 Introduction, BASIC Concepts, and Current Knowledge -- 7.2 Modeling of Reflectance Spectra with Fluorescence -- 7.2.1 Remote Sensing Reflectance -- 7.2.2 Elastic Reflectance -- 7.2.3 Fluorescence Reflectance -- 7.2.4 Inherent Optical Properties and Attenuation Coefficients -- 7.2.4.1 Absorption Coefficient. , 7.2.4.2 Scattering and Backscattering Coefficients -- 7.2.4.3 Diffuse and Radiance Attenuation Coefficients -- 7.3 Relationships Between the Fluorescence Magnitude and the Concentrations of Chlorophyll and Other Water Constituents -- 7.3.1 Simplified Fluorescence Model-Theoretical Considerations -- 7.3.2 Simplified Fluorescence Model-Comparison with Field Measurements -- 7.4 Retrieval of the Fluorescence Component from Reflectance Spectra -- 7.4.1 Combined Retrieval of the Fluorescence and Water Constituents -- 7.4.2 Fluorescence Line Height Algorithms and Their Limitations -- 7.4.3 Performance of Fluorescence Algorithms with Satellite Data -- 7.4.4 Retrieval of the Fluorescence Component from Polarimetric Hyperspectral Observations -- 7.4.5 Application of SICF to the Detection of Algal Blooms -- 7.5 Summary -- Acknowledgments -- References -- 8 Bio-optical Modeling of Phycocyanin -- 8.1 Introduction -- 8.2 Theoretical basis for remote sensing of phycocyanin -- 8.3 Literature review of remote sensing algorithms of phycocyanin -- 8.3.1 Empirical Algorithms -- 8.3.2 Semi-empirical Algorithms -- 8.3.3 Semi-analytical Algorithms -- 8.4 Evaluation of Representative Algorithms Using a Large Field Dataset -- 8.4.1 Description of the Field Dataset -- 8.4.2 Evaluation of the Estimation Accuracy -- 8.4.3 Evaluation of a Band Ratio Algorithm -- 8.4.4 Evaluation of Semi-analytical Models -- 8.4.5 Evaluation of Two Baseline Algorithms Using AOP and IOP -- 8.4.6 Discussion of Factors Influencing the Remote Estimation of Phycocyanin -- 8.5 Mapping PC Using Airborne Images -- 8.6 Summary and Future Work -- Acknowledgements -- References -- 9 Bio-optical Modeling and Remote Sensing of Aquatic Macrophytes -- 9.1 Introduction -- 9.2 Spectral Characteristics of Aquatic Macrophytes -- 9.3 Application of Remote Sensing Systems -- 9.4 Discrimination and Classification. , 9.5 Determination of Macrophyte Biophysical Properties -- 9.5.1 Use of Indices -- 9.6 Bio-Optical Modeling of Aquatic Macrophytes -- 9.7 Discussion and Priorities for Further Research -- 9.7.1 In Situ Measurement of Spectral Signatures -- 9.7.2 Signature Analysis -- 9.7.3 Bio-optical Modeling -- 9.7.4 Relationships with Biophysical Properties -- 9.7.5 Inversion Algorithms -- 9.7.6 Assessment of Remote Sensing Platforms -- 9.7.7 Regional Assessment/Global Monitoring -- 9.7.8 Role in Management -- References -- Index -- Back Cover.