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Behnisch, M and Ultsch, A (2009) Urban data-mining: spatiotemporal exploration of multidimensional data. Building Research & Information, 37(05-06), 520–32.
- Type: Journal Article
- Keywords: building stock; data-mining; Geographic Information Science (GIS); spatiotemporal analysis; urban analysis
- ISBN/ISSN: 0961-3218
- URL: https://doi.org/10.1080/09613210903189343
- Abstract:
‘Urban data-mining’ describes a methodological approach to reveal logical or mathematical and partly complex descriptions of patterns and regularities inside a set of geospatial data. The cyclical methodology procedure is characterized by six main tasks following the initial step of data collection: data inspection, structure visualization, structure definition, structure control, operationalization, and knowledge conversion. Geovisualization and spatial analysis supplement the process of knowledge conversion and communication. The multidimensional mining approach is presented as a case study applied to 12 430 German communities to analyse multidynamic characteristics between 1994 and 2004. In particular, Emergent Self Organizing Maps (ESOM) are performed as an appropriate method for clustering and classification. Their advantage is to visualize the structure of data and later on to define a number of feasible clusters. A good evidence-base for decision-makers and the implementation of planning tools would be the spatiotemporal exploration of multidimensional data leading to specific details, explanations and abstractions in the context of dynamic community behaviour. The presented techniques are expected to be of increasing interest for the management and development of building stocks, as well as for urban and regional planning processes.
Brattebø, H, Bergsdal, H, Sandberg, N H, Hammervold, J and Müller, D B (2009) Exploring built environment stock metabolism and sustainability by systems analysis approaches. Building Research & Information, 37(05-06), 569–82.
Coffey, B, Borgeson, S, Selkowitz, S, Apte, J, Mathew, P and Haves, P (2009) Towards a very low-energy building stock: modelling the US commercial building sector to support policy and innovation planning. Building Research & Information, 37(05-06), 610–24.
Hasselaar, E (2009) Health issues and the building stock. Building Research & Information, 37(05-06), 669–78.
Hassler, U (2009) Long-term building stock survival and intergenerational management: the role of institutional regimes. Building Research & Information, 37(05-06), 552–68.
Mavrogianni, A, Davies, M, Chalabi, Z, Wilkinson, P, Kolokotroni, M and Milner, J (2009) Space heating demand and heatwave vulnerability: London domestic stock. Building Research & Information, 37(05-06), 583–97.
Meijer, F, Itard, L and Sunikka-Blank, M (2009) Comparing European residential building stocks: performance, renovation and policy opportunities. Building Research & Information, 37(05-06), 533–51.
Meinel, G, Hecht, R and Herold, H (2009) Analyzing building stock using topographic maps and GIS. Building Research & Information, 37(05-06), 468–82.
Salat, S (2009) Energy loads, CO2 emissions and building stocks: morphologies, typologies, energy systems and behaviour. Building Research & Information, 37(05-06), 598–609.
Steadman, P, Evans, S and Batty, M (2009) Wall area, volume and plan depth in the building stock. Building Research & Information, 37(05-06), 455–67.
Steemers, K and Yun, G Y (2009) Household energy consumption: a study of the role of occupants. Building Research & Information, 37(05-06), 625–37.
Tanikawa, H and Hashimoto, S (2009) Urban stock over time: spatial material stock analysis using 4d-GIS. Building Research & Information, 37(05-06), 483–502.