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  • 1
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    Publication Date: 2019-07-12
    Description: A method that measures the spatial structure of images as a function of spatial resolution is presented for selecting the appropriate scale for remote sensing. Graphs are obtained by imaging the scene at fine resolution and then collapsing the image to successively coarser resolutions while calculating the local variance. For the spatial resolution of SPOT and TM imagery, local image variance is relatively high for forested and urban/suburban environments, indicating that information-extraction techniques using texture, context, and mixture modeling are appropriate for these sensor systems. For agricultural environments where local variance is low, more traditional classifiers are appropriate.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: Remote Sensing of Environment (ISSN 0034-4257); 21; 311-332
    Format: text
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  • 2
    Publication Date: 2019-07-12
    Description: Theoretical and empirical studies of variograms are presented. The sensitivity of variograms is studied through varyig parameters of scene models both in calculating explicit variograms and in simulating images. It is found that the heights of variograms are related to the proportion of an area covered by objects. It is shown that the range of influence of a variogram is related to the size of the objects in the scene and that the shape of the variogram becomes more rounded as the variance in the size distribution of objects increases. In the second part, empirically calculated variograms from real digital images are used to demonstrate these theoretical findings. These calculated variograms also show the periodicity in ground scenes and reveal anisotropy.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: Remote Sensing of Environment (ISSN 0034-4257); 25; 323-379
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  • 3
    Publication Date: 2019-07-13
    Description: Simulated forest and observed TM and SPOT images illustrate the improvements an adaptive-window texture image can have over traditional texture images for applications like image segmentation where edge effects in the texture image can be detrimental. By adaptive selection of the 'best' window position (as opposed to always having the window centered over the pixel) minimizes edge effects while retaining local texture information. Tests using 3 x 3 windows and local variance on SPOT, TM and simulated TM data show similar results.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: 1989 ASPRS/ACSM Annual Convention; Apr 02, 1989 - Apr 07, 1989; Baltimore, MD; United States
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