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基于多源数据产品集成分类制作的青藏高原现状植被图
引用本文:张慧,赵涔良,朱文泉. 基于多源数据产品集成分类制作的青藏高原现状植被图[J]. 北京师范大学学报(自然科学版), 2021, 57(6): 816-824. DOI: 10.12202/j.0476-0301.2021171
作者姓名:张慧  赵涔良  朱文泉
作者单位:1.北京师范大学地理科学学部,遥感科学国家重点实验室,100875,北京
基金项目:第二次青藏高原综合科学考察研究资助项目(2019QZKK0606)
摘    要:充分利用多源植被分类/土地覆盖分类产品各自的优势,通过专门设计与青藏高原植被类型相适应的植被分类体系,选用集成分类方法,在数据可靠性的基础上遵循一致性的原则,制作了青藏高原现状植被图,其在现势性、分类体系的针对性和分类精度上均表现更优.从分类结果的现势性来看,青藏高原现状植被图较早期中国植被图能更好地反映青藏高原植被覆盖现状;从分类体系的针对性来看,青藏高原现状植被图采用了针对青藏高原植被专门设计的分类体系,有利于从多源数据产品中充分提取出具备高可靠性和一致性的植被覆盖信息;从分类精度来看,青藏高原现状植被图的总体精度(78.09%,Kappa系数0.75)较已有相关数据产品提高了18.84% ~ 37.17%,特别是对草地、灌丛等植被类型的分类精度有明显提升. 

关 键 词:青藏高原   植被类型   植被分类   土地覆盖   集成分类
收稿时间:2021-07-20

A new vegetation map for Qinghai-Tibet Plateau by integrated classification from multi-source data products
Affiliation:1.State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Aerospace Information Research Institute of Chinese Academy of Sciences, Faculty of Geographical Science, Beijing Normal University, 100875, Beijing , China2.Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, 100875,Beijing , China
Abstract:In this study, a vegetation classification system for the vegetation types in the Qinghai-Tibet Plateau was designed.The integrated classification method, taken into account of multi-source vegetation classification / land cover classification products, was used to produce the actual vegetation map.This integrated classification method followed the principle of data consistency, and the resultant vegetation map was superior over other vegetation maps in terms of reflection of current situation, classification system, and classification accuracy.This vegetation map is timely and could better reflect current vegetation distribution than earlier ones.This vegetation map could be conducive to fully extract vegetation information from multi-source data products with high reliability and consistency.Compared with previous data products, the overall accuracy (78.09%, kappa coefficient is 0.75) of this new vegetation map was found to increase by 18.84%-37.17%, especially for grassland and shrub. 
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