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路 晓,王金满,李 博,白中科.矿山土壤特性及其分类研究进展[J].土壤,2017,49(4):670-678. LU Xiao,WANG Jinman,LI Bo,BAI Zhongke.Progresses in Soil Properties and Classification of Mining Soils[J].Soils,2017,49(4):670-678 本文二维码信息
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矿山土壤特性及其分类研究进展
Progresses in Soil Properties and Classification of Mining Soils
投稿时间:2016-05-23  修订日期:2016-11-20
DOI:10.13758/j.cnki.tr.2017.04.005
中文关键词:  矿山土壤  土壤分类  土壤特性  开采和复垦
Key Words:Mining soil  Soil classification  Soil characteristics  Exploitation and reclamation
基金项目:国家自然科学基金项目(41271528)资助。
作者单位E-mail
路 晓 中国地质大学土地科学技术学院 luxiao002016@163.com 
王金满 中国地质大学土地科学技术学院 wangjinman2002@163.com 
李 博 中国地质大学土地科学技术学院  
白中科 中国地质大学土地科学技术学院  
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中文摘要:
      矿山土分类是认识矿山土壤的基础,对矿山土壤系统分类研究是进行矿山土壤改良和植被重建的重要基础。本文从物理、化学、生物和污染 4 个方面阐述了矿山土壤特性的变化及其对矿山土壤系统分类的影响,并对分类名称、依据、指标体系和分类方法的相关研究进展进行了综述。目前,矿山土壤系统分类大多以其特有属性作为分类指标,运用光谱技术、模糊均值法和神经网络模型等方法完成分类。但这些方法都有其自身的优缺点,建议今后因地制宜地选取定量化分类指标,探索将主成分分析等数学模型与光谱等技术相结合的方法进行矿山土壤系统分类,以期为今后矿山土地复垦与利用提供科学依据。
Abstract:
      Classification is one of the foundation in studying mining soils, which is particularly important for the improvement and vegetation reconstruction of mining soils. This paper described the changes of mining soil characteristics and their influences on the classification of mining soils from four aspects of physics, chemistry, biology and pollution, summarized the research advances in the name, basis, index system and method of the classification in mining soils. At present, mining soils were classified by using spectral technology, fuzzy c-mean method and neural network model on the bases of their unique attributes, but these methods have their own advantages and disadvantages, thus, it was recommended for future study to select quantitative classification index according to the local conditions to combine principal component analysis and other mathematical models with spectral techniques for mining soil classificationin order to provide further scientific basis for land reclamation and utilization.
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