Wheel rutting: preliminary investigations of soil redox potential and automated monitoring of their presence using machine learning and highresolution LiDAR data

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research

Standard

Wheel rutting: preliminary investigations of soil redox potential and automated monitoring of their presence using machine learning and highresolution LiDAR data. / Callesen, Ingeborg; Brockmann, Bo; Fischer, Lene; Magnussen, Andreas; Dam, Erik Bjørnager.

Forest Operations for the Future - Conference Proceedings. University of Copenhagen, 2020. p. 58-62.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research

Harvard

Callesen, I, Brockmann, B, Fischer, L, Magnussen, A & Dam, EB 2020, Wheel rutting: preliminary investigations of soil redox potential and automated monitoring of their presence using machine learning and highresolution LiDAR data. in Forest Operations for the Future - Conference Proceedings. University of Copenhagen, pp. 58-62, The Nordic-Baltic conference on Operations Research: Forest Operations for the Future, Helsingør, Denmark, 22/09/2020.

APA

Callesen, I., Brockmann, B., Fischer, L., Magnussen, A., & Dam, E. B. (2020). Wheel rutting: preliminary investigations of soil redox potential and automated monitoring of their presence using machine learning and highresolution LiDAR data. In Forest Operations for the Future - Conference Proceedings (pp. 58-62). University of Copenhagen.

Vancouver

Callesen I, Brockmann B, Fischer L, Magnussen A, Dam EB. Wheel rutting: preliminary investigations of soil redox potential and automated monitoring of their presence using machine learning and highresolution LiDAR data. In Forest Operations for the Future - Conference Proceedings. University of Copenhagen. 2020. p. 58-62

Author

Callesen, Ingeborg ; Brockmann, Bo ; Fischer, Lene ; Magnussen, Andreas ; Dam, Erik Bjørnager. / Wheel rutting: preliminary investigations of soil redox potential and automated monitoring of their presence using machine learning and highresolution LiDAR data. Forest Operations for the Future - Conference Proceedings. University of Copenhagen, 2020. pp. 58-62

Bibtex

@inproceedings{cbf4e33ddaa7402f857b24430e02f6dc,
title = "Wheel rutting: preliminary investigations of soil redox potential and automated monitoring of their presence using machine learning and highresolution LiDAR data",
abstract = "The aim of this study is to report preliminary results from ongoing work that seeks to a) explore the soil environment in and around wheel tracks in forest and b) to develop an algorithm that can automate the quantification of the length and depth of wheel ruts per hectare in forest.",
keywords = "Faculty of Science, forest operations, machine learning, soil impact, digital sensors",
author = "Ingeborg Callesen and Bo Brockmann and Lene Fischer and Andreas Magnussen and Dam, {Erik Bj{\o}rnager}",
year = "2020",
language = "English",
pages = "58--62",
booktitle = "Forest Operations for the Future - Conference Proceedings",
publisher = "University of Copenhagen",
note = "null ; Conference date: 22-09-2020 Through 24-09-2020",

}

RIS

TY - GEN

T1 - Wheel rutting: preliminary investigations of soil redox potential and automated monitoring of their presence using machine learning and highresolution LiDAR data

AU - Callesen, Ingeborg

AU - Brockmann, Bo

AU - Fischer, Lene

AU - Magnussen, Andreas

AU - Dam, Erik Bjørnager

PY - 2020

Y1 - 2020

N2 - The aim of this study is to report preliminary results from ongoing work that seeks to a) explore the soil environment in and around wheel tracks in forest and b) to develop an algorithm that can automate the quantification of the length and depth of wheel ruts per hectare in forest.

AB - The aim of this study is to report preliminary results from ongoing work that seeks to a) explore the soil environment in and around wheel tracks in forest and b) to develop an algorithm that can automate the quantification of the length and depth of wheel ruts per hectare in forest.

KW - Faculty of Science

KW - forest operations

KW - machine learning

KW - soil impact

KW - digital sensors

UR - https://www.skogforsk.se/english/products-and-events/other/forest-operations-for-the-future---current-rd-in-forest-operations-and-technology-in-the-nordic-baltic-countries/

M3 - Article in proceedings

SP - 58

EP - 62

BT - Forest Operations for the Future - Conference Proceedings

PB - University of Copenhagen

Y2 - 22 September 2020 through 24 September 2020

ER -

ID: 251260768