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Use of Individual Tree and Product Level Data to Improve Operational Forestry



Details

  • Personal Author:
  • Description:
    Purpose of Review: Individual tree detection (ITD) methods and technologies for tracking individual forest products through a smart operational supply chain from stump to mill are now available. The purpose of this paper is to (1) review the related literature for audiences not familiar with remote sensing and tracking technologies and (2) to identify knowledge gaps in operational forestry and forest operations research now that these new data and systems are becoming more common. Recent Findings: Past research has led to successful development of ITD remote sensing methods for detecting individual tree information and radio frequency identification (RFID), branding, and other product tracing methods for individual trees and logs. Blockchain and cryptocurrency that allow independent verification of transactions and work activity recognition based on mobile and wearable sensors can connect the mechanized and motor-manual components of supply chains, bridging gaps in the connectivity of data. However, there is a shortage of research demonstrating use of location-aware tree and product information that spans multiple machines. Summary: Commercial products and technologies are now available to digitalize forest operations. Research should shift to evaluation of applications that demonstrate use. Areas for improved efficiencies include (1) use of wearable technology to map individual seedlings during planting; (2) optimizing harvesting, skidding and forwarder trails, landings, and decking based on prior knowledge of tree and product information; (3) incorporation of high-resolution, mapped forest product value and treatment cost into harvest planning; (4) improved machine navigation, automation, and robotics based on prior knowledge of stem locations; (5) use of digitalized silvicultural treatments, including microclimate-smart best management practices; and (6) networking of product tracking across multiple, sensorized machines. [Description provided by NIOSH]
  • Subjects:
  • Keywords:
  • ISSN:
    2198-6436
  • Document Type:
    Text
  • Funding:
    Cooperative Agreement
  • Genre:
    Journal Article
  • Place as Subject:
  • CIO:
    National Institute for Occupational Safety and Health (NIOSH)
  • Topic:
    Workplace Safety & Health
  • Location:
    North America
  • Pages in Document:
    148-165
  • Volume:
    8
  • Issue:
    2
  • NIOSHTIC Number:
    nn:20066299
  • Citation:
    Curr For Rep 2022 Jun; 8(2):148-165
  • Contact Point Address:
    Robert F. Keefe, University of Idaho Experimental Forest, College of Natural Resources, Moscow, ID, 83844-3322, USA
  • Email:
    robk@uidaho.edu
  • Federal Fiscal Year:
    2022
  • Performing Organization:
    University of Idaho
  • Peer Reviewed:
    True
  • Start Date:
    20150901
  • Source Full Name:
    Current Forestry Reports
  • End Date:
    20180831
  • Collection(s):
  • Main Document Checksum:
    urn:sha-512:a1262c4fd5e5b298a1e1f22d7be79e0a8415742f2237450324ca9afac7c2af89867630579d0e46a6b4c349489406e242cb119580cbac2e3b717b1b3090829599
  • Download URL:
  • File Type:
    Filetype[PDF - 2.56 MB ]
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