IGSNRR OpenIR
Enhancing Land Cover Mapping through Integration of Pixel-Based and Object-Based Classifications from Remotely Sensed Imagery
Chen, Yuehong1; Zhou, Ya'nan1; Ge, Yong2; An, Ru1; Chen, Yu3
2018
Source PublicationREMOTE SENSING
ISSN2072-4292
Volume10Issue:1Pages:15
Corresponding AuthorZhou, Ya'nan(zhouyn@hhu.edu.cn)
AbstractPixel-based and object-based classifications are two commonly used approaches in extracting land cover information from remote sensing images. However, they each have their own inherent merits and limitations. This study, therefore, proposes a new classification method through the integration of pixel-based and object-based classifications (IPOC). Firstly, it employs pixel-based soft classification to obtain the class proportions of pixels to characterize the land cover details from pixel-scale properties. Secondly, it adopts area-to-point kriging to explore the class spatial dependence between objects for each pixel from object-based soft classification results. Thirdly, the class proportions of pixels and the class spatial dependence of pixels are fused as the class occurrence of pixels. Last, a linear optimization model on objects is built to determine the optimal class label of pixels within each object. Two remote sensing images are used to evaluate the effectiveness of IPOC. The experimental results demonstrate that IPOC performs better than the traditional pixel-based hard classification and object-based hard classification methods. Specifically, the overall accuracy of IPOC is 7.64% higher than that of pixel-based hard classification and 4.64% greater than that of object-based hard classification in the first experiment, while the overall accuracy improvements in the second experiment are 3.59% and 3.42%, respectively. Meanwhile, IPOC produces less salt and pepper effect than the pixel-based hard classification method and generates more accurate land cover details and small patches than the object-based hard classification method.
Keywordland cover mapping mixed object uncertainty pixel-based classification object-based classification integration
DOI10.3390/rs10010077
WOS KeywordSATELLITE IMAGES ; ORIENTED METHODS ; SENSING IMAGERY ; LARGE AREAS ; ALGORITHM ; ACCURACY ; STRATEGY ; MODEL
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41701376] ; National Natural Science Foundation of China[41501453] ; Natural Science Foundation of Jiangsu Province[BK20170866] ; Key Program of Chinese Academy of Sciences[ZDRW-ZS-2016-6-3-4] ; Fundamental Research Funds for the Central Universities[2017B11714] ; Fundamental Research Funds for the Central Universities[2016B11414] ; China Postdoctoral Science Foundation[2016M600356] ; State Key Laboratory of Resources and Environmental Information System, China
Funding OrganizationNational Natural Science Foundation of China ; Natural Science Foundation of Jiangsu Province ; Key Program of Chinese Academy of Sciences ; Fundamental Research Funds for the Central Universities ; China Postdoctoral Science Foundation ; State Key Laboratory of Resources and Environmental Information System, China
WOS Research AreaRemote Sensing
WOS SubjectRemote Sensing
WOS IDWOS:000424092300076
PublisherMDPI AG
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/56946
Collection中国科学院地理科学与资源研究所
Corresponding AuthorZhou, Ya'nan
Affiliation1.Hohai Univ, Sch Earth Sci & Engn, Nanjing 210098, Jiangsu, 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.Nanjing Normal Univ, Sch Geog Sci, Nanjing 210023, Jiangsu, Peoples R China
Recommended Citation
GB/T 7714
Chen, Yuehong,Zhou, Ya'nan,Ge, Yong,et al. Enhancing Land Cover Mapping through Integration of Pixel-Based and Object-Based Classifications from Remotely Sensed Imagery[J]. REMOTE SENSING,2018,10(1):15.
APA Chen, Yuehong,Zhou, Ya'nan,Ge, Yong,An, Ru,&Chen, Yu.(2018).Enhancing Land Cover Mapping through Integration of Pixel-Based and Object-Based Classifications from Remotely Sensed Imagery.REMOTE SENSING,10(1),15.
MLA Chen, Yuehong,et al."Enhancing Land Cover Mapping through Integration of Pixel-Based and Object-Based Classifications from Remotely Sensed Imagery".REMOTE SENSING 10.1(2018):15.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Chen, Yuehong]'s Articles
[Zhou, Ya'nan]'s Articles
[Ge, Yong]'s Articles
Baidu academic
Similar articles in Baidu academic
[Chen, Yuehong]'s Articles
[Zhou, Ya'nan]'s Articles
[Ge, Yong]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Chen, Yuehong]'s Articles
[Zhou, Ya'nan]'s Articles
[Ge, Yong]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.