IMHE OpenIR  > 数字山地与遥感应用中心
Land Cover Mapping in Southwestern China Using the HC-MMK Approach
Lei, Guangbin1,2; Li, Ainong1; Bian, Jinhu1,2; Zhang, Zhengjian1; Jin, Huaan1; Nan, Xi1; Zhao, Wei1; Wang, Jiyan1,2; Cao, Xiaomin1,2; Tan, Jianbo1,2; Liu, Qiannan1,2; Yu, Huan3; Yang, Guangbin4; Feng, Wenlan5
Corresponding AuthorLi, Ainong
2016
Source PublicationREMOTE SENSING
EISSN2072-4292
Volume8Issue:4Pages:DOI: 10.3390/rs8040305
SubtypeArticle
AbstractLand cover mapping in mountainous areas is a notoriously challenging task due to the rugged terrain and high spatial heterogeneity of land surfaces as well as the frequent cloud contamination of satellite imagery. Taking Southwestern China (a typical mountainous region) as an example, this paper established a new HC-MMK approach (Hierarchical Classification based on Multi-source and Multi-temporal data and geo-Knowledge), which was especially designed for land cover mapping in mountainous areas. This approach was taken in order to generate a 30 m-resolution land cover product in Southwestern China in 2010 (hereinafter referred to as CLC-SW2010). The multi-temporal native HJ (HuanJing, small satellite constellation for disaster and environmental monitoring) CCD (Charge-Coupled Device) images, Landsat TM (Thematic Mapper) images and topographical data (including elevation, aspect, slope, etc.) were taken as the main input data sources. Hierarchical classification tree construction and a five-step knowledge-based interactive quality control were the major components of this proposed approach. The CLC-SW2010 product contained six primary categories and 38 secondary categories, which covered about 2.33 million km(2) (accounting for about a quarter of the land area of China). The accuracies of primary and secondary categories for CLC-SW2010 reached 95.09% and 87.14%, respectively, which were assessed independently by a third-party group. This product has so far been used to estimate the terrestrial carbon stocks and assess the quality of the ecological environments. The proposed HC-MMK approach could be used not only in mountainous areas, but also for plains, hills and other regions. Meanwhile, this study could also be used as a reference for other land cover mapping projects over large areas or even the entire globe.
KeywordLand Cover Mapping Hierarchical Classification Knowledge Quality Control Multi-source Data Hc-mmk Approach Clc-sw2010 Product Southwestern China
WOS HeadingsScience & Technology ; Technology
DOI10.3390/rs8040305
URL查看原文
WOS Subject ExtendedRemote Sensing
Indexed BySCI
WOS KeywordREMOTE-SENSING DATA ; TIME-SERIES ; CLASSIFICATION ; VEGETATION ; FORESTS ; SUPPORT ; INDEX ; BIODIVERSITY ; ALGORITHM ; DATABASE
Language英语
Quartile2区
TOP
WOS SubjectRemote Sensing
WOS IDWOS:000375156500038
Funding OrganizationStrategic Leader Science and Technology project(XDA05050105) ; "Ecology decade" specific project of MEPCAS(STSN-01-04) ; International Cooperation Key Project of CAS(GJHZ201320) ; National Natural Science Foundation of China(41271433 ; 41571373)
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Cited Times:22[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/17385
Collection数字山地与遥感应用中心
Affiliation1.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Chengdu Univ Technol, Coll Earth Sci, Chengdu 610059, Peoples R China
4.Guizhou Normal Univ, Sch Geog & Environm Sci, Guiyang 550001, Peoples R China
5.Chengdu Univ Informat Technol, Coll Resources & Environm, Chengdu 610225, Peoples R China
First Author Affilication中国科学院水利部成都山地灾害与环境研究所
Recommended Citation
GB/T 7714
Lei, Guangbin,Li, Ainong,Bian, Jinhu,et al. Land Cover Mapping in Southwestern China Using the HC-MMK Approach[J]. REMOTE SENSING,2016,8(4):DOI: 10.3390/rs8040305.
APA Lei, Guangbin.,Li, Ainong.,Bian, Jinhu.,Zhang, Zhengjian.,Jin, Huaan.,...&Feng, Wenlan.(2016).Land Cover Mapping in Southwestern China Using the HC-MMK Approach.REMOTE SENSING,8(4),DOI: 10.3390/rs8040305.
MLA Lei, Guangbin,et al."Land Cover Mapping in Southwestern China Using the HC-MMK Approach".REMOTE SENSING 8.4(2016):DOI: 10.3390/rs8040305.
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