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机构地区:[1]湖北省水利水电科学研究院,武汉430000 [2]河北农业大学,河北保定071000
出 处:《水土保持研究》2015年第4期276-281,共6页Research of Soil and Water Conservation
基 金:国家自然科学基金"不同结构土壤斥水性对坡面侵蚀过程的综合影响及其作用机理研究"(41401317);国家重点基础研究发展规划资助项目(2005CB121107)
摘 要:聚落景观作为人类生产生活的聚集场所,体现人类空间活动强度,揭示人类活动与景观形成与演化的机制。借助ArcGIS平台和Fragstats软件,设定空间粒度30,100,250,500,1 000m,以RMA(面积最大值法)和RCC(中心属性值法)为原则进行转换,研究聚落景观分布格局空间粒度转换以及机理。结果显示:(1)RMA法生成数据各景观类型的面积相对误差较大,特别是当粒度为1 000m时交通用地消失,RCC法在空间粒度转换中的面积相对误差较小,并且是随机的。(2)斑块面积结构和空间邻接的景观类型决定空间粒度转换中的聚落景观格局。(3)聚落景观方面,斑块数量、斑块密度以及聚集度指数下降,面积加权平均斑块分维数上升,最大斑块指数先上升后下降,表现出随着粒度增加,小斑块逐渐被聚落景观较大斑块融入,斑块破碎化降低、斑块面积扩大并趋于成片成团等特征,使得聚落景观的斑块连片程度以及优势度提升。(4)聚落景观格局变化表明RMA法突出整体分布规律,RCC法突出聚落景观的空间分布特性。As a gathering place of human production and life, Settlement landscape reflects the intensity of hu- man space activities, reveals the mechanism of the formation and evolution of the human activity and forma- tion of the landscape. In this paper, based on the ArcGIS and Fragstats software, setting granularity of 30, 100, 250, 500, 1 000 m, with RMA (the largest value method) and RCC (center property value method) for the principles, conducted space conversion to study the settlement landscape spatial distribution pattern of granularity conversion and mechanism. The results show that: (1) principle of RMA conversion to generate landscape area error is large, especially when the particle size is 1 000 m, traffic land disappeared, principle of RCC in space granularity transformation in the area of relative error is less and random; (2) the patch area of structure and spatial governs landscape type space granularity transformation of settlement landscape pat- tern; (3) patch number, patch density and aggregation index decreased, area weighted average patch fractal dimension increased, the largest plaque index rose after the fall with the increase of particle size, small pat- ches by settlement landscape gradually into larger plaques, plaque forming degree and superiority degree in- crease; (4) the principle of the RMA settlement landscape transformation response was associated with spa- tial adjacency degree and area structure highlighting the overall distribution.
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