蒋知栋, 李晶, 高杨, 曾纪勇, 位蓓蕾. 基于改进灰色聚类模型的矿区耕地损毁程度评价[J]. 中国生态农业学报(中英文), 2013, 21(6): 765-771. DOI: 10.3724/SP.J.1011.2013.00765
引用本文: 蒋知栋, 李晶, 高杨, 曾纪勇, 位蓓蕾. 基于改进灰色聚类模型的矿区耕地损毁程度评价[J]. 中国生态农业学报(中英文), 2013, 21(6): 765-771. DOI: 10.3724/SP.J.1011.2013.00765
JIANG Zhi-Dong, LI Jing, GAO Yang, ZENG Ji-Yong, WEI Bei-Lei. Using improved Gray Clustering Method to evaluate the degree of damage to arable lands in mining areas[J]. Chinese Journal of Eco-Agriculture, 2013, 21(6): 765-771. DOI: 10.3724/SP.J.1011.2013.00765
Citation: JIANG Zhi-Dong, LI Jing, GAO Yang, ZENG Ji-Yong, WEI Bei-Lei. Using improved Gray Clustering Method to evaluate the degree of damage to arable lands in mining areas[J]. Chinese Journal of Eco-Agriculture, 2013, 21(6): 765-771. DOI: 10.3724/SP.J.1011.2013.00765

基于改进灰色聚类模型的矿区耕地损毁程度评价

Using improved Gray Clustering Method to evaluate the degree of damage to arable lands in mining areas

  • 摘要: 为更加客观准确地反映矿区耕地的损毁程度, 更好地服务于耕地保护与土地复垦, 针对经典灰色聚类法单纯用阈值法确定权重, 不能较好地反映指标的损毁程度对聚类对象影响的局限性, 本文设定了有效土层厚度为主导限制性指标, 并将相对限制性指数融入到灰色聚类法中, 构建了GCM_DR(Grey Clustering Method_Dominant Restrictive Indicator & Relatively Restrictive Index)矿区耕地损毁程度评价模型, 并选用我国某高潜水位矿区塌陷损毁耕地进行了评价模型应用的验证。结果表明: 研究区2个塌陷盆地共计8个评价单元的损毁等级分别为Ⅱ、Ⅲ、Ⅳ、Ⅴ、Ⅰ、Ⅱ、Ⅲ、Ⅲ, 该趋势与其他方法基本一致, 结合实地调研情况, 表现了较高的可靠性; 主导限制性指标的设定使得该模型既考虑到了综合因素又兼顾主导因素, 一定程度上减小了评价任务的工作量, 提高评价工作的效率; 与经典灰色聚类模型相比, 改进后的模型强调指标的相对限制性, 损毁程度大的指标权重较大, 聚类系数向损毁级别高的方向倾斜, 表现了较好的灵敏性; 在确定权重时改进后的模型强调聚类指标的相对损毁程度, 一定程度上减小了分级跨度不同导致的权重分配的不合理性。因此, GCM_DR模型可应用于矿区耕地损毁程度评价工作中, 在了解耕地损毁现状、编制土地复垦方案、确定赔偿责任范围等方面有较好的应用价值。

     

    Abstract: China has limited cultivated land and huge population, making China's per-capita cultivated land far smaller than most other countries. Although it brings enormous economic wealth to the country, mineral resources mining has also destroyed a large fraction of cultivated lands. Hence for the efficient protection of cultivated lands, it is critical to evaluate (in terms of quantity and quality) cultivated land damage via mining operations in China. Grey Clustering Method can be used in such evaluations in terms of fuzzy mathematical theory. Although widely used in other fields, its application in evaluation the degree of damage caused by mining operations to cultivated lands has been highly limited. The task of this paper was to analyze the degree to which arable lands had been damaged by mining operations. The study aimed to more objectively and accurately assess the services of arable lands and the measures for reclamation and protection. The classic Gray Clustering Method was used to determine the weights of the indicators for damaged arable lands, with appropriate adjustments to relate the threshold of the indicators to cluster objects. In this paper, effective soil thickness was set to dominant restrictive indicator. Then the relative restrictive indicators were integrated into the Gray Clustering Method to construct a GCM_DR (Grey Clustering Method Dominant Restrictive Indicator and Relative Restrictive Index) which was then used to evaluate the extent of damage of arable lands in mining areas. The model was used to evaluate some damaged arable lands in the high-dive mining area and the results compared with other evaluation methods. The results showed that the degree of damage to a total of eight evaluated units of land in two collapsed basins were respectively II, III, IV, V, I, II, Ⅲ and Ⅲ. This was approximately consistent with the results of other methods, suggesting a high reliability of the proposed method. The set of dominant restrictive indicators that accounted for the combined factors and dominant factors of the model somewhat reduced assessment process and improved evaluation efficiency. Compared with the classical Gray Clustery Model, the improved model emphasized relative restrictive index which was more sensitive. The model allocated higher weights to indexes with greater degree of damage so that the clustering coefficient closely reflected the direction of severe damage. In terms of weight ratio, the improved model emphasized the relative degree of damage expressed by the clustering coefficient. Thus to some extent, it reduced the irrationality of weight distribution caused by different hierarchical spans. This made GCM_DR model more applicable in evaluating the degree of damage to cultivated lands in mining areas. The model was suitable for determining the state of arable lands, establishing land reclamation measures and consolidating land protection programs.

     

/

返回文章
返回