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Analyzing spatial variations in land use/cover distributions: A case study of Nanchang area, China

机译:土地利用/覆被分布的空间变化分析:以南昌市为例

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摘要

Quantification of spatial variation is important for analyzing and predicting the environmental and social impacts of land development. This paper presents a density-based framework to analyze spatial variations within land use/cover classes through a case study of the Nanchang area, China. By means of grid sampling, the categorical patches were represented by grid densities, and spatial indicators of class abundance, scale-area curve and neighborhood density were constructed to measure the spatial variables of area, distance and scale. The scale variations within each class were demonstrated by abundance indicators and were divided into three types with different similarity degrees, which were measured by coefficients of congruence. These variations roughly corresponded to the distribution patterns revealed by the scale area indicators. The scaling behaviors of these patterns exhibited discontinuity and coherence, which were possibly affected by the change rates of some patch characteristics in the classes. The neighborhood density indicators showed that every class was more aggregated at short distances, while multimodal patterns fluctuating in nearly random distributions occurred at considerable distances. The degree of clumping correlated positively with the abundance of each class. The characteristics of distribution sizes, ranges and patch isolation in these classes left some imprints on the variations in aggregation intensity. These findings have implications for data integration, mechanism exploration and methodological framework, which are also needed for management practices. (C) 2017 Elsevier Ltd. All rights reserved.
机译:空间变化的量化对于分析和预测土地开发的环境和社会影响非常重要。本文提出了一个基于密度的框架,通过对中国南昌地区的案例研究来分析土地利用/覆被类别内的空间变化。通过网格采样,用网格密度表示分类斑块,并构建了类别丰度,尺度-面积曲线和邻域密度的空间指标,以测量面积,距离和尺度的空间变量。每个类别内的规模变化均由丰度指标证明,并分为三种相似度不同的类型,并用同余系数来衡量。这些变化大致对应于刻度区域指示器显示的分布模式。这些模式的缩放行为表现出不连续性和连贯性,这可能受到类别中某些贴片特性的变化率的影响。邻域密度指标表明,每个类别在短距离内的聚集程度都更高,而多峰模式在相当长的距离内以几乎随机的分布波动。结块程度与每个班级的丰富程度呈正相关。这些类别中的分布大小,范围和补丁隔离的特征给聚集强度的变化留下了一些烙印。这些发现对数据集成,机制探索和方法框架都有影响,而管理实践也需要这些发现。 (C)2017 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Ecological indicators》 |2017年第5期|52-63|共12页
  • 作者单位

    Fujian Agr & Forestry Univ, Coll Resources & Environm, Fujian Prov Key Lab Soil Environm Hlth & Regulat, 15 Shangxiadian Rd, Fuzhou 350002, Fujian, Peoples R China;

    Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China;

    Fujian Normal Univ, Coll Geog Sci, Fuzhou, Fujian, Peoples R China;

    Jiangxi Acad Sci, Poyang Lake Res Ctr, Nanchang, Jiangxi, Peoples R China;

    Fujian Agr & Forestry Univ, Coll Resources & Environm, Fujian Prov Key Lab Soil Environm Hlth & Regulat, 15 Shangxiadian Rd, Fuzhou 350002, Fujian, Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Spatial pattern; Landscape; Gradient; Density indicator; Scale effect;

    机译:空间格局;景观;梯度;密度指标;比例效应;

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