Mapping land cover of the yellow river source using multitemporal landsat images

Yong Hu, Liangyun Liu, Lingling Liu, Quanjun Jiao, Jianhua Jia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Land cover is a crucial product required to be calibrated, validated and used in various land surface models that provide the boundary conditions for the simulation of climate, carbon cycle and ecosystem change. This paper presented a method to map land cover from multitemporal landsat images using Dempster-Shafer theory of evidence. The method firstly resolved in Gaussian probability density function calculate the basic probability assignment of each single satellite image, then multitemporal landsat images were combined using Dempster's Rule of combination. Finally, a decision rule based on ancillary information is used to make classification decisions. This method had 87.91% overall accuracy for the land cover types compared with the result of the Aerial hyperspectral image classification. The results of this study showed that Dempster-Shafer theory of evidence is an effective tool to map land cover using multitemporal landsat image.

Original languageEnglish (US)
Title of host publicationRemote Sensing of the Environment
Subtitle of host publicationThe 17th China Conference on Remote Sensing
DOIs
StatePublished - 2011
Externally publishedYes
EventRemote Sensing of the Environment: The 17th China Conference on Remote Sensing - Hangzhou, China
Duration: Aug 27 2010Aug 31 2010

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8203
ISSN (Print)0277-786X

Conference

ConferenceRemote Sensing of the Environment: The 17th China Conference on Remote Sensing
Country/TerritoryChina
CityHangzhou
Period8/27/108/31/10

Keywords

  • Dempster-Shafer theory
  • Land cover
  • Multitemporal
  • Yellow river source

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