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Multifractal analysis of resolution dependence in satellite imagery
Author(s) -
Gabriel P.,
Lovejoy S.,
Schertzer D.,
Austin G. L.
Publication year - 1988
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/gl015i012p01373
Subject(s) - multifractal system , brightness , remote sensing , satellite , image resolution , scale invariance , universality (dynamical systems) , radar , cloud fraction , cloud computing , physics , cloud cover , geology , statistical physics , fractal , mathematics , computer science , optics , statistics , astronomy , mathematical analysis , telecommunications , quantum mechanics , operating system
Augmenting a satellite's resolution reveals increasingly detailed structures that are found to occupy a decreasing fraction of the image, while simultaneously brightening to compensate. By systematically degrading the resolution of visible and infra red satellite cloud and surface data as well as radar rain data we define resolution‐independent co‐dimension functions that describe the spatial distribution of image features as well as the resolution dependence of the intensities themselves. The scale invariant functions so obtained fit into theoretically predicted universality classes. These multifractal techniques have implications for our ability to meaningfully estimate cloud brightness fraction, total cloud amount, as well as other remotely sensed quantities. A preliminary account of this work can be found in Gabriel et al., (1988a). See also Gabriel (1988).