摘要
林地分等是自然资源资产化管理的重要信息维度。本文以广东省林地分等工作为例,运用多源数据融合、组合分析量化指标、Python语言批处理、试生产和试分等关键技术和方法,解决了数据异构、计算流程复杂、时间和人工成本高、精度难以保障等实际生产问题。广东省林地分等实践表明,省域范围内各等别林地面积占比整体呈正态分布,分等单元未出现明显跳等现象,等别过渡较平滑,为后续林地定级和基准地价制定提供重要依据。文章总结归纳的林地分等技术体系和关键技术已同步应用于广东省园地和草地分等工作,可为全国园地、林地、草地分等定级工作提供参考思路和借鉴案例。
Forestland gradation,classification and evaluation are an important information dimensions of natural resources asset-based management.Taking forestland gradation,classification and evaluation in Guangdong as an example,this paper describes how to use key technologies and methods such as multi-source data fusion,quantitative indicators combination analysis,Python batch processing,pilot production and trial gradation,classification and evaluation.It solves the practical production problems such as heterogeneous data,complicated calculation process,high time and labor cost,and difficulty in guaranteeing accuracy.The practice of forestland gradation,classification and evaluation in Guangdong shows that the proportion of forestland area in the province is normally distributed,and there is no obvious jump in the grading unit,and the transition is relatively smooth,which can provide an important basis for the subsequent forestland gradation,classification and evaluation and benchmark land price formulation.The technology system and key techniques of forestland gradation,classification and evaluation summarized in this paper have been applied to the classification of garden land and grassland in Guangdong,which can provide ideas and cases of references for the gradation,classification and evaluation work of garden,forest and grassland in China.
作者
谢萍
XIE Ping(Land and Resources Technology Center of Guangdong Province,Guangzhou 510075,Guangdong,China;…2.Construction Land Redevelopment Key Laboratory of Ministry of Natural Resources,Guangzhou 510040,Guangdong,China)
出处
《自然资源信息化》
2023年第5期46-51,共6页
Natural Resources Informatization
关键词
林地分等
多源数据融合
组合分析法
广东
gradation,classification and evaluation of forestland
multi-source data fusion
combination analysis
Guangdong
