Land de
mand is driven by an increasing population and changing consu
mption patterns. When land is required Land Use Changes (LUC) are triggered, causing several environ
mental and social i
mpacts. Particularly topical is the assess
ment of indirect LUC effects. Several
methodological approaches have been proposed for carrying out the assess
ment. In this paper we classified LUC
models for Life Cycle Assess
ment (LCA) applications into three
main categories: Econo
mic, Causal–Descriptive and Nor
mative
models. Six
models were selected as representative of these three categories and co
mpared according to fifteen criteria covering:
modeling fra
mework, i
mpact categories assessed and
model transparency. The results show that, progresses have been
made in the Econo
mic General Equilibriu
m Models and the Causal–Descriptive Models co
mpared. Causal–Descriptive
models appear
more suitable for long-ter
m assess
ments in the LCA context while the co
mpared econo
mic
models are
more suitable for short/
mediu
m-ter
m assess
ments of LUC consequences. As LUC dyna
mics involve interdisciplinary knowledge, a co
mbination of econo
mic, biophysical and statistical data is however required to achieve a robust assess
ment of co
mplex LUC dyna
mics.
There is still considerable scope for improving current LUC models. In particular, there is room for improving precision of data, identification of marginal land and inclusion of a broader range of impact categories. Current models mainly focus on GHG emission-related impacts and rarely on other environmental impacts such as nutrient leaching, biodiversity impacts and water resource depletion. Socio-economic analyses of LUC patterns are currently excluded from LCA analysis, preventing a holistic assessment of land occupation impacts.