Anomaly detection for analysis of annual inventory data: a quality control approach

  • Authors: Roesch, Francis A.; Van Deusen, Paul C.
  • Publication Year: 2010
  • Publication Series: Scientific Journal (JRNL)
  • Source: South. J. Appl. For. 34(3):131-137


Annual forest inventories present special challenges and opportunities for those analyzing the data arising from them. Here, we address one question currently being asked by analysts of the US Forest Service’s Forest Inventory and Analysis Program’s quickly accumulating annual inventory data. The question is simple but profound: When combining the next year’s data for a particular variable with data from previous years, how does one know whether the same model as used in the past for this purpose continues to be applicable? Of the myriad approaches that have been developed for changepoint detection and anomaly detection, this report focuses on a simple quality-control approach known as a control chart that will allow analysts of annual forest inventory data to determine when a departure from a past trend is likely to have occurred.

  • Citation: Roesch, Francis A.; Van Deusen, Paul C. 2010. Anomaly detection for analysis of annual inventory data: a quality control approach. South. J. Appl. For. 34(3):131-137.
  • Keywords: sampling, control charts
  • Posted Date: September 7, 2010
  • Modified Date: September 7, 2010
  • Print Publications Are No Longer Available

    In an ongoing effort to be fiscally responsible, the Southern Research Station (SRS) will no longer produce and distribute hard copies of our publications. Many SRS publications are available at cost via the Government Printing Office (GPO). Electronic versions of publications may be downloaded, printed, and distributed.

    Publication Notes

    • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
    • Our online publications are scanned and captured using Adobe Acrobat. During the capture process some typographical errors may occur. Please contact the SRS webmaster if you notice any errors which make this publication unusable.
    • To view this article, download the latest version of Adobe Acrobat Reader.