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City Dorset / Southampton / / Company Ordnance Survey / Pearson / International Journal / National Grid / / Country Netherlands / United Kingdom / / / Facility University of Southampton / / IndustryTerm ecological applications / supervised fuzzy c-means algorithm / spatial resolution satellite sensor imagery using super-resolution pixel-swapping / improved processing / Hard classification algorithms / soft classification algorithms / sensed satellite imagery / inverse-distance weighting algorithm / real satellite sensor imagery / pixel-swapping algorithm / classification algorithms / post-processing / related applications / spatial resolution satellite sensor imagery / satellite sensor imagery / geostatistical tools / simulated satellite sensor imagery / be represented using geostatistical tools / / Organization School of Geography / University of Southampton / national mapping agency / / Person Ai / / / Position *Corresponding author / Fisher / representative / / Technology radiation / Remote Sensing / inverse-distance weighting algorithm / pixel-swapping algorithm / Hard classification algorithms / GPS / classification algorithms / supervised fuzzy c-means algorithm / Two soft classification algorithms / Two algorithms / collected using a differential GPS / / URL http /
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International Journal of Remote Sensing Vol. 27, No. 3, 10 February 2006, 473–491 Sub-pixel mapping of rural land cover objects from fine spatial resolution satellite sensor imagery using super-resolution pixel-swappin