Quantitative Remote Sensing of Land Surfaces

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. Emphasizes both the basic principles of optical remote sensing and practical algorithms for estimating land surface variables quantitatively from remotely sensed observations Presents the current physical understanding of remote sensing as a system with a focus on radiative transfer modelling of the atmosphere, canopy, soil and snow Gathers the state of the art quantitative algorithms for sensor calibration, atmospheric and topographic correction, estimation of a variety of biophysical and geoph ysical variables, and four-dimensional data assimilation

Preface xv Acronyms xix Chapter 1 Introduction 1 Chapter 2 Atmospheric Shortwave Radiative Transfer Modeling 25 Chapter 3 Canopy Reflectance Modeling 76 Chapter 4 Soil and Snow Reflectance Modeling 143 Chapter 5 Satellite Sensor Radiometric Calibration 178 Chapter 6 Atmospheric Correction of Optical Imagery 196 Chapter 7 Topographic Correction Methods 231 Chapter 8 Estimation of Land Surface Biophysical variables 246 Chapter 9 Estimation of Surface Radiation Budget: I. Broadband Albedo 310 Chapter 10 Estimation of Surface Radiation Budget: II. Longwave 345 Chapter 11 Four-Dimensional Data Assimilation 398 Chapter 12 Validation and Spatial Scaling 431 Chapter 13 Applications 472 Appendix CD-ROM Content 525 Index 528