Research On Decision-making Of Optimal Desertification Control Plants In Tibet Based On Big Data

Land desertification is one of the most serious social,economic and ecological problems facing the world today.The scientific management of desertification is crucial for improving the living environment of human beings and ensuring the sustainable development of economy and society.Plant planting is one of the effective means of desertification control.Based on the complex diversity of desertification types,causes,ecological environment,social and human environment and other influencing factors,this paper analyzes the environmental adaptability of different plants by using scientific analysis methods to maximize the ecological,economic and social benefits of plants,which is of great significance to improve the success rate,efficiency and benefit of desert control in China.On the basis of summarizing the traditional methods of plant variety selection in desertification control,this paper studies the method of plant selection based on big data,which enhances the scientificity,predictability and effectiveness of the process of plant selection,and provides a new idea for desertification control.The specific research contents are as follows:(1)Study on the establishment of comprehensive evaluation indicators system and decision-making model for the optimal selection of desertification control plantsReferring to the existing research results,considering the suitability of plants and ecological environment as well as the comprehensive benefits of plant planting,a comprehensive evaluation indicators system for the optimal selection of desertification control plants based on big data was constructed from five aspects of environmental adaptability,ecological benefits,economic benefits,social benefits and others.Meanwhile,the quantitative method was given.On this basis,a weighted fuzzy-similarity-preferrenceratio plant primary selection decision-making model based on correlation coefficient and a multi-attribute decision-making model based on hierarchical analysis were constructed.At the same time,the model was improved according to the problems encountered in practical application,which lays a theoretical foundation for plant optimal selection from "ecology,society,economy" and other aspects.(2)Study and Verification for the optimal selection of desertification control plants in Shannan of TibetFirstly,based on the analysis of environmental characteristics in Shannan of Tibet,the desertification control plants in the germplasm resource database were preliminarily screened.Then,combined with topography,soil,ecological benefits,economic benefits,social benefits,planting preferences,transportation storage,related policies and other factors,the weights of each evaluation index were determined using the analytic hierarchy process and expert scoring method.Meanwhile,the optimal selection and sequencing of desertification control plants were also realized through the multi-attribute decision-making model.Finally,an introduction experiment was conducted on the plant selection results.Through the field planting effect,the feasibility of the plant optimization method based on big data is verified,which provides theoretical guidance for enterprise decision-making.(3)The construction of germplasm resource database for desertification control plants and the development of plant optimal selection systemOn the basis of the data collection and arrangement of desertification control plants,the construction background,principle and demand of the database were analyzed.The data fields and structure of the database were designed.Then,a collection of plants germplasm resources database covering the whole country was established,which provides data support for the scientific selection of plants.In addition,starting from the system requirements,applying technologies such as big data analysis,data storage and data visualization,a system for desertification control plants optimal selection with functions of analysis,evaluation,decision-making and so on has been constructed,which provides an effective solution for accurately and intelligently matching plants in desertified areas.