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A Quantitative Characterization of Spatial Structure Features of Typical Urban Land Cover Types Using Morphological Method
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
Beijing University.
2006 (English)In: IEEE International Geoscience and Remote Sensing Symposium, 2006, 3714-3716 p.Conference paper (Other academic)
Abstract [en]

The analysis of spatial structure features in high resolution imagery is one of the most important research fields in remote sensing information processing. In this study, we attempt to quantitatively describe the differences of some spatial structure features of the selected urban land cover(use) types in 0.61-metre resolution Quickbird panchromatic imagery using morphological method. Gray-scale granulometry based on opening of each selected land use type with discs of increasing size provided a size distribution which indicates the prevailing sizes of the image structures and the corresponding volume measurement (sum of grey levels of all image pixels) losses at these sizes which are normalized. A series of directional openings with linear structuring elements were applied for each land use type and the predominant orientation of the land use type Was obtained by selecting the direction in which the volume measurement was maximal when opening was used. Also the strength of the predominant orientation information was obtained. Clear distinctions among different kinds of selected urban land use types were presented through the previously obtained prevailing sizes, normalized volume losses at these sizes, predominant orientation and its strength. It shows that these variables which reflect the size and orientation information could be integrated to characterize spatial structure features of urban land use types, which can be used in the extraction of some land use types from high resolution images.

Place, publisher, year, edition, pages
2006. 3714-3716 p.
National Category
Remote Sensing
URN: urn:nbn:se:kth:diva-89431ISI: 000237237604180OAI: diva2:503024
QC 20120307Available from: 2012-02-14 Created: 2012-02-14 Last updated: 2012-03-07Bibliographically approved

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Hu, Hongtao
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Geoinformatics (closed 20110301)
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