100
Chapter 11
Amazonia (LBA; Nobre et al., 1996). This example also shows the process
of transition from the classical mesoscale LSEs towards larger scales in
space and time (see Section 5).
The Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA)
is an international research initiative lead by Brazil. LBA is designed to
create the new knowledge needed to understand the climatological,
ecological, biogeochemical, and hydrological functioning of Amazonia, the
impact of land use changes on these functions, and the interactions between
Amazonia and the Earth system. LBA is centered around two key questions
that will be addressed through multi-disciplinary research, integrating studies
in the physical, chemical, biological, and human sciences:
How does Amazonia currently function as a regional entity?
How will changes in land use and climate affect the biological, chemical
and physical functions of Amazonia, including the sustainability of
development in the region and the influence of Amazonia on global
climate?
Remote sensing contributes to these goals in several important ways. One
of the key issues still is the proper and timely delineation of the spatial
extent and function of ecosystems with significant impact on the water,
carbon and nutrient exchange processes. The most obvious in this context
are flooded forest areas (methane and water budget) and re-growth stages
(carbon, biomass). Equally important, but much less studied, are selectively
logged areas and forests with apparently homogeneous closed canopy top
surfaces but exhibiting significant differences in biophysical function.
Improved fine-scale classification of these biophysical and hydrological
properties (and thus the possibility of its quantification) will provide crucial
information for the understanding of the Amazonian ecosystems.
Remote sensing data are also needed to integrate information and
processes pertinent to ecosystem-atmosphere exchanges of carbon, trace
gases, water, and energy across a broad range of geographic scales. Links
between remote sensing data and key variables and parameters of
atmosphere and land surface can thus be established and validated at local
scales, where extensive ground observations are practical. A combination of
remote sensing, mesoscale modeling and other spatial integration techniques
will permit an extension of this knowledge to other geographic scales.
Furthermore satellite data have the stability needed for long-term
monitoring of these variables at a wide range of temporal frequencies. This
temporal and spatial scope of satellite data provides a unique tool that can be
used to study the dynamics of vegetation communities (disturbance,
succession, fire, etc.) over a wide range of scales.
Remote sensing also helps to place the intensive study sites in their
correct ecoclimatological and geographic context, by providing basin-wide
Chapter 11
Amazonia (LBA; Nobre et al., 1996). This example also shows the process
of transition from the classical mesoscale LSEs towards larger scales in
space and time (see Section 5).
The Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA)
is an international research initiative lead by Brazil. LBA is designed to
create the new knowledge needed to understand the climatological,
ecological, biogeochemical, and hydrological functioning of Amazonia, the
impact of land use changes on these functions, and the interactions between
Amazonia and the Earth system. LBA is centered around two key questions
that will be addressed through multi-disciplinary research, integrating studies
in the physical, chemical, biological, and human sciences:
How does Amazonia currently function as a regional entity?
How will changes in land use and climate affect the biological, chemical
and physical functions of Amazonia, including the sustainability of
development in the region and the influence of Amazonia on global
climate?
Remote sensing contributes to these goals in several important ways. One
of the key issues still is the proper and timely delineation of the spatial
extent and function of ecosystems with significant impact on the water,
carbon and nutrient exchange processes. The most obvious in this context
are flooded forest areas (methane and water budget) and re-growth stages
(carbon, biomass). Equally important, but much less studied, are selectively
logged areas and forests with apparently homogeneous closed canopy top
surfaces but exhibiting significant differences in biophysical function.
Improved fine-scale classification of these biophysical and hydrological
properties (and thus the possibility of its quantification) will provide crucial
information for the understanding of the Amazonian ecosystems.
Remote sensing data are also needed to integrate information and
processes pertinent to ecosystem-atmosphere exchanges of carbon, trace
gases, water, and energy across a broad range of geographic scales. Links
between remote sensing data and key variables and parameters of
atmosphere and land surface can thus be established and validated at local
scales, where extensive ground observations are practical. A combination of
remote sensing, mesoscale modeling and other spatial integration techniques
will permit an extension of this knowledge to other geographic scales.
Furthermore satellite data have the stability needed for long-term
monitoring of these variables at a wide range of temporal frequencies. This
temporal and spatial scope of satellite data provides a unique tool that can be
used to study the dynamics of vegetation communities (disturbance,
succession, fire, etc.) over a wide range of scales.
Remote sensing also helps to place the intensive study sites in their
correct ecoclimatological and geographic context, by providing basin-wide