Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information
ISPRS Journal of Photogrammetry and Remote SensingPublished 17 December 2003
U. Benz, Peter Hofmann, G. Willhauck, Iris Lingenfelder, Markus Heynen
Citations2,509
SJR quartileQ1
SJR score3.48
SNIP3.07
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TL;DR
Principal strategies of object-oriented analysis are explained, how the combination with fuzzy methods allows implementing expert knowledge and a representative example for the proposed workflow from remote sensing imagery to GIS are described.
Abstract
Remote sensing from airborne and spaceborne platforms provides valuable data for mapping, environmental monitoring, disaster management and civil and military intelligence. However, to explore the full value of these data, the appropriate information has to be extracted and presented in standard format to import it into geo-information systems and thus allow efficient decision processes. The object-oriented approach can contribute to powerful automatic and semi-automatic analysis for most remote sensing applications. Synergetic use to pixel-based or statistical signal processing methods explores the rich information contents. Here, we explain principal strategies of object-oriented analysis, discuss how the combination with fuzzy methods allows implementing expert knowledge and describe a representative example for the proposed workflow from remote sensing imagery to GIS. The strategies are demonstrated using the first object-oriented image analysis software on the market, eCognition, which provides an appropriate link between remote sensing imagery and GIS.
Keywords
Computer ScienceEngineering
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