# Mapping Construction Costs at the National Level

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## Abstract

**:**

## 1. Introduction

## 2. Materials and Methods

#### 2.1. Construction Cost Data Collection

#### 2.2. Interpolation Methods

_{j}, are estimated by:

_{ij}is the distance from known point i to unknown point j, Z

_{i}is the value for the known point i, and n is a user defined exponent, which controls how quickly a point’s influence decreases with distance [20]. According to the previous study, a value of 2 should be used for n, and the search radius should be limited to 10 neighboring points [16]. The output cell size (grid resolution) should be 1 km. Figure 4 shows an interpolated surface map produced by the IDW method.

#### 2.3. Selection of Interpolation Method for Mapping

#### 2.4. Mapping Construction Cost

## 3. Results and Discussion

## 4. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**The 649 CCI cities in the conterminous U.S. and their CCI (city cost index) values in 2015.

**Figure 2.**A 2015 construction cost map at the national level created by using the NN (nearest neighbor) method.

**Figure 3.**Construction cost map at the national level created by using the CNN (conditional nearest neighbor) method.

**Figure 4.**Construction cost map at the national level created by using the IDW (inverse distance weighted) method.

**Figure 5.**Multiple construction cost maps at the national level created using the IDW interpolation method.

**Figure 6.**Multiple construction cost maps at the national level showing construction cost difference; (

**a**) indicates construction cost difference in one year (2015 value minus 2014 value); (

**b**) indicates construction cost difference in two years (2015 value minus 2013 value); (

**c**) indicates construction cost difference in five years (2015 value minus 2010 value); (

**d**) indicates construction cost difference in ten years (2015 value minus 2005 value).

State | City | Material | Installation | Total |
---|---|---|---|---|

Alabama | Birmingham | 97.4 | 75.2 | 87.6 |

Tuscaloosa | 96.0 | 60.2 | 80.2 | |

Jasper | 96.3 | 58.5 | 79.6 | |

Decatur | 96.0 | 61.8 | 80.9 | |

Huntsville | 96.0 | 70.1 | 84.6 | |

Gadsden | 95.9 | 59.2 | 79.7 | |

Montgomery | 97.1 | 58.3 | 80.0 | |

Anniston | 95.2 | 67.0 | 82.8 | |

Dothan | 95.9 | 53.7 | 77.3 | |

Evergreen | 95.4 | 55.6 | 77.8 | |

Mobile | 97.1 | 67.4 | 84.0 | |

Selma | 95.6 | 53.5 | 77.0 | |

Phoenix City | 96.4 | 57.2 | 79.1 | |

Butler | 95.8 | 53.9 | 77.3 | |

Arizona | Phoenix | 99.9 | 74.6 | 88.7 |

Mesa/Tempe | 99.4 | 64.4 | 83.9 | |

Globe | 99.5 | 60.5 | 82.3 | |

Tucson | 98.2 | 69.9 | 85.7 | |

Show Low | 99.6 | 61.6 | 82.8 | |

Flagstaff | 101.6 | 70.4 | 87.9 | |

Prescott | 99.1 | 61.1 | 82.4 | |

Kingman | 97.2 | 67.9 | 84.3 | |

Chambers | 97.3 | 61.8 | 81.6 |

Methods | Advantages | Disadvantages |
---|---|---|

NN | Fast and easy to calculate | Less accurate |

Widely adopted by the construction industry to conduct cost estimates | Lack of variation within the polygon; no use of state boundary | |

Can estimate CCI values for all cities at the national level | Rough surfaces for the interpolated CCI values | |

CNN | More accurate | Slow and difficult to calculate |

Consider state policies’ and regulations’ impact on cost variation | Lack of variation within the polygon | |

Can estimate CCI values for all cities at the national level | Rough surfaces for the interpolated CCI values | |

IDW | More accurate | Slow and difficult to calculate |

Smooth surfaces for the interpolated CCI values which provide a more intuitive look to identify patterns | More parameters such as power to consider and test prior to deployment | |

Can estimate CCI values for all cities at the national level | Unable to consider state policies’ impact on cost variation |

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## Share and Cite

**MDPI and ACS Style**

Zhang, S.; Lippitt, C.D.; Bogus, S.M.; Taylor, T.D.; Haley, R.
Mapping Construction Costs at the National Level. *Geographies* **2022**, *2*, 132-144.
https://doi.org/10.3390/geographies2010009

**AMA Style**

Zhang S, Lippitt CD, Bogus SM, Taylor TD, Haley R.
Mapping Construction Costs at the National Level. *Geographies*. 2022; 2(1):132-144.
https://doi.org/10.3390/geographies2010009

**Chicago/Turabian Style**

Zhang, Su, Christopher D. Lippitt, Susan M. Bogus, Tammira D. Taylor, and Renee Haley.
2022. "Mapping Construction Costs at the National Level" *Geographies* 2, no. 1: 132-144.
https://doi.org/10.3390/geographies2010009