Abstract
The construction industry relies on construction cost indexes to prepare cost estimate benchmarks and develop cost estimates. Subsequently, government agencies, non-profit organizations, and private companies routinely publish construction cost indexes for cities. Currently, all construction cost indexes are released in a tabular format for 649 cities across the conterminous United States, which is not effective in illustrating construction cost variations at the national level. This study explored the utility of various established interpolation methods and mapping techniques to visualize construction cost indexes at the national level. Geovisualization techniques such as thematic mapping provide a visual representation of construction cost data in addition to traditional tabular formats. This study explored the utility of Thiessen polygon and inverse distance weighted (IDW) methods to create thematic maps which can be used to interactively visualize construction costs at the national level. A qualitative comparison revealed that the IDW method can produce the most intuitive, interactive, and continuous surface maps to identify dynamic and previously unrecognized patterns. These continuous surface maps allow construction practitioners and academics, real estate developers, and the public to locate the geographic proximity of high or low construction costs while cost change maps allow investors and businesses to identify patterns in changing construction costs over a certain period. This work contributes to the body of knowledge by introducing interpolated maps for visualizing any construction cost-related indexes at a large scale such as the national level.
Highlights
The construction industry plays a key role in a country’s economy, in addition to producing physical structures that increase productivity and quality of life [1,2]
This research used the city cost index (CCI) as an example of construction costs for mapping, other costs related to construction or costs that contribute to the CCI, such as equipment, material, or labor costs can be interpolated and mapped at the national level
This study investigated the potential of various interpolation methods to visualize construction costs at the national level
Summary
The construction industry plays a key role in a country’s economy, in addition to producing physical structures that increase productivity and quality of life [1,2]. More details regarding NN, CNN, and IDW are discussed in the methodology section These three methods hold the potential to effectively and efficiently visualize CCI values at the national level via a series of maps to reveal spatial-temporal patterns that have traditionally been impossible to reveal by a tabular format. This is because, fundamentally, the CCI is geospatial data, i.e., a combination of location information (coordinates that define a specific feature, in this case, a specific city); attribute information (the characteristics that define a specific feature, in this case, a specific city); and temporal information (when the data are being collected, edited, and distributed). The intent of this study is to examine whether construction cost data can be mapped from NN, CNN, and IDW methods to exhibit their spatial-temporal patterns, and if so, to determine which method produces the most intuitive and interactive maps to assist construction practitioners and academics, real estate developers, investors and businesses, and the public in identifying dynamic and previously unrecognized patterns
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