Spatial Variation and Constraint Domain Selection of Remote Sensing Image Information Capacity

  • College of Urban and Environmental Science, Northwest University, Xi'an 710069, China

Received date: 2013-07-16

  Revised date: 2013-08-21

  Online published: 2014-01-05


Information capacity is a quantity unit of pixel density information. Center pixel and neighboring pixels will all be taken into account in the calculation of information capacity. The value of information capacity is closely related to the image gray levels. The more the gray level is, the greater the information capacity value will be. Thus, information capacity can objectively and effectively express land surface spatial structural information. However, the core issue of information capacity theory is the selection of the constraint domain and the determination of parameters. And appropriate setting of parameters is a key technology to ensure the accurateness of information capacity. In this study, 56 different landform areas of Shaanxi Province were selected as test areas, using the research result of remote sensing images in 2007 ETM + and 2008 SPOT5 as experimental data. According to this, two different calculation method of constraints domain in information capacity were adopted by using comparative analysis and mathematical statistics, which analyzed constraint domain selection and spatial distribution of the remote sensing image information capacity. All these experimental results show that information capacity can reflect the surface spatial structure complexity to a certain extent, and it exits a better linear relationship between information capacity and fractal dimension / information entropy, respectively. Information capacity also increases with the increase of fractal dimension and information entropy. Spatial distribution of information capacity is correlative with topographic feature of loess landform, as the same correlation with the surface spatial structure complexity of land cover types in the Central Shaanxi Plain. So, information capacity can be taken as a discriminate factor to identify the surface complexity.

Cite this article

WANG Xuhong, LI Fei, ZHANG zhe, QIN Huijie, LIU xiaoning, LI Gang . Spatial Variation and Constraint Domain Selection of Remote Sensing Image Information Capacity[J]. Journal of Geo-information Science, 2014 , 16(1) : 108 -116 . DOI: 10.3724/SP.J.1047.2014.00108


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