This study seeks a routine to quantify spatial pattern of land cover changes in semiarid environment of China based on post-classification comparison method. The method consists of three major steps: (1) the image classification and unification of classified results based on two-level land cover classification themes, (2) the establishment of land cover change classes based on an unification land cover classification theme, (3) the reclassification and mapping of land cover change classes with three overall classes including no-change, gain and loss based on the unification land cover class. This method was applied to detect the spatial pattern of land cover changes in Yinchuan Plain, one of famous irrigation agricultural zones of the Yellow River, China. The results showed the land cover had undergone a remarkable change from 1991 to 2002 in the study area (the changed area was over 30%). Rapid increase of cropland (12.5%), built-up area (131.4%) and rapid decrease of bare ground (51.7%) were alarming. The spatial pattern of land cover changes showed clear regional difference in the study area and was clearly related to human activities or natural factors. Thus, it obtained a better understanding of the human impact on the fragile ecosystem of China’s semiarid environment.
BaoLin LI1 and QiMing ZHOU2 1 State Key Laboratory of Environment and Resources Information System, Institute of Geographical Sciences and Resources Research, Chinese Academy of Sciences, Beijing 100101, China
传统的基于行政区的土地统计数据不能完全表现区域内部土地利用的空间分异特征,以武汉市为实验区,对基于网格的统计信息算法STING(Statistical Information Grid-based method)进行扩展,以景观多样性指数为定量化指标对实验区进行四叉树划分生成不均匀多级网格,建立一种拟合了行政区划界线的不均匀的多级网格结构来存储、管理和分析土地数据。并以此多级网格数据结构为平台计算和生成实验区人口密度空间分异渲染图,初步抽取了人口分布与土地利用之间的关系。实验表明,基于多级网格的统计方法能更好地表达土地利用及其相关数据的空间分异性,利于对土地资源数据的进一步挖掘以抽取所需知识。
