The effect of blurred plot coordinates on interpolating forest biomass: a case study

J.W. Coulston 1 and G.A Reams 2
1 Department of Forestry
North Carolina State University
Southern Research Station
Forestry Sciences Laboratory
3041 Cornwallis Road
Research Triangle Park, NC 27709
Phone 919-549-4071
jcoulston@fs.fed.us 
2 USDA Forest Service
Southern Research Station
Forestry Sciences Laboratory
3041 Cornwallis Road
Research Triangle Park, NC 27709
Phone 919-549-4010
greams@fs.fed.us

Abstract 
Interpolated surfaces of forest attributes are important analytical tools and have been used in risk assessments, forest inventories, and forest health assessments.  The USDA Forest Service Forest Inventory and Analysis program (FIA) annually collects information on forest attributes in a consistent fashion nation-wide.  Users of these data typically perform interpolations with the kriging or inverse distance weighting methods which requires the coordinates of each FIA plot.  However because of privacy issues, FIA uses two methods to manipulate plot locations to insure landowner privacy.  The influence these manipulations have on the accuracy of interpolated surfaces is unknown.  We investigated the influence by comparing actual and interpolated estimates of forest biomass created from data with manipulated coordinates for three interpolation techniques.  We found that kriging consistently under-performed the inverse distance and Thiessen polygon methods.  Overall the inverse distance method performed best.  We suggest using the inverse distance method for spatial interpolation of FIA data with blurred plot coordinates when relatively little spatial autocorrelation exists.    

Keywords: forest inventory and analysis, spatial statistics, cross-validation, Food security act of 1985

In: McRoberts, R. et al. (eds).  Proceedings of the joint meeting of The 6th International Symposium On Spatial Accuracy Assessment In Natural Resources and Environmental Sciences and The 15th Annual Conference of The International Environmetrics Society, June 28 – July 1 2004, Portland, Maine, USA.

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