摘要
建立土地利用变化模型,模拟多种情景下的土地利用变化过程,能够为科学的土地利用决策提供辅助支持。以常州市新北区为研究区,从政策特征因子、全局特征因子和空间特征因子3个方面构建土地利用情景特征因子体系;运用多智能体建模方法构建基于主体的土地利用情景模拟模型;设定快、中、慢3种经济社会发展条件下的土地利用情景(I、II、III),模拟研究区2006-2020年土地利用变化。结果表明:3种土地利用类型的空间全局拟合度都相对较高,城镇用地、农村居民点用地和耕地的空间全局拟合度分别为78.45%、99.85%、98.35%;空间变化拟合度较低,分别为55.18%、0.02%、69.11%。在3种土地利用情景下,城镇用地增加面积分别为3788.44、2922.83和2114.64hm2,农村居民点用地减少面积分别为1106.60、858.61和592.35hm2,耕地减少面积分别为5378.72、4817.03和4238.97hm2。说明情景I下城镇化速度较快,城乡用地转换明显,农村居民点整治力度较大;情景II下城镇用地空间扩张和人口增长都减缓速度,耕地资源的流失得到一定程度控制;情景III下城乡用地变化速度显著放缓,耕地资源流失得到有效控制。
To put forward feedback information of the scenario simulation model for the references of land use planning decision, we reviewed and analyzed the land use characteristics (1996-2009) in Xinbei district of Changzhou, and extracted three important types of land use: cultivated land, construction land and rural residential land. Typical relation analysis method and spatial gridding Logistic regression analysis method were used to made quantitative analysis of these three types of driving forces and obtain the main influential driving forces for each land use. Based on the analysis of land use characteristics and driving forces, the study built land use scenario characteristic system from three aspects which included political characteristics, global characteristics and spatial characteristics, and expressed land use scenario characteristics quantitatively. The MAS technology was introduced to construct an agent-based land use scenario simulation model, and using the development platform of Eclipse+Swarm, realize the land use scenario simulation model. The results showed that the changes of structure in Xinbei district were increasingly complicated; reduction of agricultural land contributed most to the increase of urban land. In term of spatial arrangement, the changes of land use types were the greatest in the study areas of eastern or southeastern parts along the administrative region boundary, or the Yangtze River catchment. 1) The results showed that fitting degree of the spatial global simulation was high, that of construction land, rural residential land and cultivated land was 78.45%, 99.85%, 98.35% separately, and fitting simulation of spatial variation for construction land, rural residential land and cultivated land was 55.18%, 0.02%, 69.11% separately. 2) The study set three scenarios of socio-economic development (with high, medium and low developing speed) and simulated the land use changes from 2006 to 2020. The results showed that in the three scenarios, the construction land would increase 3788.44, 2922.83 and 2114.64 hm2; the cultivated land would increase 1106.60, 858.61 and 592.35 hm2; the rural residential land would increase 5378.72, 4817.03 and 4238.97 hm2. In the scenario I, the urbanization would go fast, the urban-rural land convertion would be obvious, and the renovation and reconstruction of the rural residential land would enhanced; in the scenario I1, the urban expansion and population growth would slow down, and the cultivated land loss would be decrease; in the scenario III, the urban-rural land convertion would decrease obviously, and the cultivated land loss would be prevented effectively. 3)The compactness analysis under the three scenarios showed that the compact degree would be low in the scenario I (construction land, rural residential land and cultivated land was 0.0059, 0.0036, 0.0024, separately)and in the scenario III (construction land, rural residential land and cultivated land was 0.0057, 0.0031, 0.0024, separately), but high in the scenario II(construction land, rural residential land and cultivated land was 0.0061, 0.0034, 0.0022 separately); the rural residential land would be dispersive in the scenario III and the renovation of the rural villages would be the least in the scenario II.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2013年第4期255-265,I0009,F0003,共13页
Transactions of the Chinese Society of Agricultural Engineering
基金
国家自然科学基金资助项目(40901183)
江苏省高校自然科学研究面上项目(12KJB170004)
关键词
土地利用
多智能体系统
模型
情景模拟
特征因子
常州市新北区
land use, multi agent system, models, scenario simulation, characteristic factor, Xinbei District of Changzhou City