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Implementing GIS regression trees for generating the spatial distribution of copper in Mediterranean environments: the case study of Lebanon

机译:实施GIS回归树以生成地中海环境中铜的空间分布:黎巴嫩案例研究

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摘要

Soil contamination by heavy metals has become a widespread dangerous problem in many parts of the world, including the Mediterranean environments. This is closely related to the increase irrigation by waste waters, to the uncontrolled application of sewage sludge, industrial effluents, pesticides and fertilizers, to the rapid urbanization, to the atmospheric deposition of dust and aerosols, to the vehicular emissions and to many other negative human activities. In this context, this paper predicts the spatial distribution and concentration level of copper (Cu) in the 195 km~2 of Nahr el-Jawz watershed coastal area situated in northern Lebanon using a geographic information system (GIS) and regression-tree analysis. The chosen area represents a typical case study of Mediterranean coastal landscape with deteriorating environment. Fifteen environmental parameters (parent material, soil type, pH, hydraulical conductivity, organic matter, stoniness ratio, soil depth, slope gradient, slope aspect, slope curvature, land cover/use, distance to drainage line, proximity to roads, nearness to cities, and surroundings to waste areas) were generated from satellite imageries, Digital Elevation Models (DEMs), ancillary data and/or field observations to statistically explain Cu laboratory measurements. A large number of tree-based regression models (214) were developed using (1) all parameters, (2) all soil parameters only, and (3) selected pairs of parameters. The best regression tree model (with the lowest number of terminal nodes) combined soil pH and surroundings to waste areas, and explained 77% of the variability in Cu laboratory measurements. The overall accuracy of the predictive quantitative copper map produced using this model (at 1:50,000 cartographic scale) was estimated to be ca. 80%. Applying the proposed tree model is relatively simple, and may be used in other coastal areas. It is certainly of significant interest to local governments and municipalities. It will serve several development projects concerned with improving the environmental conditions and the quality of living in coastal areas.
机译:重金属对土壤的污染已成为世界许多地方(包括地中海环境)普遍存在的危险问题。这与废水灌溉的增加,污水污泥,工业废水,农药和化肥的无节制使用,快速的城市化,粉尘和气溶胶在大气中的沉积,车辆排放以及许多其他负面因素密切相关。人类活动。在此背景下,本文使用地理信息系统(GIS)和回归树分析法预测了黎巴嫩北部纳赫尔-贾兹(Nahr el-Jawz)流域沿海地区195 km〜2中铜(Cu)的空间分布和浓度水平。选择的区域代表了环境恶化的地中海沿岸景观的典型案例研究。十五个环境参数(母体材料,土壤类型,pH,水力传导率,有机质,石质比,土壤深度,坡度,坡度,坡度曲率,土地覆盖/使用,与排水线的距离,与道路的距离,与城市的距离)以及废物区域的周围环境)是通过卫星图像,数字高程模型(DEM),辅助数据和/或现场观察生成的,以统计学方式解释铜实验室的测量值。使用(1)所有参数,(2)仅所有土壤参数以及(3)选择的参数对开发了许多基于树的回归模型(214)。最好的回归树模型(末端节点数最少)将土壤pH值和周围环境结合到废物区域,并解释了Cu实验室测量值的77%的变异性。使用此模型(在1:50,000制图比例下)生成的预测性定量铜图的总体准确性估计为。 80%。应用所提出的树模型相对简单,并且可以在其他沿海地区使用。当然,这对地方政府和市政当局都具有重大意义。它将为几个与改善环境条件和改善沿海地区生活质量有关的发展项目提供服务。

著录项

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  • 作者单位

    Department of Agroecology and Environment, Faculty of Agricultural Sciences (DJF), Aarhus University, Blichers Alle 20, P.O. Box 50, DK-8830 Tjele, Denmark, Department of Geography, GIS Research Laboratory, Faculty of Letters and Human Sciences, Lebanese University, P.O. Box 90-1065, Fanar, Lebanon;

    Department of Agroecology and Environment, Faculty of Agricultural Sciences (DJF), Aarhus University, Blichers Alle 20, P.O. Box 50, DK-8830 Tjele, Denmark;

    Universite de Reims Champagne-Ardenne, EA 3795 GEGEN AA, 2 esplanade Roland Garros, 51100 Reims, France;

    Faculte des Sciences de Tunis, Campus universitaire, Universite El Tunis Manar, Avenue 7 Novembre 2092, Tunis;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Cu concentration; heavy metals; soil pollution; GIS regression trees; mediterranean environments; lebanon;

    机译:铜浓度重金属;土壤污染;GIS回归树;地中海环境;黎巴嫩;

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