Towards Precision Forestry: Methods for Environmental Perception and Data Fusion in Forest Operations

Lari Melander

Research output: Book/ReportDoctoral thesisCollection of Articles

Abstract

Publicly available data describing forest environments has increased considerably in the past decade, mainly due to the development of the remote sensing technologies in the field. In Finland, information about tree properties and forest soil is available for the whole country with a resolution of 16m × 16m grid cells. At the same time, most of the logging in the world is performed with fully mechanized equipment. The automation level in these machines varies considerably, but the most advanced forest machines, the cut-to-length machines that are common in the Nordics in particular, are close to becoming autonomous robots. Such machines are designed for optimizing log production based on the needs of the sawmill for example, but they can also generate new information about the state of the forest, i.e., act as a forest data source. On the other hand, detailed information about the environment that the machine will encounter during the forest operations is valuable when optimizing the machine route or guiding the operator in adjusting the machine settings.

In this thesis, the interactions between the forest machine and the forest environment are studied by analyzing the distinct forest data sources together. The thesis suggests the automatic data fusion of forest data sources for collecting new forest data with forest machines during forest operations and for being able to react in advance to environmental conditions. The effect of the varying conditions between forest operations is reduced by means of the forest clusters recommended for the forests in Finland, thus making the recorded data from forest operations comparable to each other. In addition, novel measurement systems are proposed for forest machines to improve their forest environment sensing capabilities, thus further increasing the amount of collected environmental data from forest operations.

The results of the thesis show that the data fusion of forest data sources reliably enables analysis of machine and operator performance in varying environmental conditions. With the fusion approach, it was possible to identify statistically significant differences in machine signals when the forest environment changed. The proposed measurement systems for estimating the rut depth caused by the forest machine and the stoniness index of the forest ground were proved to be working solutions by the data collected in the thesis.
Original languageEnglish
Place of PublicationTampere
PublisherTampere University
ISBN (Electronic)978-952-03-1863-5
ISBN (Print) 978-952-03-1862-8
Publication statusPublished - 2021
Publication typeG5 Doctoral dissertation (articles)

Publication series

NameTampere University Dissertations - Tampereen yliopiston väitöskirjat
Volume379
ISSN (Print)2489-9860
ISSN (Electronic)2490-0028

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