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Proceedings Paper

Key technologies of land use information extraction based upon multisource remote sensing data: a case study of hilly-plain transition region in the middle and lower reaches of the Yellow River
Author(s): Heli Lu; Guifang Liu
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Paper Abstract

It was a trend that image was classified through combining multi-source remote sensing data with non-remote sensing data by GIS technology. In this paper, technological framework of land use information extraction was established using multi-sources remote sensing data (TM and CBERS-02B), DEM, slope data, land use map and other geographic auxiliary data. The result showed :( 1) It was possible to combine TM and CBERS-02B as land use sources data because of their similar spatial resolution and spectral resolution. In this research the method of multi-level supervised classification was adopted. (2) Interpretation accuracy was improved by establishing background database through GIS technology. First, non-remote sensing information, such as topographic map, soil map, land-use map, transportation map, etc, was integrated as background database. Then land use classifications were overlapped with above database. The results showed that uncertainty could reduce by 23.2%. (3) In the study area dry land spectrums in plain area, hilly area and the Yellow River flood plain were very different and spectrums of habitation in plain and the Yellow River land wash were the same. As for above phenomenon of "same object with different spectrums" and "different objects with same spectrum", expert knowledge database was established based upon relationship between remote sensing image and geographical environment. As a result average classification accuracy was improved by 12.1%.

Paper Details

Date Published: 13 November 2010
PDF: 8 pages
Proc. SPIE 7857, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications III, 785712 (13 November 2010); doi: 10.1117/12.869066
Show Author Affiliations
Heli Lu, Henan Univ. (China)
United Nations Univ. (Japan)
Guifang Liu, Henan Univ. (China)


Published in SPIE Proceedings Vol. 7857:
Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications III
Allen M. Larar; Hyo-Sang Chung; Makoto Suzuki, Editor(s)

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