Wang Jiao1; Cheng Weiming2; Zhou Chenghu2; Zheng Xinqi1
Source Publicationjournalofgeographicalsciences
AbstractDeveloping approaches to automate the analysis of the massive amounts of data sent back from the Moon will generate significant benefits for the field of lunar geomorphology. In this paper, we outline an automated method for mapping lunar landforms that is based on digital terrain analysis. An iterative self-organizing (ISO) cluster unsupervised classification enables the automatic mapping of landforms via a series of input raster bands that utilize six geomorphometric parameters. These parameters divide landforms into a number of spatially extended, topographically homogeneous segments that exhibit similar terrain attributes and neighborhood properties. To illustrate the applicability of our approach, we apply it to three representative test sites on the Moon, automatically presenting our results as a thematic landform map. We also quantitatively evaluated this approach using a series of confusion matrices, achieving overall accuracies as high as 83.34% and Kappa coefficients (K) as high as 0.77. An immediate version of our algorithm can also be applied for automatically mapping large-scale lunar landforms and for the quantitative comparison of lunar surface morphologies.
Document Type期刊论文
Recommended Citation
GB/T 7714
Wang Jiao,Cheng Weiming,Zhou Chenghu,et al. automaticmappingoflunarlandformsusingdemderivedgeomorphometricparameters[J]. journalofgeographicalsciences,2017,27(11):1413.
APA Wang Jiao,Cheng Weiming,Zhou Chenghu,&Zheng Xinqi.(2017).automaticmappingoflunarlandformsusingdemderivedgeomorphometricparameters.journalofgeographicalsciences,27(11),1413.
MLA Wang Jiao,et al."automaticmappingoflunarlandformsusingdemderivedgeomorphometricparameters".journalofgeographicalsciences 27.11(2017):1413.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Wang Jiao]'s Articles
[Cheng Weiming]'s Articles
[Zhou Chenghu]'s Articles
Baidu academic
Similar articles in Baidu academic
[Wang Jiao]'s Articles
[Cheng Weiming]'s Articles
[Zhou Chenghu]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Wang Jiao]'s Articles
[Cheng Weiming]'s Articles
[Zhou Chenghu]'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.