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Mesures physiques et signatures en télédétection

models require inputs that are specific to each species and canopy layer (e.g., LAI, spectral and dielectric
properties, canopy architecture). Also each model requires some representation of processes or properties
simulated by the others.
Modeling Framework
Although scientists from a wide range of disciplines have studied forested ecosystems, it has been difficult to
relate and contrast models of forested ecosystems from such disparate fields as biogeochemistry, ecophysiology,
land surface climatology, pedology, plant demography, remote sensing science, and soil physics. Integrated
approaches spanning more than two or three of these disciplines have proved unsatisfactory to specialists, yet
questions of how forested ecosystems respond to global change require integrated approaches. Our approach is to
develop the modeling tools and data to construct a virtual workbench or laboratory (Figure 2) for collaborative
modeling and testing ideas that cross disciplines, using the spatial context provided by data from remote sensing.
Key differences from previous integrated models stem from our efforts to keep critical elements accessible to
specialists in the various disciplines and from providing the type of graphical interface previously associated
with applied science and engineering models or teaching environments.
We encapsulate existing models to be more "object like" so they can collaborate in an object
oriented environment. (See Figure 2.) The environment supports a standard protocol for passing information
among models and for responding to interactive requests for information or graphical display of intermediate
results. Time is incremented by a single clock process, but models executing the same time step may run
concurrently. The user selects which models to use for a particular simulation, configures them, and may create
multiple instances of a single type of model. Models need not run on the same computer as the graphical
interface or other models. This extends the framework described by Levine et al. (1993) by allowing greater
flexibility in selecting which models participate in any single simulation and requiring fewer changes to the
simulation code of existing models. The combination of an assortment of encapsulated models, a common
graphical interface, and tools for scheduling and interprocess communication, establishes a framework for model
integration. Rather than building a single integrated model of a particular ecosystem, we plan to extend and
improve the framework as understanding improves and new data become available.
Our approach in the second phase of the FED Project has been to develop a modeling workbench that can link
individual submodels of forest physiology, growth and succession, soil processes, and the radiation regime
within and external to the forest-soil complex. These linked models are to be used in combination with groundbased,
groundbased, airborne and satellite observations, to better understand the dynamics of forest ecosystem evolution. By
the end of Phase II, we will be able to predict multi-spectral response (optical and microwave) from simulated
forest ecosystems for a variety of conditions, and as such, have a sensitive indicator of both direction and
magnitude of ecosystem change. The approach allows us to test hypotheses about process interactions, spatial
and temporal scaling, related to global change. This hypothesis testing occurs as we: (a) complete the logical
and functional integration of the various process sub-models using an object oriented approach; (b) analyze the
extensive ground-based, airborne, and satellite data sets which have been acquired in order to derive the products
that are needed as inputs to the models and are useful in improving our understanding of ecosystem processes;
and (c) rigorously validate both the sub-models and integrated models by comparing model-derived results with
ground-based and remote observations.
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