Abstract
In the CR (Czech Republic), there are a lot of prefabricated housing estates built in the 70s and 80s of the 20th century, which are at the end of their life cycle. The main goal of the project was to evaluate the rate of energy savings in the long term due to the revitalization of prefabricated apartment buildings, and thus provide feedback to the relevant authorities on its effectiveness. Another goal was to evaluate selected parameters of living comfort in the locality for the purposes of the real estate market with the possibility of providing them to those interested in living in the locality. A complex of methods was used, which evaluate criteria from various spheres, such as environment, spatial relationships, social aspects, etc. The authors used a combination of multi-criterial analysis methods (MCA) and spatial analysis within a Geographical Information System (GIS). Of all MCA methods, weighted linear combination (WLC) was chosen as the most suitable. In the spatial analyses, the matter of solution was, above all, the distance to the center and the transport within the given locality. The above-mentioned methods served as a model for evaluating whether a panel house in question is or is not suitable for reconstruction. The input data of the model are spatial data—national map series of the CR, environmental data (noise maps, energy demands of buildings)—and statistical data obtained from various sources (city administration of Brno, relevant organizations, and interviews with respondents). Within Inquiry Form 3, potential groups of respondents were addressed: Group A—people over fifty, group B—young families with children, group C—students under 25. The projected model was tested in Brno city in the locality of Nový Lískovec (CR). The proposed model provided information on the quality of housing in a given locality in terms of energy intensity, noise pollution, transport accessibility, and civic amenities. The output is a multi-criteria model with GIS support, which is generally applicable. The results of the model analyses led to the demonstration of the effectiveness of revitalization. The results can be used for estate offices or other organizations in the form of graphical outputs of appropriate variants on the basis of solving a lot of criteria when searching for a suitable residence.
Highlights
In the Czech Republic (CR), there are many prefabricated houses from the 1970s or 1980s, which are conceptually obsolete from the point of view of modern times and, in many aspects, no longer meet current standards of modern living
We focus mainly on the parameters of energy savings, noise pollution of the site caused mainly by traffic, and spatial analysis based on questionnaire surveys, as well as creating a model combined with multi-criterial analysis (MCA) and weighted linear combination (WLC) for use in the real estate market
It has been shown that a significant part of the costs can be saved by introducing metering systems for sub-households in the building, which leads to significant overall energy savings in both central heating and hot water consumption
Summary
In the Czech Republic (CR), there are many prefabricated houses from the 1970s or 1980s, which are conceptually obsolete from the point of view of modern times and, in many aspects, no longer meet current standards of modern living. As the demands for permanent housing are constantly growing, the problem of whether it is preferable to reconstruct existing buildings or to build a new housing developments was solved. According to Reference [1], the first method, i.e., reconstruction of existing prefabricated buildings, is more economical. The main emphasis here is mainly on the energy performance of buildings and the economics of operation. To evaluate selected parameters in the locality related to the attractiveness of housing in terms of housing costs (energy), transport services, amenities, and noise pollution for the purposes of the real estate market, with the possibility of presenting results to those interested in living in the locality
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