Mapping land cover of the Yellow River source using multi-temporal Landsat images

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

doi:10.1117/12.910403

15 August 2011 Mapping land cover of the Yellow River source using multi-temporal Landsat images

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

Proceedings Volume 8203, Remote Sensing of the Environment: The 17th China Conference on Remote Sensing; 82030P (2011) https://doi.org/10.1117/12.910403
Event: Seventeenth China Symposium on Remote Sensing, 2010, Hangzhou, China

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.

Citation Download Citation

Yong Hu, Liangyun Liu, Lingling Liu, Quanjun Jiao, and Jianhua Jia "Mapping land cover of the Yellow River source using multi-temporal Landsat images", Proc. SPIE 8203, Remote Sensing of the Environment: The 17th China Conference on Remote Sensing, 82030P (15 August 2011); https://doi.org/10.1117/12.910403

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KEYWORDS

Earth observing sensors

Image classification

Landsat

Climate change

Probability theory

Hyperspectral imaging

Remote sensing

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