74
process and therefore limit the number of possible solutions. Indeed, two or
more different geophysical situations may lead to quite similar sets of
measurements for a given instrument, but the more complete the sampling,
the easier it is to distinguish between these geophysical situations (Gobron et
al. 1997 and Martonchik et al. 1998b).
3.
WHERE DO WE STAND, AND WHERE DO WE
GO FROM HERE?
Few instruments, if any, have been dedicated so far to the acquisition of
data relevant for LSP studies on a global basis. Existing sensors suffer from
significant drawbacks, including lack of reliable and accurate calibration,
low spatial resolution, and very poor or biased sampling. In addition, support
for the development of advanced algorithms has been quite limited, partly as
a result of the absence of appropriate sensors.
This situation is evolving quite rapidly, in response to both scientific and
technological developments. All major Space Agencies have invested sizable
resources to design and implement a new generation of Earth Observation
platforms and sensors (e.g., MERIS on the ESA ENVISAT, MODIS on the
NASA Terra, or GLI on the NASDA ADEOS-II platform.) Some of these
new sensors are partly or fully dedicated to the acquisition of data on the
state of the Earth surface, either at a medium spatial resolution but on a
global scale, or at a high spatial resolution for limited regions. The upcoming
availability of such advanced instruments has motivated significant
algorithmic developments. For instance, users of information on land
surfaces will soon have access to extensive documentation of environmental
variables such as albedo, Leaf Area Index (LAI), or the Fraction of
Absorbed Photosynthetically Active Radiation (FAPAR). These values will
ideally be accompanied by documented accuracy and reliability estimates,
directly from the ground segments set up by the Space Agencies or from
third party companies. This is in contrast with recent or even current
practices, when users were (are) provided with raw data or at best vegetation
index values, without clear indications as to their meaning or intrinsic
variability.
In the same vein, the acquisition of a more representative sample of the
angular and spectral signatures (including observations in the blue band, as
well as narrower and well-positioned bands in the red and near-infrared
regions) will lead to products of higher quality. This is because these new
sensors will be much less sensitive to atmospheric perturbations, for
instance. The multi-angular capability of advanced sensors such as MISR
and POLDER will further lead to improved products and services. Indeed,
Chapter 9
process and therefore limit the number of possible solutions. Indeed, two or
more different geophysical situations may lead to quite similar sets of
measurements for a given instrument, but the more complete the sampling,
the easier it is to distinguish between these geophysical situations (Gobron et
al. 1997 and Martonchik et al. 1998b).
3.
WHERE DO WE STAND, AND WHERE DO WE
GO FROM HERE?
Few instruments, if any, have been dedicated so far to the acquisition of
data relevant for LSP studies on a global basis. Existing sensors suffer from
significant drawbacks, including lack of reliable and accurate calibration,
low spatial resolution, and very poor or biased sampling. In addition, support
for the development of advanced algorithms has been quite limited, partly as
a result of the absence of appropriate sensors.
This situation is evolving quite rapidly, in response to both scientific and
technological developments. All major Space Agencies have invested sizable
resources to design and implement a new generation of Earth Observation
platforms and sensors (e.g., MERIS on the ESA ENVISAT, MODIS on the
NASA Terra, or GLI on the NASDA ADEOS-II platform.) Some of these
new sensors are partly or fully dedicated to the acquisition of data on the
state of the Earth surface, either at a medium spatial resolution but on a
global scale, or at a high spatial resolution for limited regions. The upcoming
availability of such advanced instruments has motivated significant
algorithmic developments. For instance, users of information on land
surfaces will soon have access to extensive documentation of environmental
variables such as albedo, Leaf Area Index (LAI), or the Fraction of
Absorbed Photosynthetically Active Radiation (FAPAR). These values will
ideally be accompanied by documented accuracy and reliability estimates,
directly from the ground segments set up by the Space Agencies or from
third party companies. This is in contrast with recent or even current
practices, when users were (are) provided with raw data or at best vegetation
index values, without clear indications as to their meaning or intrinsic
variability.
In the same vein, the acquisition of a more representative sample of the
angular and spectral signatures (including observations in the blue band, as
well as narrower and well-positioned bands in the red and near-infrared
regions) will lead to products of higher quality. This is because these new
sensors will be much less sensitive to atmospheric perturbations, for
instance. The multi-angular capability of advanced sensors such as MISR
and POLDER will further lead to improved products and services. Indeed,
Chapter 9