A GIS-based Bottom-up Building Archetype Development Approach for the Middle Eastern Building Stock
Abstract
Globally, residential buildings have a significant potential where greenhouse gas emissions can be reduced by lowering the energy and material demands. Bottom-up building stock modeling approaches facilitate detecting these demands and can be applied in various dimensions by taking individual building characteristics into account. However, it is not feasible to model and simulate every single building in a country’s stock in detail. Archetype modeling is a widely implemented method used in bottom-up approaches, categorizing similar buildings based on different factors under overarching representative types and extrapolating them across country or region levels. In this way, the number of buildings in focus decreased by preserving their notable characteristics. However, identifying archetypes for broader extents is often a challenging and complex process considering that residential buildings differ across countries and are highly dependent on the localized characteristics. These characteristics are shaped by the complicated interplay of physical (i.e., climate, local materials, topography), technological, economic, societal, and political factors. The representativeness of archetypes is crucial for reflecting the emissions rooted in countries’ building stock and is directly proportional to how successfully they address these factors. A more facilitating methodology for characterization factor identification in archetype development is needed to represent broader scales better. On the other hand, while several established archetype models representing the European and Northern American building stock exist, the modeling attempts are not resonated well in the Middle Eastern region. The Middle East hosts many oil-producing countries, and fossil-fuel-based energy sources are quite common and cheaper. Considering the increasing population rates, abnormalities in climate, and overheating in the buildings due to global warming, the region’s building stock is required to be holistically examined with the help of good archetype models. GIS environments offer multifaceted and geo-spatially linked data compilation, query, management, and visualization features that may be a guiding platform to lower the complexity of archetype development and characterization issues for the region. The study discusses the possibilities and advantages of GIS environments’ advanced data handling and visualization capabilities that may facilitate the archetype creation processes over a case study for the Middle East region. In this regard, the regions’ specific population, GDP, climate characteristics, residential building densities, primary construction materials are compiled, stored in different layers, and visualized in a GIS platform as the main drivers of the archetype characterization process. The presented approach provides an integrated platform where various data types can be stored, filtered, and visualized in different layers simultaneously and may help to find similarities and dissimilarities between each pair of building characteristics across countries to support archetype development processes.
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