292
Chapter 29
sensing measurements or to their relationships with surface or processes’
parameters. It must be envisaged that the evolution of the mission
specifications will have to take into account results of such studies to
provide improved characterization of the biosphere state and dynamics.
2.
MISSION OBJECTIVES
2.1
Surface parameters mapping
This is the basic requirement, especially for climate and meteorological
studies where boundary conditions have to be prescribed as in the case of
General Circulation Models or forecasting models. Factors such as albedo,
surface roughness, or resistances to heat exchanges (sensible and latent) are
important variables for these models, and they can be either determined
directly from the measurements or inferred from identification of land cover.
The seasonal and long-term variations of such variables are related to
vegetation dynamics. The capability to identify, through these variations,
physical characteristics of land cover is a key to accurate prescription of
these variables. Scales addressed in GCM or forecasting models (typically
about 100 km) require that land cover and its variability must be determined
with a sampling of about 8 to 10 km: the basic spatial resolution needed for
identification of land cover and its variability is 1 km.
2.2
Agricultural, pastoral and forest production
Since the beginning of the land surface satellite remote sensing era
(1972), important projects (for example, LACIE, AGRISTARS for USDA,
MARS for CEC, TREES for JRC/ESA) have been set up to develop
methodologies and strategies to use remote sensing data either for mapping
of land use in anthropogenized or natural ecosystems, or for estimation of
production potential. Their specific objective was to determine the evolution
of productions. This objective had to be adapted to the management of crop
production for agricultural exporting countries, to the monitoring of pastoral
resources and their dependence from meteorological evolution, to the
evaluation of possible global impacts of deforestation and more generally to
the need for information related to political or social orientations and
decisions.
Chapter 29
sensing measurements or to their relationships with surface or processes’
parameters. It must be envisaged that the evolution of the mission
specifications will have to take into account results of such studies to
provide improved characterization of the biosphere state and dynamics.
2.
MISSION OBJECTIVES
2.1
Surface parameters mapping
This is the basic requirement, especially for climate and meteorological
studies where boundary conditions have to be prescribed as in the case of
General Circulation Models or forecasting models. Factors such as albedo,
surface roughness, or resistances to heat exchanges (sensible and latent) are
important variables for these models, and they can be either determined
directly from the measurements or inferred from identification of land cover.
The seasonal and long-term variations of such variables are related to
vegetation dynamics. The capability to identify, through these variations,
physical characteristics of land cover is a key to accurate prescription of
these variables. Scales addressed in GCM or forecasting models (typically
about 100 km) require that land cover and its variability must be determined
with a sampling of about 8 to 10 km: the basic spatial resolution needed for
identification of land cover and its variability is 1 km.
2.2
Agricultural, pastoral and forest production
Since the beginning of the land surface satellite remote sensing era
(1972), important projects (for example, LACIE, AGRISTARS for USDA,
MARS for CEC, TREES for JRC/ESA) have been set up to develop
methodologies and strategies to use remote sensing data either for mapping
of land use in anthropogenized or natural ecosystems, or for estimation of
production potential. Their specific objective was to determine the evolution
of productions. This objective had to be adapted to the management of crop
production for agricultural exporting countries, to the monitoring of pastoral
resources and their dependence from meteorological evolution, to the
evaluation of possible global impacts of deforestation and more generally to
the need for information related to political or social orientations and
decisions.