Employing Crowdsourced Geographic Information to Classify Land Cover with Spatial Clustering and Topic Model

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Summary

This paper investigates a faster and more automated method that does not require remotely sensed images for land cover classification and achieves an overall accuracy of approximately 80%, providing evidence that CGI with textual information has a great potential forLand cover classification.

Type
article
Published
2017-06-13
Cited by
23
References
35
Access
Open access

Keywords

Land cover, Crowdsourcing, Computer science, Cover (algebra), Cluster analysis

References

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