Details

Autor(en) / Beteiligte

• Liang, Shunlin

Titel

Quantitative remote sensing of land surfaces [electronic resource]

Link zum Volltext

• Wiley Online Library - AutoHoldings Books

Beschreibungen/Notizen

• Description based upon print version of record.
• Includes bibliographical references and index.
• QUANTITATIVE REMOTE SENSING OF LAND SURFACES; Contents; Preface; Acronyms; CHAPTER 1 Introduction; 1.1 Quantitative Models in Optical Remote Sensing; 1.2 Basic Concepts; 1.2.1 Digital Numbers; 1.2.2 Radiance; 1.2.3 Solid Angle; 1.2.4 lrradiance; 1.2.5 Bidirectional Reflectances and Albedos; 1.2.6 Extraterrestrial Solar lrradiance; 1.3 Remote Sensing Modeling System; 1.3.1 Scene Generation; 1.3.2 Scene Radiation Modeling; 1.3.3 Atmospheric Radiative Transfer Modeling; 1.3.4 Navigation Modeling; 1.3.5 Sensor Modeling; 1.3.5.1 Spectral Response; 1.3.5.2 Spatial Response
• 1.3.6 Mapping and Binning1.4 Summary; References; CHAPTER 2 Atmospheric Shortwave Radiative Transfer Modeling; 2.1 Radiative Transfer Equation .; 2.2 Surface Statistical BRDF Models; 2.2.1 Minnaert Function; 2.2.2 Lommel-Seeliger Function; 2.2.3 Walthall Function; 2.2.4 Staylor-Suttles Function; 2.2.5 Rahman Function; 2.2.6 Kernel Functions; 2.3 Atmospheric Optical Properties; 2.3.1 Rayleigh Scattering; 2.3.2 Mie Scattering; 2.3.3 Aerosol Particle Size Distributions; 2.3.4 Gas Absorption; 2.3.5 Aerosol Climatology; 2.4 Solving Radiative Transfer Equations; 2.4.1 Radiation Field Decomposition
• 2.4.2 Numerical Solutions2.4.2.1 Method of Successive Orders of Scattering; 2.4.2.2 Method of Discrete Ordinates; 2.4.3 Approximate Solutions: Two-Stream Algorithms; 2.4.4 Representative Radiative Transfer Solvers (Software Packages); 2.5 Approximate Representation for Incorporating Surface BRDF; 2.6 Summary; References; CHAPTER 3 Canopy Reflectance Modeling; 3.1 Canopy Radiative Transfer Formulation; 3.1.1 Canopy Configuration; 3.1.2 One-Dimensional Radiative Transfer Formulation; 3.1.3 Boundary Conditions; 3.1.4 Hotspot Effects; 3.1.5 Formulations for Heterogeneous Canopies
• 3.2 Leaf Optical Models3.2.1 "Plate" Models; 3.2.2 Needleleaf Models; 3.2.3 Ray Tracing Models; 3.2.4 Stochastic Models; 3.2.5 Turbid Medium Models; 3.3 Solving Radiative Transfer Equations; 3.3.1 Approximate Solutions; 3.3.1.1 Models Based on KM Theory; 3.3.1.2 Decomposition of the Canopy Radiation Field; 3.3.1.3 Approximation of Multiple Scattering; 3.3.2 Numerical Solutions: Gauss-Seidel Algorithm; 3.4 Geometric Optical Models; 3.5 Computer Simulation Models; 3.5.1 Monte Carlo Ray Tracing Models; 3.5.1.1 Forward and Reverse Ray Tracing; 3.5.1.2 Canopy Scene Generation
• 3.5.1.3 A Forest Ray Tracing Algorithm3.5.1.4 Botanical Plant Modeling System Model; 3.5.1.5 SPRINT Model; 3.5.2 Radiosity Models; 3.5.2.1 Generating the 3D Scene; 3.5.2.2 Calculating the Emission for All Surfaces in the Scene; 3.5.2.3 Computing the View Factors; 3.5.2.4 Solving the Radiosity Equation; 3.5.2.5 Rendering the Scene for a Given Viewpoint and Calculating BRF; 3.5.2.6 Applications; 3.6 Summary; References; CHAPTER 4 Soil and Snow Reflectance Modeling; 4.1 Single Scattering Properties of Snow and Soil; 4.1.1 Optical Properties of Snow; 4.1.2 Optical Properties of Soils
• 4.2 Multiple Scattering Solutions for Angular Reflectance from Snow and Soil
• Processing the vast amounts of data on the Earth's land surface environment generated by NASA's and other international satellite programs is a significant challenge. Filling a gap between the theoretical, physically-based modelling and specific applications, this in-depth study presents practical quantitative algorithms for estimating various land surface variables from remotely sensed observations.A concise review of the basic principles of optical remote sensing as well as practical algorithms for estimating land surface variables quantitatively from remotely sensed observations.Emp
• English