Forest Management with Images Captured with Fish-Eye Lenses

A special issue of Journal of Imaging (ISSN 2313-433X).

Deadline for manuscript submissions: closed (31 March 2020) | Viewed by 292

Special Issue Editor


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Guest Editor
Department of Computer Systems and Software Engineering, School of Computer Engineering, National Distance Education University (UNED), 28040 Madrid, Spain
Interests: computer vision; pattern recognition; artificial intelligence; image processing; robotics
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Special Issue Information

Dear Colleagues,

The use of imaging sensors allows the extraction of useful information in different areas. For instance, they make possible a more efficient use of resources while facilitating the realization of different tasks related to forest management. Nevertheless, outdoor environments present characteristics which make the application of image processing techniques a difficult task, e.g., due to lighting conditions or partial occlusions.

To deal with the assessment of variables required for forest management and inventory, several approaches related to remote and proximal sensing techniques have been proposed. In the last decade, approaches based on terrestrial photogrammetry have also started to be developed for this purpose as an alternative to airborne laser scanning, including the use of fish-eye lenses which obtain hemispherical images. Thus, this kind of passive sensors may provide a better option in terms of energy consumption, lower deployment, and data collection costs compared to active sensors.

The emphasis of this Special Issue is placed on the fish-eye sensors oriented toward specific image processing and computer vision applications for forest management. The following is a list of the main topics covered by this Special Issue. The issue will, however, not be limited to these topics:

  • Image acquisition devices and systems in forest environments;
  • Image processing techniques: color, segmentation, texture analysis, and image fusion;
  • Computing vision-based approaches: pattern recognition, 3D scene reconstruction;
  • Stereo photogrammetry for forest inventory purposes;
  • Applications: leaf area index (LAI), tree diameter at breast height (DBH), height and volume, basal area, crown cover fraction, biomass, number of trees per ha.

Papers must present innovative methods and approaches, or novel applications of existing tools.

Prof. Pedro Javier Herrera Caro
Guest Editor

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. Journal of Imaging 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 1800 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

  • Photogrammetry
  • Hemispherical images
  • Fish-eye lenses
  • Forest management

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Published Papers

There is no accepted submissions to this special issue at this moment.
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