Down-scaling LUCC based on the histo-variogram

来源 :Science in China(Series E:Technological Sciences) | 被引量 : 0次 | 上传用户:bchen2009
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In remote sensing applications,accurate extraction of land type area after classification is very impor-tant.But for images of land use/cover change(LUCC) obtained from the special spatial resolution re-mote sensing data,it will be of great significance to obtain the land type area information with higher resolution by making use of spatial distribution characteristcs information of the land type itself first and further scaling-down in a given scale threshold on the basis of the existing spatial resolution data.An explicit expression of the relationship between the measurement scale,global fractal dimension and the land type area corresponding to different measurement scales is obtained on the research basis of the authors’ histo-variogram using the standardized area index(SAI).A good attempt has been made to obtain the land type area information with higher resolution by merely using the spatial distribution characteristcs information of the land type in the image itself and further scaling-down in a given scale threshold on the basis of the existing spatial resolution data. In remote sensing applications, accurate extraction of land type area after classification is very impor- tant.But for images of land use / cover change (LUCC) obtained from the special spatial resolution re-mote sensing data, it will be of great significance to obtain the land type area information with higher resolution by making use of spatial distribution characteristcs information of the land type itself first and further scaling-down in a given scale threshold on the basis of the existing spatial resolution data. An explicit expression of the relationship between the measurement scale, global fractal dimension and the land type area corresponding to different measurement scales is obtained on the research basis of the authors’ histo-variogram using the standardized area index (SAI). A good attempt has been made to obtain the land type area information with higher resolution by merely using the spatial distribution characteristcs information of the land type in the image itself and further scaling-down in a given scale threshold on the basis of the existing spatial resolution data.
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