A comparison of accuracy and cost of LiDAR versus stand exam data for landscape management on the Malheur National Forest

Susan Hummel, A. T. Hudak, E. H. Uebler, M. J. Falkowski, K. A. Megown

Research output: Contribution to journalArticlepeer-review

109 Scopus citations

Abstract

Foresters are increasingly interested in remote sensing data because they provide an overview of landscape conditions, which is impractical with field sample data alone. Light Detection and Ranging (LiDAR) provides exceptional spatial detail of forest structure, but difficulties in processing LiDAR data have limited their application beyond the research community. Another obstacle to operational use of LiDAR data has been the high cost of data collection. Our objectives in this study were to summarize, at the stand level, both LiDAR- and Landsat (satellite)-based predictions of some common structural and volume attributes and to compare the cost of obtaining such summaries with those obtained through traditional stand exams. We found that the accuracy and cost of a LiDAR-based inventory summarized at the stand level was comparable to traditional stand exams for structural attributes. However, the LiDAR data were able to provide information across a much larger area than the stand exams alone.

Original languageEnglish (US)
Pages (from-to)267-273
Number of pages7
JournalJournal of Forestry
Volume109
Issue number5
DOIs
StatePublished - 2011

Keywords

  • Forest management
  • Inventory
  • LiDAR
  • Silviculture
  • Stand exams

Fingerprint

Dive into the research topics of 'A comparison of accuracy and cost of LiDAR versus stand exam data for landscape management on the Malheur National Forest'. Together they form a unique fingerprint.

Cite this