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Sustainable Agriculture and Advances of Remote Sensing

Special Issue Information

Dear Colleagues,

Over the past few decades, remote sensing technologies have witnessed tremendous improvements in sensors, platforms, and data analysis. Numerous satellite programs provide free or commercial imageries, new unmanned aerial vehicles equipped with high performing sensors are being developed, and a number of wireless sensors and types of machinery have been introduced. However, the applications of these technologies in agricultural engineering are limited and not well documented. Remote sensing technologies are efficient and cost-effective for crop production, crop detection, and crop monitoring. They are used in precision agriculture, digital farming, automation, and robotics. With the ongoing climate change, remote sensing technologies can be used to obtain information on land use/land cover as well as in subsurface. They can be used for point clouds acquisition and 3D reconstruction of crops. Free imageries provided by Sentinel and Landsat satellites can be used for leaf area estimation, field boundary, and cultivated area determination. Their precision and performance can be improved by using very high spatial resolution commercial satellites or orthophotos acquired by UAVs. In addition, navigation satellite system signals can be used in agricultural machinery control, automation, and robotics.

This Special Issue will focus on the latest advances in remote sensing technology and agricultural engineering. Authors are invited to submit original manuscripts on topics including (but not limited to): 

  • Photogrammetry for crop detection and crop monitoring;
  • Aquaculture and fisheries;
  • New materials for agriculture engineering;
  • Satellite technologies for farming and precision agriculture;
  • Fusion of remote sensing and applied geophysics for subsurface and hydrogeological modelling;
  • Crop 3D imaging and reconstruction;
  • Multispectral and hyperspectral data analysis;
  • Navigation satellite system signals for agricultural machinery control and site-specific applications;
  • Remote sensing time series data analysis for environmental impact and landscape analyses.

Prof. Dr. Dimitrios S. Paraforos
Dr. Anselme Muzirafuti
Prof. Dr. Giovanni Randazzo
Dr. Stefania Lanza
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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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

  • agricultural engineering
  • remote sensing
  • novel farming and precision agriculture
  • aquaculture and fisheries
  • fertilisation
  • crop detection and monitoring
  • satellite technologies
  • automatic control
  • unmanned aerial vehicles (UAVs)
  • image processing
  • farming by satellite
  • digital farming
  • geographic information system (GIS)
  • applied geophysics
  • climate change
  • land use/cover change
  • anthropogenic impact
  • landscape planning
  • engineering geology
  • ecological studies
  • 2D imaging, 3D imaging and reconstruction
  • machine learning
  • deep learning
  • autonomous field investigation
  • multispectral data analysis
  • hyperspectral data analysis
  • LIDAR data analysis
  • RADAR data analysis
  • aerial photogrammetry
  • crop production
  • crop detection
  • crop monitoring
  • agricultural machinery control
  • automation and robotics
  • leaf area estimation
  • field boundary and cultivated area determination
  • precision seeding
  • modeling and simulation of water table fluctuation
  • wireless sensor networks
  • drones
  • GPS
  • point clouds acquisition and analysis
  • remote sensing time series data analysis
  • environmental impact

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Appl. Sci. - ISSN 2076-3417Creative Common CC BY license