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基于知识粒度的森林生态系统健康评价指标赋权方法

刘素芝1,何小东1,李建军1,2**   

  1. 1中南林业科技大学, 长沙 410004; 2中国林业科学研究院资源信息研究所, 北京 100091)
  • 出版日期:2014-04-10 发布日期:2014-04-10

The method of attribute weight in forest ecosystem health evaluation based on knowledge granularity.

LIU Su-zhi1, HE Xiao-dong1, LI Jian-jun1,2**   

  1. (1College of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China; 2Institute of Forest Resource Information Techniques, China Academy of Forestry, Beijing 100091, China)
  • Online:2014-04-10 Published:2014-04-10

摘要:

依据系统科学原理,从影响森林健康包括的系统活力、系统组成、系统恢复力和林地环境等方面筛选13个指标构建森林健康评价指标体系;针对健康评价取值未知(无决策属性)的状况,利用粗糙集理论的属性重要度分析各指标因子对森林健康的影响程度,提出将基于知识粒度和属性重要度的森林健康评价指标赋权法。根据二类调查和样地调查数据,以湖南省大围山自然保护区8个次生林群落和2个人工林样地为应用实例,结果表明:森林健康评价指标体系的林分郁闭度、林分蓄积量、叶面积指数等13个指标在大围山自然保护区森林健康评价中的权重与专家打分法得到的结果基本相符,并且对样地进行了评价,其中只有1个处于健康,7个处于亚健康,2个处于不健康。与层次分析法、主成分分析法等赋权方法相比,基于粗糙集的森林健康评价指标赋权法不需要提供任何先验信息,以森林健康系统相关信息为分析依据,直接从反映森林健康的指标数据中挖掘各因子之间的相关性及其重要度,不依赖专家经验,信息量越大,所得权重越客观。该评价指标赋权法真实有效,评价结果更符合客观实际,为森林健康评价和健康经营提供理论依据。

 

关键词: 抽穗扬花期, 灌水, 晚稻, 产量, 低温, 生理特性

Abstract: According to the theory of system science, this paper established an evaluation system of forest health including 13 indicators from system vitality, composition and resilience and forest environment aspects. To solve the problem in which the health evaluation values are unknown, that is, no decision attribute, this paper applied attribute importance degree of rough set theory to analyze the indexes’ influence on forest health, with the forest health evaluation index weight being obtained based on knowledge granularity and attribute importance. We took eight secondary forest communities and two plantations in Daweishan Nature Reserve of Hunan Province as study cases. The results showed that the weights of 13 indexes were basically consistent with the expert scoring results. The evaluation results indicated that only one plot was at health level, seven at subhealth level and two at unhealthy level. Compared with the analytic hierarchy process method (AHP) and the principal component analysis method (PCA), this method did not need any prior information but took the information related to the forest health system as the basis to mine correlation and importance degree among factors directly reflecting forest health. It did not depend on experts’ experience, and the greater the amount of information, the more objective the attribute weight was. The results suggested that the evaluation method was real and effective and the evaluation result was more objective, providing a theoretical basis for forest health assessment and management.

Key words: late rice, heading and flowering stage, irrigation, yield, low temperature, physiological characteristics.