Empirical Assessment of Geographically Based Surface Interpolation Methods for Adjusting Construction Cost Estimates by Project Location
Publication: Journal of Construction Engineering and Management
Volume 140, Issue 6
Abstract
The accuracy of cost estimates is crucial to the success of construction projects with knowledge of project location being fundamental to the outcome of cost estimating. Location factors are commonly used to adjust construction cost estimates by project location, but these factors are not available for all locations. To date, the nearest neighbor (NN) method, based on simple, proximity-based interpolation has been used when a city lacks a sampled location factor even if this method was not empirically validated. This paper provides several contributions. First, the validity of the proximity-based method was substantially supported through the analysis of the global spatial autocorrelation of the changes in location factors from 2005 to 2009. Using two established cost index databases, it was found that there is spatial correlation between cost indexes for specific cities. Therefore, cost estimators can spatially interpolate values to understand cost indexes at places that are not listed in the database. Second, comparing different spatial interpolation techniques, including NN for how well they can interpolate cost indexes across space revealed that two alternative methods, the conditional nearest neighbor (CNN) and the inverse distance weighted (IDW) methods, lead to more accurate estimates. These findings are relevant to industry practitioners because they justify the use of interpolation as well as identify how to obtain improvements in preliminary estimates by simply replacing an interpolation method with another. Last, this study also provided preliminary evidence supporting the development of spatial prediction models for construction costs, which is an additional point of departure from the existing body of knowledge.
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References
Bivand, R. (1998). “A review of spatial statistical techniques for location studies.” 〈http://bora.nhh.no/bitstream/2330/2091/1/rober%20bivand221.pdf〉 (Oct. 25, 2009).
Bolstad, P. (2005). GIS fundamentals, a first text on geographic information systems, 2nd Ed., Eider Press, White Bear Lake, MN.
Carrat, F., and Valleron, J. F. (1992). “Epidemiologic mapping using the ‘kriging’ method. Application to an influenza-like illness epidemic in France.” Am. J. Epidemiol., 135(11), 1293–1300.
Chu, W. (2005). “Two million-scale state boundaries map layer.” U.S. Geological Survey in National Atlas of the United States, 〈http://nationalatlas.gov/mld/statesp.html〉 (Jan. 29, 2014).
Chu, W. (2006). “U.S. Cities and towns map layer.” U.S. Geological Survey in National Atlas of the United States, 〈http://nationalatlas.gov/mld/citiesx.html〉 (Jan. 29, 2014).
De Rubies, V., Tosi, P., Gasparini, C., and Solipaca, A. (2005). “Application of kriging technique to seismic intensity data.” Bull. Seismol. Soc. Am., 95(2), 540–548.
Dingman, S. L., Seely-Reynolds, D. M., and Reynolds, R. C., III (1988). “Application of kriging to estimating mean annual precipitation in a region of orographic influence.” Water Resour. Bull., 24(2), 329–339.
Elton, E. J., Gruber, M., and Blake, C. (1995). “Fundamental economic variables, expected returns, and bond fund performance.” J. Finan., 50(4), 1229–1256.
ESRI ArcMap 10.1 [Computer software]. Redlands, CA, ESRI.
Franke, R., and Nielson, G. (1980). “Smooth interpolation of large sets of scattered data.” Int. J. Numer. Methods Eng., 15(11), 1691–1704.
Gould, F. E. (1997). Managing the construction process, Prentice Hall, Columbus, OH.
Hock, R., and Jensen, H. (1999). “Application of kriging interpolation for glacier mass balance computations.” Geogr. Ann. Phys. Geogr., 81(4), 611–619.
Ito, K. (1987). Encyclopedic dictionary of mathematics, 2nd Ed., MIT Press, Cambridge, MA.
Johannes, J. M., Koch, P. D., and Rasche, R. H. (1985). “Estimating regional construction cost differences: theory and evidence.” J. Manage. Dec. Econ., 6(2), 70–79.
Journel, A. G., and Huijbregts, C. J. (1978). Mining geostatistics, Academic Press, London; New York.
Kaymaz, I. (2005). “Application of kriging method to structural reliability problems.” J. Struct. Safety, 27(2), 133–151.
Krige, D. G. (1951). “A statistical approach to some basic mine valuation problems on the Witwatersrand.” J. Chem. Metall. Mining Soc. S. Af., 52(6), 119–139.
Lee, J., and Wong, D. W. S. (2001). Statistical analysis with ArcView GIS, Wiley, New York.
Lu, G., and Wong, D. (2008). “An adaptive inverse-distance weighting spatial interpolation technique.” J. Comput. Geosci., 34(9), 1044–1055.
McCluskey, W. J., Deddis, W. G., Lamont, I. G., and Borst, R. A. (2000). “The application of surface generated interpolation models for the prediction of residential property values.” J. Property Invest. Finance, 18(2), 162–176.
Migliaccio, G. C., Guindani, M., D’Incognito, M., and Zhang, L. (2013b). “Empirical assessment of spatial prediction methods for location cost-adjustment factors.” J. Constr. Eng. Manage., 858–869.
Migliaccio, G. C., Zandbergen, P., and Martinez, A. A. (2009). “Assessment of methods for adjusting construction cost estimates by geographical location.” Proc., 2009 Construction Research Congress, ASCE, Seattle, WS.
Migliaccio, G. C., Zandbergen, P., and Martinez, A. A. (2013a). “Empirical comparison of methods for estimating location cost adjustments factors.” J. Manage. Eng., in press.
Monestiez, P., Courault, D., Allard, A., and Ruget, F. (2001). “Spatial interpolation of air temperature using environmental context: Application to a crop model.” Environ. Ecol. Stat., 8(4), 297–309.
Mueller, T. G., Pusuluri, N. B., Mathias, K. K., Cornelius, P. L., Barnhisel, R. I., and Shearer, S. A. (2004). “Map quality for ordinary kriging and inverse distance weighted interpolation.” Soil Sci. Soc. Am. J., 68(6), 2042–2047.
Oliver, M. A., and Webster, R. (1990). “Kriging: A method of interpolation for geographical information systems.” Int. J. Geogr. Inform. Syst., 4(3), 313–332.
Pietlock, B. A. (2006). “AACE international recommended practice No. 28R-03: Developing location factors by factoring—As applied in architecture and engineering, procurement and construction.” 〈http://www.aacei.org/technical/rps/28r-03.pdf〉 (Mar. 22, 2008).
Popescu, C. M., Phaobunjong, K., and Ovararin, N. (2003). Estimating building costs, Marcel Dekker, New York.
Reinsch, C. (1967). “Smoothing by spline functions.” Numerische Mathematik, 10(3), 177–183.
Shepard, D. (1968). “A two-dimensional interpolation function for irregularly-spaced data.” ACM/CSC-ER: ACM Annual Conf./Annual Meeting, Association for Computing Machinery, New York, 517.
Su, B. D., Jiang, T., and Jin, W. B. (2006). “Recent trends in observed temperature and precipitation extremes in the Yangtze River basin, China.” Theor. Appl. Climatol., 83(1–4), 139–151.
Taylor, J. R. (1997). An introduction to error analysis: The study of uncertainties in physical measurements, 2nd Ed., University Science Books, Sausalito, CA.
Trangmar, B. B., Yost, R. S., and Uehara, G. (1985). “Application of geostatistics to spatial studies of soil properties.” J. Adv. Agronomy, 38, 45–94.
U.S. Census Bureau News. (2013). “U.S. Bureau news.” 〈http://www.census.gov/const/C30/release.pdf〉 (Jan. 2, 2013).
U.S. Department of Defense (USDOD). (2005). “Unified facilities criteria design guide: Construction cost estimating.” 〈http://www.wbdg.org/ccb/DOD/UFC/ufc_3_700_02a.pdf〉 (Oct. 25, 2009).
Waier, R. H. (2006). Building construction cost data 2006, Robert S. Means Co., Norwell, MA.
Yang, W. R., Wang, R. S., Huang, J. L., Chen, Z., and Li, F. (2007). “Application of inverse distance weighted interpolation method in contaminated site assessment.” J. Appl. Ecol., 18(9), 2013–2018.
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Published In
Journal of Construction Engineering and Management
Volume 140 • Issue 6 • June 2014
Copyright
© 2014 American Society of Civil Engineers.
History
Received: Feb 25, 2013
Accepted: Jan 27, 2014
Published online: Mar 14, 2014
Published in print: Jun 1, 2014
Discussion open until: Aug 14, 2014
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