全球及区域模式中陆面过程的地表植被覆盖分类方法

全球和区域尺度上陆面生态系统与气候密切相关。全球和区域模式的发展对于我们认识气候与陆地生态的变化起到重要作用。在这些模型中，植被覆盖是影响大气-植被间热量、水分和CO2等交换的重要陆面参数。在分析了陆地植被覆盖分类原理基础上，介绍了目前全球不同植被覆盖分类方案，包括基于地基观测的植被分布、基于生物气候特征的分类方案（如：Holdridge的方案）；特别近年来陆面过程试验表明，各种遥感数据源（如：NOAA—AVHRR，EOS—MODIS，Landsat—TM）等为我们提供了有利的工具来监测全球植被动态，完善植被分类，并且采用高时空分辨率的全球土地覆盖状况特征，在不同时空尺度揭示植被-大气相互作用。本文分析了代表性的3种基于卫星遥感技术的陆面植被分类方案，分别是BATS（18类）、SIB（9类）、SIB2（12类）和BIOME—BGC（31类）陆地模式的植被覆盖分类方案．最后分析了目前可用于全球植被覆盖分类的新的遥感数据库。

Vegetation classification scheme of land surface process in GCM & RCM

It is well known that climate is closely related to the terrestrial ecosystem of land surface in global and regional scales.The development of AGCM and Regional Climate Model(RCM) play an important role for us to understand the relationship between climate change and terrestrial ecosystems change.In these models,the vegetation cover is key land surface parameter which impact on the exchange process between atmosphere and vegetation,including heat,water and CO2 etc. In this paper,the physical mechanisms of terrestrial vegetation cover classification methods were analyzed.And several global vegetation cover classification schemes were introduced;such as ground-based vegetation cover classification method,biome-climatic-based vegetation cover classification method(i.e.,Holdridge's scheme).Particularly,in recently the land surface proceeding experiments demonstrated that remote sensing data derived from NOAA-AVHRR,EOS-MODIS,Landsat-TM provide us with a powerful means,which we can monitor the dynamics of the global vegetation,vegetation classification and understand the real land cover condition in global scale with related high-resolution in time-space scales, and reveal the interaction between vegetation and climate in various temporal and spatial scales.The four land surface vegetation classifications schemes using remote sensing data were analyzed,including BATS(18types),SIB(9 types),SIB2(12 types) and BIOME-BGC(31types).In the end,the vegetation classification is discussed based on newly remote sensing satellite dataset.