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Data warehouse means a decision support database allowing integration, organization, historisation, and management of data fromheterogeneous sources, with the aim of exploiting them for decision-making. Data warehouses are essentially based onmultidimensional model. This model organizes data into facts (subjects of analysis) and dimensions (axes of analysis). In classicaldata warehouses, facts are composed of numerical measures and dimensions which characterize it. Dimensions are organized intohierarchical levels of detail. Based on the navigation and aggregation mechanisms offered by OLAP (On-Line Analytical Processing)tools, facts can be analyzed according to the desired level of detail. In real world applications, facts are not always numerical, and canbe of qualitative nature. In addition, sometimes a human expert or learned model such as a decision tree provides a qualitativeevaluation of phenomenon based on its different parameters i.e. dimensions. Conventional data warehouses are thus not adapted toqualitative reasoning and have not the ability to deal with qualitative data. In previous work, we have proposed an original approachof qualitative data warehouse modeling, which permits integrating qualitative measures. Based on computing with wordsmethodology, we have extended classical multidimensional data model to allow the aggregation and analysis of qualitative data inOLAP environment. We have implemented this model in a Spatial Decision Support System to help managers of public spaces toreduce annoyances and improve the quality of life of the citizens. In this paper, we will focus our study on the representation andmanagement of imprecision in annoyance analysis process. The main objective of this process consists in determining the leastharmful scenario of urban building sites, particularly in dense urban environments

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

HANDLING IMPRECISION IN QUALITATIVE DATA WAREHOUSE: URBAN BUILDING SITES ANNOYANCE ANALYSIS USE CASE