Review article
Applications of Remote and Proximal Sensing for Improved Precision in Forest Operations
Bruce Talbot
orcid.org/0000-0003-1935-5429
; Norwegian Institute for Bioeconomy Research Department of Forestry and Forest Resources Hoegskoleveien 7 1430 Ås NORWAY
Marek Pierzchała
; Norwegian Institute for Bioeconomy Research Department of Forestry and Forest Resources Hoegskoleveien 7 1430 Ås NORWAY
Rasmus Astrup
; Norwegian Institute for Bioeconomy Research Department of Forestry and Forest Resources Hoegskoleveien 7 1430 Ås NORWAY
Abstract
This paper provides an overview of recent developments in remote and proximal sensing technologies and their basic applicability to various aspects of forest operations. It categorises these applications according to the technologies used and considers their deployment platform in terms of their being space-, airborne or terrestrial. For each combination of technology and application, a brief review of the state-of-the-art has been described from the literature, ranging from the measurement of forests and single trees, the derivation of landscape scale terrain models down to micro-topographic soil disturbance modelling, through infrastructure planning, construction and maintenance, to forest accessibility with ground and cable based harvesting systems. The review then goes on to discuss how these technologies and applications contribute to reducing impacts on forest soils, cultural heritage sites and other areas of special value or interest, after which sensors and methods necessary in autonomous navigation and the use of computer vision on forest machines are discussed. The review concludes that despite the many promising or demonstrated applications of remotely or proximately sensed data in forest operations, almost all are still experimental and have a range of issues that need to be addressed or improved upon before widespread operationalization can take place.
Keywords
sensors; automation; operational efficiency; forest operations; precision forestry
Hrčak ID:
190935
URI
Publication date:
1.7.2017.
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