Journal of Korean Society of Forest Science (한국산림과학회지)

Korean Society of Forest Science (한국산림과학회)
권호 표지

A Comparison of Systematic Sampling Designs for Forest Inventory

  • Yim, Jong Su (Department of Forest Inventory and Remote Sensing, Faculty of the Forest Sciences and Forest Ecology Georg-August University) ;
  • Kleinn, Christoph (Department of Forest Inventory and Remote Sensing, Faculty of the Forest Sciences and Forest Ecology Georg-August University) ;
  • Kim, Sung Ho (Division of Forest Resource Information, Korea Forest Research Institute) ;
  • Jeong, Jin-Hyun (Division of Forest Resource Information, Korea Forest Research Institute) ;
  • Shin, Man Yong (Department of Forest Resources, College of Forest Science, Kookmin University)
  • Received : 2008.10.27
  • Accepted : 2009.01.21
  • Published : 2009.04.30
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Abstract

This study was conducted to support for determining an efficient sampling design for forest resources assessments in South Korea with respect to statistical efficiency. For this objective, different systematic sampling designs were simulated and compared based on an artificial forest population that had been built from field sample data and satellite data in Yang-Pyeong County, Korea. Using the k-NN technique, two thematic maps (growing stock and forest cover type per pixel unit) across the test area were generated; field data (n=191) and Landsat ETM+ were used as source data. Four sampling designs (systematic sampling, systematic sampling for post-stratification, systematic cluster sampling, and stratified systematic sampling) were employed as optimum sampling design candidates. In order to compute error variance, the Monte Carlo simulation was used (k=1,000). Then, sampling error and relative efficiency were compared. When the objective of an inventory was to obtain estimations for the entire population, systematic cluster sampling was superior to the other sampling designs. If its objective is to obtain estimations for each sub-population, post-stratification gave a better estimation. In order to successfully perform this procedure, it requires clear definitions of strata of interest per field observation unit for efficient stratification.

Keywords

Acknowledgement

Supported by : Korea Forest Service

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