Simulation of Land-Use Policies on Spatial Layout with the CLUE-S Model

Currently, the simulation of land use and land cover change is one of the research focuses in land resource management. Models for simulating this topic have been used by lots of scholars. In the process of experiments, especially using the models, to grasp the characteristics of data has a significant impact on the simulation results. With the changes in policies of land use, the spatial layout has shown a new form. How to simulate the change is one of the focuses in the current Land Resource Management. Therefore, this paper analyzes the current land use of the study area in two aspects: the structure and spatial layout, studying on changes in demand according to the current major changes of policies for land use in the area.; based on the in-depth analysis, by making reasonable choices of land use classification and using the logical regression analysis and ROC curve to select driving factor which is suitable for the characteristics of the study area; a reasonable simulation is then conducted for the impact on the spatial layout for land use change policies through CLUE-S model. The result shows that the exact parameters in line with the characteristics of the study area in CLUE-S mode could simulate the land use spatial layout for many land-use policies such as "construction land uphill", "construction land making room for arable land", "construction land along the river and road development", "key industries land expansion". The results have certain significance on land use changes and land use planning. In order to assist the decision making and improve the efficiency of land use, using this method can help the department of land and resource use to simulate the situation of the land use from the structure and the spatial layout in future according to the demands and the local policies of the land.

Abstract licence: CC BY

12 more references, whose wording the paper’s licence keeps private.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.