Paper
24 October 2012 Dynamic modelling of future land-use change: a comparison between CLUE-S and Dinamica EGO models
Author Affiliations +
Abstract
Land-use and land-cover change has been a research focus in global environmental change. Recent research found that land-use change could influence the structure of biogeochemical spheres as well as material and energy recycle directly or indirectly. Land-use dynamic models are considered as an effective technique to study the processes of land-use modification. The objective of this paper is to compare two widely use land-use dynamic models, CLUE-S and Dinamica EGO, from the perspective of land-use change amount, spatial characteristics, and their utility. A case study was conducted to examine the ascendants of each model and Kappa coefficient was used to compare the simulation accuracy. The modelling experiments reflected that the predictions of land-use change based on CLUE-S and Dinamica EGO matched broadly with actual situation. CLUE-S was better in overall accuracy whereas the Markov process in Dinamica EGO could precisely predict the amount of land-use change. Moreover, the spatial pattern of simulation map based on Dinamica EGO was more consistent with empirical result. Both results indicate their possible further applicability for forecasting future land-use change and corresponding studies.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wei Yi, Zhiqiang Gao, and Maosi Chen "Dynamic modelling of future land-use change: a comparison between CLUE-S and Dinamica EGO models", Proc. SPIE 8513, Remote Sensing and Modeling of Ecosystems for Sustainability IX, 85130H (24 October 2012); https://doi.org/10.1117/12.927781
Lens.org Logo
CITATIONS
Cited by 3 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Modeling

Agriculture

Data modeling

Climate change

Data centers

Geographic information systems

Roads

Back to Top