PROGRESS IN GEOGRAPHY ›› 2005, Vol. 24 ›› Issue (5): 79-87.doi: 10.11820/dlkxjz.2005.05.009

• Original Articles • Previous Articles     Next Articles

Review of Land-use Model

LIN Qing1,2, LUO Geping1, CHEN Xi1   

  1. 1. Xinjiang Institute of Ecology and Geography, CAS, Urumqi 830011, China|
    2. Graduate School of the Chinese Academy of Sciences, Beijing 100039, China
  • Received:2005-03-01 Revised:2005-07-01 Online:2005-09-25 Published:2005-09-25

Abstract:

Land use change is one of the main research subjects of global environmental change and sustainable development. Driving force is the core subject of LUCC, including both biophysical and human factors at different temporal and spatial scales. Land-use models are useful for disentangling the complex suite of socio-economic and biophysical forces that influence the rate and spatial pattern of land use change and for estimating the impacts of changes in land use. Furthermore, models can support the exploration of future land use changes under different scenario conditions. Scenario analysis with land use models can support land use planning and policy. Many land use models are available, developed from different disciplinary backgrounds. This paper reviews several current land use change models to identify priority issues for future land use change modelling research. All these models were divided into three classes: empirical and statistical models (e.g., regression model), dynamic (process-based) models (e.g., cellular automata model and system dynamic model) and integrated models (e.g., conversion of land use and its effects, or CLUE model). For each of these models, a review is given and the advantages and disadvantages are discussed. Some suggestions for improving each model have also been put forward. Finally, we get three general conclusions. First, dynamic, process-based simulation models appear to be better suited to predict changes in land-use system than empirical, statistical models. Second, empirical, statistical models can complement dynamic (process-based) simulation models. Third, in the future, an integrated approach to modeling——that is based on multidisciplinary and cross-sectoral combining elements of different modelling techniques——will probably best serve the objective of improving understanding of land-use change processes. If this requirement is satisfied models will better support the analysis of land use dynamics and land use policy formulation.

Key words: driving force, land use and land cover change (LUCC), land use system, model