Selecting Evaluation Indices for Cleaner Production of Plantation Logging in Southern China with Fuzzy Clustering Methods

Abstract

Over the years, China has shown a significant reduction in natural forest resources, while the increasing area of plantations has made greater contributions to the huge demand for wood. In southern China, these new plantations have produced some problems such as environmental hazards of logging operations and the most reasonable use of forest resources. A new management process called »cleaner production« is defined as reducing pollution from its source, increasing the rate of utilization of resources, and preventing the generation of pollutants in the production of services and products. In recent years, cleaner production has been widely applied to industrial processes such as agriculture and other environmental industries. In order to make rational use of plantation resources, to achieve maximum economic efficiency and to reduce or remove the environmental hazards of logging operations, it is necessary to carry out an in-depth study of cleaner production on the process of logging operations. This paper aims to establish an index system for cleaner production evaluation of plantation logging. The fuzzy clustering method was used to initially screen twenty-nine indices. After screening by the fuzzy clustering method, six first-grade indices and twelve second-grade important indices were selected as formal evaluation indices. The six first-grade indices are 1) cutting area design index, 2) logging operation techniques index, 3) ecological environmental impact index, 4) utilization of resource and energy index, 5) sustainable development index, and 6) safety production management and protection index. A maximum and minimum matrix method and a correlation coefficient matrix method were used to establish the similar matrix in the fuzzy clustering method. The screening results were then compared. The comparison shows that out of the twelve second-grade indices, ten are similar and two are different. The results suggest that the fuzzy clustering method is reliable for screening indices