IMHE OpenIR  > 数字山地与遥感应用中心
Integrating MODIS and Landsat Data for Land Cover Classification by Multilevel Decision Rule
Guan, Xudong1; Huang, Chong2; Zhang, Rui3
Corresponding AuthorHuang, Chong(huangch@lreis.ac.cm)
2021-02-01
Source PublicationLAND
Volume10Issue:2Pages:18
AbstractIn some cloudy and rainy regions, the cloud cover is high in moderate-high resolution remote sensing images collected by satellites with a low revisit cycle, such as Landsat. This presents an obstacle for classifying land cover in cloud-covered parts of the image. A decision fusion scheme is proposed for improving land cover classification accuracy by integrating the complementary information of MODIS (Moderate-resolution Imaging Spectroradiometer) time series data with Landsat moderate-high spatial resolution data. The multilevel decision fusion method includes two processes. First, MODIS and Landsat data are pre-classified by fuzzy classifiers. Second, the pre-classified results are assembled according to their assessed performance. Thus, better pre-classified results are retained and worse pre-classified results are restrained. For the purpose of solving the resolution difference between MODIS and Landsat data, the proposed fusion scheme employs an object-oriented weight assignment method. A decision rule based on a compromise operator is applied to assemble pre-classified results. Three levels of data containing different types of information are combined, namely the MODIS pixel-level and object-level data, and the Landsat pixel-level data. The multilevel decision fusion scheme was tested on a site in northeast Thailand. The fusion results were compared with the single data source classification results, showing that the multilevel decision fusion results had a higher overall accuracy. The overall accuracy is improved by more than 5 percent. The method was also compared to the two-level combination results and a weighted sum decision rule-based approach. A comparison experiment showed that the multilevel decision fusion rule had a higher overall accuracy than the weighted sum decision rule-based approach and the low-level combination approach. A major limitation of the method is that the accuracy of some of the land covers, where areas are small, are not as improved as the overall accuracy.
Keywordimage classification decision fusion multi-temporal remote sensing
DOI10.3390/land10020208
Indexed BySCI
Language英语
Funding ProjectNational Science Foundation of China[41901309] ; Special Project of Lancang-Mekong River Cooperation of the Ministry of Science and Technology of the People's Republic of China ; CAS Light of West China Program ; Youth Talent Team Program of the Institute of Mountain Hazards and Environment, CAS[SDSQB-2020000032] ; Youth Talent Team Program of the Institute of Mountain Hazards and Environment, CAS[Y8R2230230] ; Agricultural Resources and Environmental Survey with Information Platform Construction in Lancang-Mekong River Basin
WOS Research AreaEnvironmental Sciences & Ecology
WOS SubjectEnvironmental Studies
WOS IDWOS:000622688600001
Funding OrganizationNational Science Foundation of China ; Special Project of Lancang-Mekong River Cooperation of the Ministry of Science and Technology of the People's Republic of China ; CAS Light of West China Program ; Youth Talent Team Program of the Institute of Mountain Hazards and Environment, CAS ; Agricultural Resources and Environmental Survey with Information Platform Construction in Lancang-Mekong River Basin
PublisherMDPI
Citation statistics
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/56023
Collection数字山地与遥感应用中心
山地灾害与地表过程重点实验室
Corresponding AuthorHuang, Chong
Affiliation1.Chinese Acad Sci, Res Ctr Digital Mt & Remote Sensing Applicat, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
3.Chinese Acad Sci, Inst Mt Hazards & Environm, Key Lab Mt Hazards & Earth Surface Proc, Chengdu 610041, Peoples R China
Recommended Citation
GB/T 7714
Guan, Xudong,Huang, Chong,Zhang, Rui. Integrating MODIS and Landsat Data for Land Cover Classification by Multilevel Decision Rule[J]. LAND,2021,10(2):18.
APA Guan, Xudong,Huang, Chong,&Zhang, Rui.(2021).Integrating MODIS and Landsat Data for Land Cover Classification by Multilevel Decision Rule.LAND,10(2),18.
MLA Guan, Xudong,et al."Integrating MODIS and Landsat Data for Land Cover Classification by Multilevel Decision Rule".LAND 10.2(2021):18.
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