Using SaTScanTM spatial-scan software with national forest inventory data: a case study in South Carolina

  • Authors: Randolph, KaDonna
  • Publication Year: 2017
  • Publication Series: Scientific Journal (JRNL)
  • Source: Mathematical and Computational Forestry & Natural-Resources Sciences

Abstract

The USDA Forest Service Forest Inventory and Analysis (FIA) program makes and keeps current an inventory of all forest land in the United States. To comply with privacy laws while at the same time offering its data to the public, FIA makes approximate plot locations available through a process known as perturbing ("fuzzing") and swapping. The free spatial scanning software program SaTScanTM together with FIA data was used to examine the effects of this process and other arrangements of FIA data on the detection of hotspots of standing dead trees in South Carolina. Only 77.8%, 85.7%, and 66.7% of the hotspots identified in datasets with unaltered plot coordinates were observed when the coordinates were fuzzed, swapped, or both fuzzed and swapped, respectively. Aggregating plot-level data to census tract and county dampened the effect of fuzzing and swapping but resulted in the identification of fewer hotspots overall. Within the framework of forest health monitoring in which failing to identify a problem that truly exists can have serious repercussions, neither relying solely on fuzzed and swapped data nor aggregated data will suffice. The addition of buffer data to evaluate the stability of hotspots located near the study area boundary is recommended.

  • Citation: Randolph, KaDonna. 2017. Using SaTScanTM spatial-scan software with national forest inventory data: a case study in South Carolina. Mathematical and Computational Forestry & Natural-Resource Sciences. 9(1):1–13.
  • Keywords: FIA data, hotspot detection, point pattern analysis, SaTScan, spatial scan statistic
  • Posted Date: August 25, 2017
  • Modified Date: September 25, 2017
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