boring or even more distant locations can be as important
as the conditions at the location itself.
Land-use and land-cover change are the result of
many interacting processes. Each of these processes
operates over a range of scales in space and time. These
processes are driven by one or more of these variables
that influence the actions of the agents of land-use and
cover change involved. These variables are often referred
to as underlying driving forces which underpin
the proximate causes of land-use change, such as wood
extraction or agricultural expansion (Geist and Lambin
2001). These driving factors include demographic factors
(e.g., population pressure), economic factors (e.g.,
economic growth), technological factors, policy and
institutional factors, cultural factors, and biophysical
factors (Turner and others 1995, Kaimowitz and Angelsen
1998). These factors influence land-use change
in different ways. Some of these factors directly influence
the rate and quantity of land-use change, e.g. the
amount of forest cleared by new incoming migrants.
Other factors determine the location of land-use
change, e.g. the suitability of the soils for agricultural
land use. Especially the biophysical factors do pose
constraints to land-use change at certain locations,
leading to spatially differentiated pathways of change. It
is not possible to classify all factors in groups that either
influence the rate or location of land-use change. In
some cases the same driving factor has both an influence
on the quantity of land-use change as well as on
the location of land-use change. Population pressure is
often an important driving factor of land-use conversions
(Rudel and Roper 1997). At the same time it is the
relative population pressure that determines which
land-use changes are taking place at a certain location.
Intensively cultivated arable lands are commonly situated
at a limited distance from the villages while more
extensively managed grasslands are often found at a
larger distance from population concentrations, a relation
that can be explained by labor intensity, transport
costs, and the quality of the products (Von Thu¨nen
1966). The determination of the driving factors of land
use changes is often problematic and an issue of discussion
(Lambin and others 2001). There is no unifying
theory that includes all processes relevant to landuse
change. Reviews of case studies show that it is not
possible to simply relate land-use change to population
growth, poverty, and infrastructure. Rather, the interplay
of several proximate as well as underlying factors
drive land-use change in a synergetic way with large
variations caused by location specific conditions
(Lambin and others 2001, Geist and Lambin 2001). In
regional modeling we often need to rely on poor data
describing this complexity. Instead of using the underlying
driving factors it is needed to use proximate variables
that can represent the underlying driving factors.
Especially for factors that are important in determining
the location of change it is essential that the factor can
be mapped quantitatively, representing its spatial variation.
The causality between the underlying driving
factors and the (proximate) factors used in modeling
(in this paper, also