文献类型：期刊文献

中文题名：沽源县土地利用格局的多尺度模拟与分析

英文题名：Spatial Land Use Patterns in Guyuan County: Simulation and Analysis at Multi-Scale Levels

作者：张永民[1];周成虎[2];郑纯辉[1];李立伟[3]

第一作者：张永民

机构：[1]河南财经学院资源与环境科学系;[2]中国科学院地理科学与资源研究所;[3]河南省林业调查规划院

第一机构：河南财经政法大学资源与环境学院

年份：2006

卷号：28

期号：2

起止页码：88-96

中文期刊名：资源科学

外文期刊名：Resources Science

收录：CSTPCD;;北大核心:【北大核心2004】；CSSCI:【CSSCI2006_2007】；CSCD:【CSCD2011_2012】；

基金：河南财经学院博士科研启动基金;国家自然科学基金项目(编号:40225004)

语种：中文

中文关键词：土地利用格局;空间模拟;Logistic回归模型

外文关键词：Spatial land use patterns; Spatial simulation; Logistic regression models

摘要：基于由遥感和数字高程模型数据源得到的土地利用、地形、河流、湖泊、道路,以及城镇和农村居民点等空间数据,本文运用Logistic回归模型对河北省沽源县耕地、林地和草地的空间分布格局进行了模拟。为了分析土地利用格局模拟过程中的尺度相关性特征,本文分别在100m×100m、250m×250m、500m×500m、750m×750m和1 000m×1 000m共5个空间模拟尺度的基础上构建了相应的土地利用格局模拟模型。结果显示,在不同的模拟尺度上,土地利用格局模拟模型的变量数目与变量系数都存在一定的差异,表明土地利用格局与其决定因素之间的关系包含一定的尺度相关性特征。比较不同模拟尺度上模型的拟合优度,发现当模拟尺度为500m时,耕地、林地和草地格局模拟模型的拟合优度均达到最高(ROC值分别为0.745,0.738和0.714)。研究结果揭示了沽源县土地利用格局形成与演变的重要决定因素,这为进一步研究该县未来的土地利用动态变化情景奠定了基础;研究结果也可以为沽源县及其相似地区的土地利用规划决策提供科学依据。
A spatial understanding of the relationships between different land use and their determinants is an important contribution towards sustainable land use planning. Land uses in Guyuan county, Hebei province, were investigated by means of binary logistic regression with the purpose of deriving potential determinants of spatial land use patterns on the basis of terrain characteristics and infrastructural conditions. Terrain characteristic variables were firstly calculated with the smallest spatial unit of 50 m （ 50 m regular grids. Then, these variables, together with infrastructural variables and land use data, were aggregated into 5 artificial aggregation units （ 100m×100m, 250m × 250m, 500m×5oom,750m×750m, and 1 000m × 1 000m） to explore spatial scale dependence of the relation between spatial land use patterns and their possible determinants. For all aggregation levels independent binary logistic regression models were constructed for investigating spatial patterns of land use types of cultivated land, forestland and grass land. The results showed that spatial patterns of the three land use types could be well explained by different combinations of potential determinants. In most cases, terrain characteristics as well as infrastructural conditions are important for the explanation of spatial patterns of land use types, although the variables included in the models and their relative importance varies between land use types. Also for every land use type, the model variables varies with aggregation levels, indicating spatial scale effects. In addition, all these land use models are validated by an ROC method. The ROC can compare a map of actual land use distribution to maps of modeled probability for land use types. The results indicate that 500m×500m is an significant unit for simulating the distribution of land use types of cultivated land （ROC = 0.745）, forest land （ROC = 0.738） and grass land （ROC = 0.714） in the study area. It is argued that these types of analysis can provide valuable information for modeling future land use change scenarios that need to consider local and regional conditions of actual land use. On the other hand, the probability maps of the land use types obtained from this study can also support government decisions on land management, such as the conversion of unsustainable cultivated land into forest land or grass land.