Digital Photogrammetry in Forestry: Opportunities, Challenges, and Future Directions

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Inventory, Modeling and Remote Sensing".

Deadline for manuscript submissions: 15 October 2025 | Viewed by 77

Special Issue Editors


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Guest Editor
Faculty of Forestry, University of Sopron, 9400 Sopron, Hungary
Interests: forestry; GIS; remote sensing; photogrammetry; laser scanning

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Guest Editor
Remote Sensing Centre, University of Debrecen, 4032 Debrecen, Hungary
Interests: remote sensing; photogrammetry; laser scanning; hyperspectral imaging

Special Issue Information

Dear Colleagues,

Digital photogrammetry is a continuously evolving, dynamically developing, and efficient tool capable of capturing detailed spatial and spectral information on forests. Thanks to drones and the latest photogrammetry software products, the application of digital photogrammetry is becoming increasingly accessible in forestry practices as well. In this Special Issue, we seek research and publications that examine, further develop, and push the boundaries of digital photogrammetry in forestry applications, including aspects such as the following:

  • Terrestrial photogrammetry, under- and over-canopy drone photogrammetry, and aircraft photogrammetry applications;
  • Data fusion, aerial photogrammetry combined with laser scanning and/or satellite remote sensing, or time series analysis;
  • Delineation of tree crowns, determination of tree heights, diameters, taper function, and curvatures of stems using aerial and/or terrestrial approach;
  • Biomass and carbon stock estimation applications;
  • Change detection and monitoring using multispectral, thermal imaging photogrammetry;
  • Topographic and forest floor mapping, including forest roads, fallen dead trees, and saplings;
  • Tree species detection from aerial and terrestrial images or from point cloud based on stem and crown shape;
  • Latest image matching, segmentation, and classification techniques and their applications, including artificial intelligence, such as convolutional neural networks (CNNs), and neural radiance fields (NeRFs);
  • Automated photogrammetry systems for forest health, disturbance, fire, visitor, and wildlife monitoring.

Dr. Kornél Czimber
Dr. Péter Burai
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • digital photogrammetry
  • terrestrial
  • airborne
  • UAV/UAS
  • stem detection
  • crown delineation
  • forest monitoring
  • image matching
  • artificial intelligence

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Published Papers

This special issue is now open for submission.
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