Spatial Structure Evaluation of Natural Secondary Forest around Dongting Lake Based on Entropy Weight - Cloud Model

Li, X.; Zhang, G., and Li, J., 2020. Spatial structure evaluation of natural secondary forest around Dongting Lake based on entropy weight - cloud model. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 484–489. Coconut Creek (Florida), ISSN 0749-0208.In order to provide theoretical support for the formulation of optimized measures of stand spatial structure, 15 sample plots are set up in Daweishan Nature Reserve, Longhushan national forest farm in Yuanjiang City and Lutou national forest farm in Pingjiang County to analyze and evaluate the stand spatial structure of natural secondary forest around Dongting Lake. After determining the spatial structure unit of trees by Voronoi diagram, the five indicators including mingling degree, neighborhood comparison, openness comparison index, neighborhood pattern and angle competition index are segmented to correspond to the five grades of stand spatial structure divided by the combination of qualitative and quantitative methods. Then through the comprehensive assessment on stand spatial structure by entropy weight-cloud model, the fifteen plots are evaluated as grade III and grade IV, respectively accounting for two-thirds and one-thirds of all plots, which indicates that the reasonable stand spatial structure of natural secondary forest around Dongting Lake is above the average. As a new evaluation method of stand spatial structure, the entropy weight-cloud model has solved the issue of qualitative and quantitative conversion, and objectively calculate the weights of indicators, so as to enrich the evaluation methods of stand spatial structure, overcome the one-way evaluation by single indicator, improve the objectivity and scientificity of evaluation results, and provide theoretical basis for the scientific guidance of stand spatial structure optimization.