Within urban areas, green spaces play a critically important role in the quality of life. They have remarkable impact on the local microclimate and the regional climate of the city. Quantifying the ‗greenness' of urban areas allows comparing urban areas at several levels, as well as monitoring the evolution of green spaces in urban areas, thus serving as a tool for urban and developmental planning. Different categories of vegetation have different impacts on recreation potential and microclimate, as well as on the individual perception of green spaces. However, when quantifying the ‗greenness' of urban areas the reliability of the underlying information is important in order to qualify analysis results. The reliability of geo-information derived from remote sensing data is usually assessed by ground truth validation or by comparison with other reference data. When applying methods of object based image analysis (OBIA) and fuzzy classification, the degrees of fuzzy membership per object in general describe to what degree an object fits (prototypical) class descriptions. Thus, analyzing the fuzzy membership degrees can contribute to the estimation of reliability and stability of classification results, even when no reference data are available. This paper presents an object based method using fuzzy class assignments to outline and classify three different classes of vegetation from GeoEye imagery. The classification result, its reliability and stability are evaluated using the reference-free parameters Best Classification Result and Classification Stability as introduced by Benz et al. in 2004 and implemented in the software package eCognition OPEN ACCESS

The first generation of digital, and subsequently online, regional atlases did only little to reconceptualize the idea behind this established cartographic category. Using the case study of a regional atlas for Central Asia, the authors propose a fundamental re-thinking as a usercentric and target-group-specific front end for emerging Spatial Data Infrastructures. 'Next generation' regional atlases are anticipated as open frameworks based upon distributed online services; extensible, mashable, and modifiable, flexibly adjusting to situated devices.Regional or national atlases rarely followed established principles or modelled after some blueprint, but were often tied to research initiatives resulting in unique and even outstanding products. Examples are the Salzburg-Atlas (LENDL et al. 1955), pioneering the use GI_Forum -Journal for Geographic Information Science, 1-2015. © Herbert Wichmann Verlag, VDE VERLAG GMBH, Berlin/Offenbach. ISBN 978-3-87907-558-4. © ÖAW Verlag, Wien.