摘要
以甘肃省为例,通过分析林草大数据指标的基本特征,将其从空间尺度和服务对象2个方面进行分类。之后,依照地理景观与植被分布,将甘肃省分为河西走廊荒漠绿洲、祁连山森林草地、陇中—陇东黄土高原、陇南—陇东南山地森林和甘南高寒草地灌丛5个生境区,并在阐述了各生境区主要的生态服务功能的基础上,明确和提取出适宜于相应生境区的关键指标。
The rapid development of big data technology has provided new methods for the efficient processing of massive basic data in the forest and grass industry and the protection and restoration of the ecological environment.The rational classification and scientific extraction of basic data indices are important for the construction of the forest and grassland big data platform.Our study took Gansu Province as an example,classified as the two aspects of spatial scale and service objects by analyzing the basic characteristics of forest and grassland big data indicators.Furthermore,according to the geographical landscape and vegetation distribution,Gansu Province was divided into five habitat areas:Hexi Corridor Desert Oasis,Qilian Mountain Forest and Grassland,Loess Plateau of middle-east of Gansu,Mountain Forest of south-southeast of Gansu,and Gannan Alpine Grassland Shrub.The key indicators suitable for the corresponding habitat area were clarified and extracted based on the description of the main ecological service functions of each habitat area,which provided theoretical support for the scientific construction of the Gansu forest and grassland big data platform,and this will be helpful for the efficient resolution of ecological and environmental problems.
作者
张琴
王新源
程小云
曲浩
唐霞
ZHANG Qin(Gansu Institute of Forestry Survey and Planning,Gansu Lanzhou 730020)
出处
《林业科技》
2021年第1期27-33,共7页
Forestry Science & Technology
基金
国家自然科学基金面上项目(41877540)
甘肃省林草局草原生态修复治理科技支撑项目(甘林草函[2020]72号)。
关键词
林草大数据
空间尺度
服务对象
生境区
指标提取
Forest and grassland big data
Spatial scale
Service object
Habitat area
Index extraction