PREFACE
XVii
radiometric calibration and various postlaunch vicarious calibration methods.
The calibration coefficients for land remote sensing satellite thematic map-
ping (Landsat TM) and National Oceanic and Atmospheric Administration
advanced very high-resolution radiometer (NOAA AVHRR) data are pro-
vided for easy reference. Chapter
6
presents the basic principles and practical
methods of atmospheric correction that convert top-of-atmosphere (TOA)
radiance to surface reflectance. It focuses mainly on estimating aerosol
optical properties from single-viewing remotely sensed data, but multiangle
imaging spectroradiometric
(MISR)
aerosol estimation methods representing
multiangular remote sensing and those for estimating total column water
vapor content of the atmosphere are also discussed. Chapter
7
discusses
various topographic correction algorithms that remove the disturbance caused
by the variable land surface topography. The current status of digital eleva-
tion model (DEM) data is also evaluated. Chapter
8
presents various meth-
ods for estimating land surface variables, such
as
leaf area index, fraction
of
the photosynthetically active radiation (FAPAR) absorbed by vegetation
canopies, the fraction of vegetation coverage, and biochemical concentra-
tions. Statistical algorithms (based mainly
on
vegetation indices from multi-
spectral and hyperspectral remotely sensed data) and physical inversion
methods (based mainly on process models introduced in the first few chap-
ters of the book) are presented.
Chapters
9
and 10 discuss various methods for estimating land surface
radiation budget components, such
as
broadband albedo, broadband emissiv-
ity, and skin temperature.
In
calculating broadband albedo, we focus mainly
on
the conversion algorithms from narrowband to broadband. In estimating
skin temperature, split-window algorithms
as well
as
other temperature and
emissivity separation algorithms are presented. Chapter
1
1
presents four-di-
mensional data assimilation algorithms and applications. This
is
a quantita-
tive, objective method for inferring the state of the dynamic system from
heterogeneous, irregularly distributed, and temporally inconsistent observa-
tional data with differing accuracies. One unique feature is the ability to
estimate environmental variables that are not related to any remotely sensed
radiometric quantities. The basic principles and the typical algorithms are
introduced, and the applications to hydrology and crop growth are demon-
strated. Chapter
12
discusses the validation of the estimated land surface
variables and various methods of spatial scaling. Since land surface variables
drive various models related to land surface processes, the accuracy of the
remotely sensed products will largely affect the model outputs and the final
conclusions. The validation rationale, NASA
EOS
validation programs, and
some validation methodologies are presented. Because of its importance in
remote sensing besides validation, spatial scaling is presented separately. The
emphasis is on downscaling methods, including linear unmixing, generating
continuous fields, decomposition of normalized difference vegetative index
(NDVI) temporal profiles, multiresolution data fusion, and statistical down-
scaling global
(or
general) circulation model
(GCM)
outputs.