Spatial modeling of landscape processes
Important
for:
-
analysis
and prediction of landscape processes
-
decision
support in land management
Modeling
progress:
-
empirical
---> process based
-
spatially
averaged ---> distributed
-
static
---> dynamic
Challenges:
-
data
intensive - large heterogeneous data sets
-
complex
spatial interactions and multiscale effects
-
high
level of uncertainty and difficult validation
