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Proceedings Paper

Mapping urban green from IKONOS data by an object-oriented knowledge-base and fuzzy logic
Author(s): Demetre P. Argialas; Panos Derzekos
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Paper Abstract

Urban green is recognized as an important functional element of the city, which affects directly the standard of living. The present paper is concerned with the study of urban green by means of object-oriented image analysis of high-resolution IKONOS data. More specifically, the potential for detecting urban green and quantitatively assessing it was explored. The analysis included two levels of segmentation and classification. On the first level, objects to which the image was segmented were subsequently classified according to a vegetation index (Scaled MSAVI) to areas with dense, thin or no vegetation. On the second level the image was classified in larger areas that simulated building blocks according to the relative area of vegetation, in order to create a thematic map of urban green density. The evaluation of the results indicated that detection and quantitative assessment of urban green was achieved with satisfactory accuracy. The use of additional data (DEM, hyperspectral, GIS) will allow a more detail study of the urban green from high resolution data by means of object-oriented image analysis

Paper Details

Date Published: 14 March 2003
PDF: 11 pages
Proc. SPIE 4886, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology II, (14 March 2003); doi: 10.1117/12.463281
Show Author Affiliations
Demetre P. Argialas, National Technical Univ. of Athens (Greece)
Panos Derzekos, National Technical Univ. of Athens (Greece)


Published in SPIE Proceedings Vol. 4886:
Remote Sensing for Environmental Monitoring, GIS Applications, and Geology II
Manfred Ehlers, Editor(s)

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