林业海量数据挖掘与分析:方法与应用  

Forest Big Data Mining and Analysis:Methods and Applications

作　　者：张弦[1] ZHANG Xian(Ecology Branch,Yunnan Academy of Forestry Survey and Planning,Kunming 650000,China)

机构地区：[1]云南省林业调查规划院生态分院,昆明650000

出　　处：《林业科技情报》2025年第1期113-115,共3页Forestry Science and Technology Information

摘　　要：该文探讨了在大数据时代背景下如何利用数据挖掘与分析技术,对林业领域的海量数据进行有效地处理与应用。文章首先阐述了林业海量数据的特点及面临的挑战,然后重点介绍了几种常用的数据挖掘与分析方法,包括关联规则挖掘、决策树和聚类分析等。接着,文章结合实际案例讨论了这些方法在林业资源调查、森林灾害预警和生态系统监测等方面的应用。最后,文章展望了林业海量数据挖掘与分析技术的发展趋势,并提出了进一步研究的方向。This paper explores how to effectively process and apply massive data in the forestry field using data mining and analysis techniques in the context of the big data era.The article first elaborates on the characteristics and challenges of big data in forestry,then focuses on several commonly used data mining and analysis methods,including association rule mining,decision trees,and cluster analysis.Then,combining practical cases,the article discusses the application of these methods in forest resource surveys,forest disaster early warning,ecosystem monitoring,and other aspects.Finally,the article looks forward to the development trends of big data mining and analysis technologies in forestry and proposes further research directions.

关 键 词：林业 海量数据 数据挖掘 数据分析 应用 

分 类 号：S71[农业科学—林学]