Special Issue "Computation and Analysis of Remote Sensing Imagery and Image Motion"

A special issue of Computation (ISSN 2079-3197). This special issue belongs to the section "Computational Engineering".

Deadline for manuscript submissions: 9 February 2022.

Special Issue Editor

Dr. Evangelos Maltezos
E-Mail Website
Guest Editor
ICCS i-sense Group, Institute of Communication and Computer Systems, 15773 Zografou, Greece
Interests: object detection; object tracking; classification; machine learning; 3D reconstruction

Special Issue Information

Dear Colleagues, 

The technological development in the fields of image processing, computer vision, and remote sensing provides new tools and automated solutions for several applications, such as situational awareness, urban development, change detection, forest and crop monitoring, emergency response, etc. 

This Special Issue invites manuscripts that present both academia and industry research for processing the information contained into remote sensing data. As this is a broad area, there are no constraints regarding the field of application. In this context, the aim of this Special Issue is to present the current state-of-the-art methods for the computation and analysis of remote sensing data and image motion in several fields of applications.

Dr. Evangelos Maltezos
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 papers will be 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. Computation 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 1400 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

  • object detection
  • object tracking
  • classification
  • machine learning
  • super resolution
  • human pose estimation
  • motion detection
  • satellite imagery
  • UAV imagery
  • terrestrial imagery

Published Papers (1 paper)

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Research

Article
Unimodal and Multimodal Perception for Forest Management: Review and Dataset
Computation 2021, 9(12), 127; https://doi.org/10.3390/computation9120127 - 29 Nov 2021
Viewed by 202
Abstract
Robotics navigation and perception for forest management are challenging due to the existence of many obstacles to detect and avoid and the sharp illumination changes. Advanced perception systems are needed because they can enable the development of robotic and machinery solutions to accomplish [...] Read more.
Robotics navigation and perception for forest management are challenging due to the existence of many obstacles to detect and avoid and the sharp illumination changes. Advanced perception systems are needed because they can enable the development of robotic and machinery solutions to accomplish a smarter, more precise, and sustainable forestry. This article presents a state-of-the-art review about unimodal and multimodal perception in forests, detailing the current developed work about perception using a single type of sensors (unimodal) and by combining data from different kinds of sensors (multimodal). This work also makes a comparison between existing perception datasets in the literature and presents a new multimodal dataset, composed by images and laser scanning data, as a contribution for this research field. Lastly, a critical analysis of the works collected is conducted by identifying strengths and research trends in this domain. Full article
(This article belongs to the Special Issue Computation and Analysis of Remote Sensing Imagery and Image Motion)
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