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Articles | Volume XXXVIII-4/W19
https://doi.org/10.5194/isprsarchives-XXXVIII-4-W19-131-2011
https://doi.org/10.5194/isprsarchives-XXXVIII-4-W19-131-2011
07 Sep 2012
 | 07 Sep 2012

DELINEATING PARAMETERS FOR OBJECT-BASED URBAN STRUCTURE MAPPING IN SANTIAGO DE CHILE USING QUICKBIRD DATA

A. Huck, S. Hese, and E. Banzhaf

Keywords: urban structure types (UST), object-based image analysis, Quickbird data, Santiago de Chile, land use/land cover, Risk Habitat Megacity

Abstract. This work aims to parameterize the urban structure types (UST) in Santiago de Chile on statistical block level. In connotation of remote sensing UST are defined as land-use structure entities. Central input data for this object-oriented approach is spatially very high resolution panfused and atmospherically corrected Quickbird data. To analyse and assess the structural properties of urban land- cover objects within block level entities, basic and robust land-cover class descriptions are developed. For enhanced class descriptions several image object scales are created. Based on defined UST and additional field data a set of test areas is selected for four municipalities assigned to different socio-spatial clusters in Santiago de Chile. In all test areas the distribution of the basic land- cover classes is parameterized using complex sub-object and relational image object descriptions. The central features to characterise the UST in this study are percentage area and density of subscale land-cover class objects. To carry out this analysis, the expert knowledge on UST is valuable to choose specific reference objects within the statistical block level. After the concept is implemented at the smallest scale, the approach can successfully be applied to the whole municipality once specific structural information are aggregated. The work is linked to activities of the project Risk Habitat Megacity and developed in close cooperation with the Helmholtz Centre for Environmental Research – UFZ in Leipzig, Germany. Finally, the resulting land-use structure entities will be linked to socio-spatial characteristics in the above mentioned cluster with respect to urban vulnerability.