Application of artificial neural networks on extracting permafrost information

  • Jiujun Lv*
  • , Yuanman Hu
  • , Xiuzhen Li
  • , Xianwei Wang
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A back propagation artificial neural network was used to extract permafrost information in Huzhong National Nature Reserve, China. 400 field sites of permafrost information were investigated as training sites for the network and accuracy test for the classification results. Different combinations of input sources were used as training layers for the network, which included land cover, equivalent latitude, aspect, and radar image. Results of permafrost classification suggest that the neural network is available in the study area. The best combination to extract permafrost information includes land cover, equivalent latitude and radar image. But aspect may have little use in classifications of permafrost in the area.

Original languageEnglish
Title of host publicationProceedings - 4th International Conference on Natural Computation, ICNC 2008
Pages91-94
Number of pages4
DOIs
StatePublished - 2008
Externally publishedYes
Event4th International Conference on Natural Computation, ICNC 2008 - Jinan, China
Duration: 18 Oct 200820 Oct 2008

Publication series

NameProceedings - 4th International Conference on Natural Computation, ICNC 2008
Volume4

Conference

Conference4th International Conference on Natural Computation, ICNC 2008
Country/TerritoryChina
CityJinan
Period18/10/0820/10/08

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