Change search
Refine search result
1 - 2 of 2
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Lidberg, William
    et al.
    Swedish University of Agricultural Sciences.
    Paul, Siddhartho Shekhar
    Swedish University of Agricultural Sciences.
    Westphal, Florian
    Jonkoping University.
    Richter, Kai Florian
    Umea University.
    Lavesson, Niklas
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Melniks, Raitis
    Latvian State Forest Research Institute Silava, Latvia.
    Ivanovs, Janis
    Latvian State Forest Research Institute Silava, Latvia.
    Ciesielski, Mariusz
    Forest Research Institute, Poland.
    Leinonen, Antti
    Finnish Forest Centre, Finland.
    Agren, Anneli M.
    Swedish University of Agricultural Sciences.
    Mapping Drainage Ditches in Forested Landscapes Using Deep Learning and Aerial Laser Scanning2023In: Journal of irrigation and drainage engineering, ISSN 0733-9437, E-ISSN 1943-4774, Vol. 149, no 3, article id 04022051Article in journal (Refereed)
    Abstract [en]

    Extensive use of drainage ditches in European boreal forests and in some parts of North America has resulted in a major change in wetland and soil hydrology and impacted the overall ecosystem functions of these regions. An increasing understanding of the environmental risks associated with forest ditches makes mapping these ditches a priority for sustainable forest and land use management. Here, we present the first rigorous deep learning-based methodology to map forest ditches at regional scale. A deep neural network was trained on airborne laser scanning data (ALS) and 1,607 km of manually digitized ditch channels from 10 regions spread across Sweden. The model correctly mapped 86% of all ditch channels in the test data, with a Matthews correlation coefficient of 0.78. Further, the model proved to be accurate when evaluated on ALS data from other heavily ditched countries in the Baltic Sea Region. This study leads the way in using deep learning and airborne laser scanning for mapping fine-resolution drainage ditches over large areas. This technique requires only one topographical index, which makes it possible to implement on national scales with limited computational resources. It thus provides a significant contribution to the assessment of regional hydrology and ecosystem dynamics in forested landscapes.

    Download full text (pdf)
    fulltext
  • 2.
    Schlyter, Peter
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Spatial Planning.
    Stjernquist, Ingrid
    Stockholm University.
    Managing Forestry in a Sustainable Manner: The Importance of System Analysis2022In: Transformation Literacy: Pathways to Regenerative Civilizations / [ed] Petra Künkel, Kristin Vala Ragnarsdottir, Springer, 2022, p. 145-158Chapter in book (Refereed)
    Abstract [en]

    This chapter examines from systems and livelihood perspectives, with Nemoral and Boreal forest zones of the Global North and Sweden as examples, how forestry may meet current and future sustainability challenges both as a traditional resource base and with respect to other ecosystem services. Previous and current forest policy/governance is briefly described against the background that Swedish forestry is based both on huge holdings by few industrial owners as well as on a multitude of small individual, often family owned, forest estates. Successful delivery against environmental objectives will require careful balancing of interests and the active participation of local forest owners. Cumulative effects of old and new societal demands on forestry and their impact on local livelihoods poses in this respect a systemic risk as economic and social sustainability often gets limited consideration. There is a need for a more synoptic and systemic analysis of how forestry is affected by multiple, partly contradictory, demands from an increasing array of stakeholders, in order to enable a move towards a biobased economy. Stakeholder-based group modelling is a potentially powerful analytic and conflict reducing approach that could help improve forestry’s contribution to the acute need to handle the climate change and current sustainability challenges.

    Download full text (pdf)
    fulltext
1 - 2 of 2
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf